Advanced Google Analytics course | Pavel Brecik | Skillshare

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Advanced Google Analytics course

teacher avatar Pavel Brecik, Web Analytics Evangelist

Watch this class and thousands more

Get unlimited access to every class
Taught by industry leaders & working professionals
Topics include illustration, design, photography, and more

Watch this class and thousands more

Get unlimited access to every class
Taught by industry leaders & working professionals
Topics include illustration, design, photography, and more

Lessons in This Class

46 Lessons (3h 48m)
    • 1. INTRO

      1:33
    • 2. 1 - Attribution INTRO

      0:48
    • 3. 1.1 - Attribution - football parallel

      1:52
    • 4. 1.2 - Attribution and traffic sources example

      3:49
    • 5. 1.3 - Attribution - available models

      3:47
    • 6. 1.4 - Attribution - Model comparison tool setup

      5:04
    • 7. 1.5 - Attribution models usage

      5:54
    • 8. 1.6 - Attribution and landing pages

      3:41
    • 9. 1.7 - Attribution and page value

      8:10
    • 10. 1.8 - Attribution and device categories

      4:58
    • 11. 2 - Platforms discrepancies - INTRO

      0:43
    • 12. 2.1 - Sessions discrepancies

      7:29
    • 13. 2.2 - Conversions discrepancies

      4:00
    • 14. 3 - Scopes INTRO

      0:35
    • 15. 3.1 - Scopes theory

      3:11
    • 16. 3.2 - Scopes and data processing

      5:26
    • 17. 3.3 - Scopes application

      8:01
    • 18. 4 Custom dimensions INTRO

      0:30
    • 19. 4.1 - Custom dimensions - what it is?

      2:35
    • 20. 4.2 - Custom dimensions examples

      13:22
    • 21. 4.3 - Custom dimensions setup

      6:53
    • 22. 5 - Custom reports INTRO

      0:31
    • 23. 5.1 - Custom reports - Explorer

      11:03
    • 24. 5.2 - Custom reports - Flat table

      6:43
    • 25. 5.3 - Custom reports - Map overlay

      4:32
    • 26. 6 Assisted conversions INTRO

      0:41
    • 27. 6.1 - Assisted conversions theory

      4:16
    • 28. 6.2 Assisted conversions GA examples

      10:41
    • 29. 7 - Events INTRO

      1:35
    • 30. 7.1 - Events theory

      3:23
    • 31. 7.2 - Events examples

      8:56
    • 32. 8 - Regular expressions INTRO

      1:05
    • 33. 8.1 - Regular expressions theory

      8:40
    • 34. 8.2 - Regular expressions examples

      5:00
    • 35. 9 - Top conversion paths INTRO

      0:40
    • 36. 9.1 - Top conversion paths - how to use it?

      12:33
    • 37. 10 - Filters INTRO

      0:44
    • 38. 10.1 - Filters application in GA

      11:32
    • 39. 11 Calculated metrics INTRO

      1:00
    • 40. 11.1 - Calculated metrics - how to set them up

      6:30
    • 41. 12 - Custom channel grouping - INTRO

      0:49
    • 42. 12.1 - Custom channel grouping examples

      12:46
    • 43. 13 - Custom alerts INTRO

      0:33
    • 44. 13.1 - Custom alerts - how to use them

      8:49
    • 45. 14 - Automation in Google sheets INTRO

      0:48
    • 46. 14.1 - Automation in Google spreadsheets - examples

      12:18
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About This Class

The course follows the previous one "Ultimate Google Analytics course + 50 practical examples" and is designed for all of you who already spent some time in Google Analytics and want to enrich your current knowledge. I assume you know how the session is defined and who/what user is :).

All external resources are available here.

The course will cover topics such as Attribution, Assisted conversions, Top conversion paths, Scopes or couple of custom things like dimensions and metrics, alerts or reports. We'll explain how and why the volume of sessions and clicks differs and if you evaluate paid campaigns from tools like Google Ads or Facebook Ads you will be surprised how misleading data you're driven by.

Meet Your Teacher

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Pavel Brecik

Web Analytics Evangelist

Teacher

My focus is especially on data-driven marketing and decision making. In ideal case explained by short stories using Google Analytics :).

I've started with Web Analytics at AVG Technologies, then I worked in the biggest Czech agency h1.cz and currently in Mall Group, where I'm responsible for analytics for the whole company. You can bribe me with smoky whisky and sour espresso. I'm based in Prague, Czech republic.

It's said data is new black gold. Instead of oil everyone can drill the data. Let's try it and make your next business decision based on data not on feeling.

See full profile

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Transcripts

1. INTRO: Hi, guys. My name is Paul Ibricic, and I'm a weapon analyst in Public Analytic Collector. The scores is designed for intermediate level of knowledge, which means all of you who know how exactly session is defined, who actually user is or you know, that brown trade has nothing in common with time. I expect you've already done simple traffic sources evaluation. Improve your website based on internal sites or data, or you at least played with tickled final data. If you're not sure about all these topics, then I recommend you to go to my first course Ultimate Google Analytics Course, plus 50 practical examples. And it will be much easier for you to understand lessons covered in this one. If all of that sounds like a basics to, then you are as right place. We'll talk about a bit. Advanced content such as attributions, assisted conversions, discrepancies between platforms, scopes, many custom things like dimensions and metrics or custom reports. The full list of lessons is below, and all of them will be shown on practical examples. You may apply instantly on your data. I chose topics I believe will have business impact, and they are based on my long term experience as an analyst and consultant. If there's anything unclear, feel free to ask during any lesson ready, so let's master it. 2. 1 - Attribution INTRO: If you've already spent some time in Google Analytics, I'm sure you've heard about attribution. It's mostly discussed when it comes to traffic sources evaluation and it's well deserved attention. I personally consider understanding attribution as fundamental knowledge because it effects more reports than just the most popular one about traffic sources. If we look on attribution as away or set off rules by which we assign credit to something, you might be surprised. But it also effects, for example, landing pages, evaluation page value or device category data, and we're going to cover all of them in blessing. 3. 1.1 - Attribution - football parallel: The first topic is about attribution. It's having a discussed recently and it's well deserved. So let's have a look on it. I would like to start with the Village. Very simple illustration, which should help us to understand what attribution X is and how exactly does it work? So let's assume we have a football team or, if you are based in the United States, a soccer team which consists off goalkeeper, couple of defenders, couple of midfielders and two strikers and the way it works, Did they have to do a combination before they want to score ago? Right? So let's do this illustration. Action starts at the goalkeeper who has the ball, and he's passing it to one of defenders. Then defender is passing Nable to meet fielders. They do a great combination. They possible to striker, and then he finally scores. So this is the way it works in a football, and it's pretty much the same in traffic sources attribution. If we would then look on the med results or much statistics, we only would see that striker number 11 scored. This is it with no credit to meet fielders, defenders or goalkeeper also did a lot of work, right? If there was no goalkeeper, no defenders or midfielders, then probably Striker wouldn't be able to score. So this is very nice. Burl off how it works when it comes to traffic sources evaluation. So police remember this one because it's very, very similar when we will talk about traffic sources. So this was very simple illustration and well, it's important to remember that only the last player who had a ball is then gets them the credit in the Met results. So that was it. And let's go to see another Pirlo off this example from the football to traffic sources attribution. 4. 1.2 - Attribution and traffic sources example: if we now switch from football to attribution of traffic sources in Google Analytics and Logan Juan. Particular example. Important to know is that it's very unlikely that users will come on Lee through one channel and then convert. And you might be surprised how complicated this converting paths are. And don't worry, we'll cover that during the lesson. So London Luke on one example. Let's assume a user is for the first time coming to your website through display campaign. Hey, saw nice banners We collect on it but did nothing through the first session. He didn't convert, and he left the website. Then, after a couple of days, he was searching for some particular search Curie in, for example, Google a clicked on your head and came against your website and did nothing. He left without doing nothing, but he signed up to your newsletter, and after another a couple of days he received the 1st 1 He clicked on it and again, did nothing leave a website without converting. And then finally, after a couple more days, hey came through organic session and he converted, and the way it works in Google Analytics, this is the parallel which is similar to football on Lee. The last channel will get the credit for the conversion. All previous ones are ignored and you might say, OK, that's not fair. And I completely agree with you on this attribution Model s called Last Click, which means only the last one gets the credit and previous ones are ignored to be more precise. Standard attribution Model in Google analytics is called last known direct click, which means that if there waas on direct session after that organic one, still organic would get the credit for the conversion. So this is the difference between last week and last. Non direct click and don't worry right now about it will get the much deeper into it. And we showed during the course advanced approaches which will help us to get closer to reality than through last non direct late model. Ah, the waist I'm talking about are about assisted conversions and top converging paths. And what is important to remember that there is no such a thing as universal attribution model which will fit to any business toe all kind of campaign to around and so on and so on . This is why it's not easy in a row goal should be to get us close as possible to reality. And now I I'm sure you agree with me. That last known direct leg is very, very far from reality. What it basically means is that if I will now go to Google Analytics account and it doesn't matter in which one you are in this course, I will again use Google merchandise store account. And right now, I'm in acquisition all traffic and source medium report, which is report. I'm sure every one of you has seen a lot of times. And listen, look on the very right side of it. If we have ah number of transactions year for particular channel, it basically means that, for example, for the 1st 1 which is Google Organic in 1000 and 41 times, this channel was last known direct leg one And then there was a conversion. So this is what it tells me. So in any report you are, you use source medium, for example, also as ah second the rhythm engine and then you see number of transaction. It tells you how many times this channel waas last norm directly one. And then there was a conversion. So there was a brief introduction to traffic sources, and right now we will look to another attribution all those that are available in Google Analytics. 5. 1.3 - Attribution - available models: Now we know how to set it up when it comes to selecting only one converting type and look back window in this video, we're going to have a look. What are available attribution models in Google Analytics. How to find it out is exactly Here s we can see here is by default pre selected last interaction attribution Models. If we cling on this drop down button, we can see that here are two for 67 pretty find attribution boulders we can play with. So, um, very nice thing Here are this illustration images which are truly amazing Even without knowing what are exact rules how attribution models work. They help you to understand it in pretty much one second. So let's have a look on it. Last in direction, as you probably know, always gives the credit to the last channel in the converting path. Last known directly is something we described in one of the previous videos. Ah, and it considers also being the direct channel after some known direct one, and if such a thing happens, it still gives the credit to the last known direct click channel. So this is a default standard model in Google analytics. Then there is Ah, I would say nonsense called last Google X clicks, which only gives the credit to the last Google at traffic. Ah, sorry. Last Google at session. So pleased. You know, they used this one awarded if possible, it doesn't make much sense. Then there is a first interaction which is exact opposite of last in direction. And it gives credit on Lee to the first general, which is almost equally Ah, an affair as this one but can be used. For example, if you will find out that your display channel is mostly in the beginning, off the conversion paths, feel free to use it. Why not? Ah, and then here are three models which divide credit for the story which divides credit for the conversion. Among all of the channels, the 1st 1 is linear, so it divides equally credit for the conversion between all the channels that occurred in conversion path. Then there is a time DK, which gives the most of the credit for the conversion to the last general than a bid last to the previous one in the least, credit to the 1st 1 And then there is last one, which is called position based, and this one gives 40% off conversion to the first channel. Also, 40% of conversion to the last general and ah, last 20% are evenly distributed between the channel that were in the middle. Ah, in the middle off the first and last channel. So these are attribution all those available in Google Analytics and we're going to play with them right now if you want to find out what is Ah, a bit deeper definition off every attribution model you think you can just click on this icon? So, for example, this one on this actually is enabling you to build your custom attribute from model, which is, uh, much more advanced technique. And please, if you want to do that, go through all the score so you will have enough knowledge to start building your own attribution models. But this gives you the details. How exactly is every attribution order built? So, yeah, feel free to click here and find out Ah, very details and that will say yes. So right now we know what it attributions. Models are available and we're going to play with them 6. 1.4 - Attribution - Model comparison tool setup: in order to play with different attribution models available in Google Analytics. We have to go from acquisition DAP from the standard reporting two conversions attribution and model Comparison tool In this video, we're going to show how to set it up correctly before we dig into analysis. So you should see something similar. What I see right now don't worry right now about channels because the first thing we have to do is is a correct set up. So the first thing is to select Onley one conversion you're using because by default it will have pre selected probably all of them which doesn't make much sense. So we should filter only the one conversion You want to look on and in the ideal case, it should be your heart convert based on which you evaluate your website performance. So, in case of merchandise store, I will only leave here Transaction Click, apply. And then there is Ah, another thing called Look back window will stop by here for a second What it is If you click here, you can see that he can use this switch from 0 to 90 days What it is. Uh, sorry, I just moved would with it. I didn't want to. Anyway, it's written here that we can select from 0 to 90 days. And what this number basically tells me is that from the day off conversion, which is ah, zero, how far in the past she got should I look on the traffic sources that occurred in one? Particulary converting both. This is what it tells me. So it could be from 0 to 90 days. I will repeat. It tells me for how long to the past should I look and consider all traffic sources that occurred in one converting bath And it's not easy to find How long should that be? Is like five days, 90 days, something in between and the results will differ based on this number. So in the there isn't isn't like one official rule that will tell us. Okay, this is your number, but I will try to give you my rule thump I'm using when I am blank with this attribution Models To find it out, we have to go to multi channel funnels report and then time like and this report will help us to find this number again. We have to do the same set up as in as in ah motile comparison tool Select only one conversion and here try to find out how many conversions occur within some period of time. But this report tells me how long it takes from the ah first session to the conversion in days. So it tells me that during the day zero, which is the same day we came for the first time. To that to the website 65 conversions occurred exactly the this way. Ah, it's day. It's took one day to the 3% of conversions, two days to one born eight and so on and so on. In my rule, thump I'm using is I'm trying to cover at least 85% off conversions and I'm taking this time like as the look back window, then in model comparison tool. So if I If I will look here on merchandise store data, I can see that there's ah if I look on the 20 to 30 look back window, it tells me that there was 17% of conversion Ah, covering more than 12 days from the day zero, which tells me that the some off off these days from the 0 to 11 is about 82% almost 83. So if I open it, if I will count two more days, that would give me 85% off conversions in total. Right? I have 65 up to the 11. There's about 82% plus doom or I'm approximately on the 85% of convergence. So this is this is ah, the first thing we have to do to find out how how long our look back window should be. So if I will now go back to attribution to the report we already seen to model Comparison Tool And I will set this to 12 or 30 days as we said so low. Okay, let's say way Goto 13. Okay. Yeah, Here we are. Here we are now we are prepared to do proper model comparison. Ah, analysis s Oh, yeah, that was it. We have it set up. And now let's go to the data and dig very deep into it. 7. 1.5 - Attribution models usage: So let's have a look what we can do with it attribution Models in model Comparison tool. Ah, the first thing I recommend you to do is to switch from multi channel grouping or from default one to source medium because sometimes the way the channels are group are purely on the Google based rules. And sometimes it creates Ah, very big other channels. So I recommended to switch to source medium and right now how to use it and what we can do with it. We can basically compare our various attribution models to each other. So I have here lost in direction and I will compare it to, for example, the first interaction just to show you how it works. And what will it do with data? So what it tells me. Basically, it tells me that if I would use a different attribution model how the volume of conversions would be assigned among channels, which means that if I would switch from the let's use here the last non direct lake which is a pretty find one and compare it to the first indirection, for example, which is probably equally wrong as this one for all channels it can make sense for some of them, but not for all of them. Ah, it was. Tell me that if I would use Ah first interaction attribution model it would. It would tell me that. Okay. Instead, off Ah, almost 1200 conversions for this channel. May Google blacks referral. You only have 966. And what? It tells me we have to interpret this information. Is this channel primarily in the beginning of the conversion path, or is it supposed to be in the end or summer in the middle? So that's the question we have to have before we start to do some action based on this data and pretty much exact same will happen with any report use if I am playing with the default wants. And I'm not in Google Analytics premium account, which has data driven model, which is from what we have available in Google right now, the closest to Dio to the reality eso if I'm not in the premium account, I'm using time in the gay, which from the experience is the closest to reality. What I have. Ah, and the bad news is that you cannot change. Ah, or said this attribution model as your refilled one. So it would recalculate all the well use off conversions for traffic sources instead of report reporting. You only can see in here, but still, it's a good good place to to go. So what I'm playing here is this one. It would tell me OK, that your ah direct by this mortal should have much more conversions that in half on. And it requires a lot of time to looking on the data, understanding what your channels are. How do you how do you communicate them, which campaign to do around there before you start to do some conclusions based on the new attribution model So, yeah, feel free to play with it. Try to find out the one that fits your business the best one on then Don't be afraid to use . For example, first Interaction attribution model. If you have a lot of brand campaigns running, feel free to switch it and only look on the brand campaigns. They're not on the old channels but, for example, yeah, for for brand campaigns might make sense to use this one. Why not? If my experience is that in the most of the conversion parts brand campaigns are in the beginning off it in the end. So this is something that should help us. Better sensitivity, how they work. But still it's far from reality. An attribute Sorry. Assisted conversions and top conversion paths. Lessons will give you the full picture, how to work with it. So don't don't try to make the conclusion based on Lee on this report without understanding the context. And as I said, wait until assisted conversions and top conversion paths report. If you want to, you can create your own custom attributions more. Don't by clicking here, and it'll show you this window based on which you can build your your new one. But please wait with it until until you finish this course. Ah, or you can import the one from the gallery, which are available online, and anyone can download them and start to use them. So yeah, this is it. You can use any acquisition. Did I mention here even as primary or secondary them engine. So we, for example, I would only filter Google CPC. I only have one line here. Yeah, that's it, and I can for example, use secondary damage in campaign. What I'm trying to show is that, for example, if you would have some specific brand campaigns, you can filter them and compare How many conversions would they have if you twitch from last non direct link to some different attribution model there is, and it can change again. It can. Different will differ a lot. A zoo can see here. The differences are like 35 for almost 40% for some of the campaigns. We have small numbers, but still the point here is to show you what you can do with it. And it's always specific for every kind of business and repeated. The probably the most important knowledge here is that there is no universal attribution model that will help you evaluate every channel and every business you have. So it requires a bit more views matching together data from model comparison toe assisted conversions and top conversant parts. So this was it. And let me know. How did it go in your case, 8. 1.6 - Attribution and landing pages: you may ask how it's attribution and lending Bages connected it ISS and let me show you pretty much the same example we were working with when it comes to traffic sources. Ah, as you know, a landing pages or every session has its own landing page, and it's always the one. And I'm sure they do, at least once tried or seen or received the landing pages evaluation, let me show you how it can be distorted by attribution and heavily distorted. Let's assume that for the first time he user is coming to our website and he is landing on a product veto page. He does nothing, leaves a website without conversion. Then, after a couple of days, he's coming back again. But this time his landing on a category page again, as in the case of Session one, he does nothing is leaving website because you were just searching. For example, for some notebook, you have another category pages. For the third time, he's coming to contact page because he, for example, wanted to see what are your opening covers. And again he's leaving without doing any action, and then finally he gets all necessary information. He got through previous three sessions, and now he's coming to your website and he is converting. And exactly as in the case off traffic sources, this conversion is Onley assigned to a home page as a landing page. So this is the way it works. You may not know about it, but but this is it. So based on this, can we say that, for example, product detail or category page doesn't work? No, we can't because every page has a different goal. And evaluating them based on conversion rate, which were often happens, is a very, very bad approach. So let me show you what I mean. If I will now go back to G A and to the report, I'm sure all of you have seen multiple times, which is a standard report in behavior side content and landing pages and the very common approaches that if we look on the landing page we evaluated based on a conversion right on that, to me is like very naive approach, as we now showed. Why is it so? There are much better metrics for evaluating lending Bages, such as bounce rate, which is much more helpful than convergent rates I would say in the case, off evaluation of landing pages, e commerce convergent rate can be more deceiving metric than helpful one. So yes, much better approach to East Lew gonna bounce rate which will kill me. How? Maney off people left website after seeing only one page on. And for those who didn't bounce, I would like to see ah, Which page was the next one, which which they went to. And this is this. I can find out by either using a secondary dimension that's next page part or by going to side usage report and then filtering their particular landing page and then seeing next page past there. So yeah, this is it. Ah, exactly. Same principle also applies here, so please keep that in mind. Next time you will evaluate Lending Bages. And as you know, every landing page has a different goal. Some of them is supposed to get the just the people to the next page. Some of them is supposed to show details about the product. Some of that was supposed to help choose a product which is a category pages and so on and so on. So this is This is based on what we shoot. Evaluate landing pages, not on Ecommerce conversion rate. So yeah, that was it. 9. 1.7 - Attribution and page value: another topic, you may ask, How is it connected with attribution? It's page value and it is, and let me show you how I assume you already know how page value is calculated. But if not, let's do a quick recap. If you If you are sure how it's calculated, feel free to skip for two more minutes. Ah, but for those who, if you are not sure, let's do this. Let's assume we have a two sessions. Or maybe what is the logic? First, logging off this metric is to tell us how much every page contributed to our told the lab revenue. And if you're not an e commerce business than not to revenue but to amount or William of Conversions you have. And how is it calculated? Let's assume we have a first session, which starts with a page A than user is viewing Page B and is leaving go upside without a convert. Then there is a session number do, which has exactly the same start user viewing Page A and Page B. And then there is a page see and conversion with the value of $100. And now let's have a look how the page value for every page will be calculated. General formula is following Ah, it's the revenue off the total revenue off all sessions in which particulate er page was viewed, divided by number off sessions in which particulate page was viewed. So if we now go to the page A. The total revenue off all sessions in which Page A was viewed IHS 100 plus zero, which is 100 and the number off sessions in which Page A was beauties, too, So 100 divided by two is 50 for be exactly the same. Total revenue off all sessions in which page a sorry Paige B. Was viewed is 100 plus zero, which is 100 divided by number off sessions in which page beavers viewed which stew and this gives me again 100 divided by two sessions, $50 for page see, it will be slightly different. Ah, the total revenue off all sessions in which Page see was viewed is 100. But the number of sessions in which page CBO's viewed is one so 100 divided by one is 100. This is why PHC has higher value and now slightly back to Dealogic. As we can see, both pages had the same start by the session, too. There was also a page see, and it ended with conversion. So the logic is that if there was no page see in the session number do there probably was also no conversion as what's in the case of Session one. So this is why page value for Page See is hired and for Page eight and page beat. So this is the logic, and now you might no, why or how beta value is distorted by attribution because it only gets the credit to the session to the pages that were Butte during the session during which conversion occurred. So hopefully you got it. If not, we'll explain it in more detail on the next flight. So let's go there. And ah, this is the illustration you already know. So let's assume that user is coming for the first time to your website Ewing pages a B C. But doing nothing living the website. Then, after a couple of days, he's coming again, viewing pages the E and half and again doing nothing. Then there is a session number three again after a couple of days viewing pages GH and I and again doing nothing. And then finally, user is coming viewing pages J, k and L and converting and what will happen You, I guess. No. Uh, all that previous nine pages from a two I will be ignored and Onley to the pages J. K and l on the page. Actually, some value will be calculated to page volumetric again. You may, you may say, OK, that's not fair. And I agree with you because what if, for example and this is very common scenario What if, for example, all these pages from a I have been your content pages, the block polls you're writing, You're spending a lot of time on it on it, And then you look on the page value and you see zero there. Can you say, Okay, they do not work. You cannot at all because viewer has viewed or so user has viewed all of them and then converting by viewing, for example, pages J. K and L, which could have been, for example, product page, category page and maybe a checkup it. So again here we can see how it is. I sit I was distorted. And now let's go to the interface to show how to work with it. Ah, for those of you who have never seen yet page value as a metric, you have to go to behavior reports, side content and all pages, and it's on the very right. You might notice that some of the pages have significantly higher page value than the others, which is quite normal. If we look on what kind of pages they are, it's basket and signing. And why is it significantly higher? It's quite normal, because if you would like to buy something, you definitely help Half go have to go through Basket page or you have to sign. And so that's quite obvious why this bait value for this particular pages is higher. But we'll know. Uh, let's have a look on the line number three, which is this page. It really doesn't matter what. Actually, this page is right now, but let's assume that was one of your content pages and you would like to see Okay, how much does this particulate er Page contributes to my total revenue or total conversions ? And how to do that? Uh, what I would do is do, ah, segmentation based on a user, and I stress the word user. What I mean by this is pardon. We have to go to segments and here, creating a new one by clicking here. I'm sorry and going to conditions. The first thing we have to select ISS switch from sessions to users because it will. They take all 90 days, users browsing history. Ah, and we want to include all the users that viewed, for example, age. Um, let's take, for example, this one. It really doesn't matter. So now we have a segment of users that they viewed this page. We have to name it and save it, and then in order to compare it or to find out how much incremental value this page half as sorry, we have to create exactly the same segment based on the user's. But exclude those users who has viewed this page, which would give us two contradictory segments in one of them. Users who viewed particular page will be included in the other one they wouldn't, and now we can compare those two segments to see whether users review this page have higher conversion rate or not. In ideal case, you should wait with this, um, approach off looking on. Ah, you on ah, particular page. Why? Can't say value but contribution to total revenue. And wait until the lesson where we will show how to use or how to build a custom report and how to create a calculating metric. Because ideal calculated metric you would use here wouldn't be standard e commerce converting right by the users conversion rate. Don't worry if you're not sure right now what it is and wait until two mentioned lessons. So, yeah, that was it. That was Ah, um, the connection between attribution on the page value. 10. 1.8 - Attribution and device categories: the last stopping regarding attribution will be about device category. This one will be slightly different because it's not that easy to measure it as the previous wants. But I want to give you an idea what I mean. Let's assume is following scenario when one user is coming for the first time to our website by a mobile device again for the second time. Also, why a mobile device, then while tablet and then finally coming on the desktop and converting. And as you know what will happen on Lee, The last device category will get the credit for the conversion which in this case is desktop and it's not that easy to measure it right now. So it will be more off a concept than the thing we can measuring Google Analytics. But what I mean by this Ah, I've seen couple of cases where it happened. Where happened Ah, this thing. There was a significant improvement in mobile experience for example, releasing a new mobile Baranova website, or changes in its responsiveness and the expectation waas a significant boost off mobile conversion rate, which is valid expectation, and I would do the same, but it didn't happen as much as it was expected. On the other hand, after doing ah bit of analysis, we found out that there was also significant increase in the desktop conversion rate, which might happen. For example, if you are on the market where people are not used to buying a mobile devices for any reason they have. It may happen that it won't be that significant increase on your money in your mobile devices conversion rate, but on the desktop, and I've seen it as I said a couple of times. So this is the concept I want to want to give you. It's not easy, easy to measure it because Google Analytics measurement is cookie based, which means that every browser and every device has a new cookie. So it's a new user, so we cannot see exactly how it works. But now we have one feature available in Google analytics that can help us to at least be closer to to reality. Let's now go to Google Analytics and show a simple think. Ah, right now I'm in the audience. More violent overview report, pardon and let's seem with it, a significant change in mobile experience. Uh, definitely makes sense to do is very, very simple thing, which I'm sure all of you did go to this report. Select metric conversion rate you release. And okay, here we have it. And they're just simply blot every device category you have in time and try to find out whether we won't spot some increase or decrease in ideal case increase of your conversion rate after particulary dates. So, for example, you had some release, and it makes sense to do is to check both mobile and desktop experience. How did it improve or not? So the the reason for that might be the case we just described a minute ago, so I'm not going to repeat it. But this is easy way to check the second way, which is available for us. It's called cross device, and, as you can see, slim better. So it's here just for a couple off months. I would say right now on, and I can't see the here because I mean the merchandise store, if they do not provide me this date down, but in your county definitely should see it. So if you go to device paths report, yeah, I can see I don't have permissions for it. You should see exactly. The sequence is similar to what we showed on a slide. The sequences off device categories and Google is doing this report based on their global cookie because they can recognize our recognize us on both off devices or basically, on all devices we have. We're least once ah, locked into our Google account. So ah, face this report Device Parks will tell you whether there is some specific sequence off devices through which users I buy are buying. So, for example, you might be able to find out whether most of the session starts or most of the users convergent paths that the proper word users conversion paths start in the mobile and finishing a desktop, or it's wise versa or it's purely random. So yeah, this will. This will give you the sensitivity, sensitivity. How much device category and attribution is also Ah, a case in your website. So let me know. How did it go and and hopefully you understand this. This concept 11. 2 - Platforms discrepancies - INTRO: I'm sure that you've seen or at least heard about, discrepancies in volume of conversions or sessions in Google analytics and at serving platforms. These discrepancies can sometimes be very huge. And the reason for that it's very simple. They just used different methodology. Let me ask you a simple question. Where do you evaluate, for example, Facebook or Google Ads? Campaigns? If your answer is interfaces of mentioned platforms, I might have a disturbing news for you. Let me show you. Why is it so? And it's all about D duplication. 12. 2.1 - Sessions discrepancies: the first interfaces, discrepancies will cower here. It's about sessions. A lot of people tends to compare two metrics, clicks and sessions as the one, and they think they should approximately be the same. And that in the real world isn't the case. Eso common scenario is that you opened a Facebook interface. Ah, then you watching them on the metric called clicks, and then you find exactly the same campaign in Google Analytics, and you're looking on the Sessions metric, and these numbers are very far from each other on you think. OK, there's probably something wrong, and it doesn't have to be. It's maybe about understanding how it works and what is the interpretation? Ah, the reason for these numbers is for for these numbers, being different is that they use a different methodology off measurement. The important thing to understand and remember is that the click and decision are measured at different time. Ah, the moment when Click is measured is actually exactly at the moment when you click on the yet where a session is measured ones you're trekking, coat is loaded and sense the first data into Google Analytics an issue. For example, try to imagine how a nowadays a lot off pop up windows with ads or some large display campaigns on the website work is that you were often do miss Click, for example on the banner because you want to close it. But the close button is very small, so you miss click and you're going to You are being redirected to the website so you were very, very instantly closing the new tap into which website is loaded. But the clique was actually measured on you close. Ah, a new tab where the session would start on the website even before a tracking code was loaded and fired, the first dating to Google analytics. So this is Ah, what mostly happens especially in the banner or this black and paint on I've seen a couple off. Examples were the difference between volume of clicks and session waas 80% Eso Yes, don't be scared. If you see such a huge number, we just have to know how to how to interpret it on the the time difference between the moment when click and the session can be measured can be really something between two and five seconds. So it's quite a long time when it comes to online experience, where it can very quickly either miss clicking on a banner or then very quickly closing a newly open taps with the sessions, which was supposed to start from the click on the Yet. So this is, Ah, brief, brief introduction to the difference between the clicks and decisions, and the differences can actually be under both sides. So there also can be more sessions than clicks. And let's have a look on the these three examples, which will tell us what is typical for for having, for example, more clicks than sessions. This is very typical for ah, display campaigns, and it's exactly the case, which we described right now. When people are doing a lot of miss clicks and they close, they basically clothes or kill the session when before it can start. So we will have a lot of clicks but significantly less sessions. This is very typical for this play campaigns if there is approximately the same volume off clicks and sessions, this is mostly typical for search campaigns, and especially if they are looking for if users are looking for general keywords like mobile phones or laptops or something like this. So this is similar four for ah, search campaigns. And if there are more sessions than clicks, which is third case, then you either are having wrong tagging, which is a very bad and it's not a pleasure to work than with this data. It basically means that you are taking more than one campaign with the same you tm tagging . So then you will see significantly higher number of sessions or you're using all you are running a very good retention campaigns. Mostly, this is mostly typical for the brand campaign. So if User, for the first time is looking for your brand, he finds it clicks and clicks on the website and four for the second time. He's coming directly by typing your websites name into the browser and pressing Enter. Still, the second session would be or the direct session would be attributed to the previous non direct traffic source. So as we now know, high attribution Works and ah, the campaign window for this lost for six months. So every following session which would be direct, would be actually a tree beauty to that non direct, such or sorry known direct traffic source and let me show you in the interface how it may look like we're in the acquisition Google as and campaigns report. And here we have a list off Google's complaint, and we have here all three examples off differences between clicks and sessions. The 1st 1 is called YouTube brand. We can see that there's almost 4200 clicks, and only or not only but but on Lee meant by having less sessions than clicks, which is 2700. So it's approximately 50,000 mawr 50 Sorry, 50% more clicks than sessions, which is typical for display Campaign, which a YouTube brand campaign is very nice example of that. Then, for example, let's have a look on the line number seven, where we have 278 clicks in 270 sessions. This is very difficult for search campaign, So let me just check if it's the case or not. Uh, uh huh, Yeah, he were. We can see the barrels campaign for various categories, like Man had had head gear, kids, women's. So yeah, that was that was, um search. Convene. And then we have a last one which is line number five, which is Google brand. It has 700 clicks and 800 sessions, so more sessions and clicks also can happen. And it's normal. We just have to understand it. Ah, and is written here. It's a brand campaign. So users for the first time probably came by looking for some Google merchandise store keyword or something like this. Then they found find it out, and for the second time, they were coming directly. But because of that campaign window that lost for the six months, every following direct session will be attributed to non direct traffic Channel two previous known direct traffic channel, which in this case will be this brand campaign. So this is, quite, ah, normal ratio between sessions and clicks for the for the brand campaigns s Oh yeah, that was it. We now understand how sessions discrepancies occur and how to understand them. 13. 2.2 - Conversions discrepancies: The second topic regarding discrepancies we're going to talk about is commercials. Discrepancies. Ah, people very often tend to compare a volume of conversions. They have an at serving platforms such as Facebook, Google ads being ads and the volume of conversions in Google Analytics. And these numbers never match, and you might be surprised how different can they be? Ah, the reason for that is that lettering, platforms and Google analytics use completely different methodology when assigning conversions. As we know from the lesson about attribution the way Google Analytics signs it is. Ah, based on last click attribution model, which means that only the last general in converting bath gets credit for the conversion. Where is in case off entering platforms hit works completely different. And let me show you how Let us human following scenario Ah, there was a click from a Facebook at and there was a conversion after this clique within 30 days, no matter how many channels Ah, there waas after a Facebook lake in the moment of conversion, Facebook conversion tracking coat will send information to Facebook interface. Hey, guys who have a conversion, we should count it. So this is the way it works. The problem becomes in a moment when there isn't only one page general or whatever eternal the days about more of them. So let's assume there was a first click from Facebook and, after a couple of days, a click from Google ads and then, in the end, click from being at and then converting. If all of this clicks, which means sessions happened within 30 days in the moment of conversion, every single one of these platforms and I repeat every single one of them since information to their interface. Hey, guys, we have a conversion. We should assign it to us. This is the way it works and let me show you now what would happen if he will try to evaluate conversions from at serving platforms? Let's assume that every click cost us $1 the revenue of this conversion waas $5. So you would open a Facebook interface and he would see their okay. I have a cost of $1.75 dollars. Then you would open Google Ads interface and you would see the same thing. Okay, there was a cost of $1 I have revenue $5 exactly the same thing in being gets, Ah, I have a cost $1 revenue, $5. If you would sum it up, you would. You would say to yourself, Okay, I have a three conversions with cost $3 every $15. Now that bad, right? And that comes a reality check. You would open the Google analytics, and he would see I only have one conversion with $75 but the same costs $3. So this is the fundamental difference between how Google analytics and how at serving platforms assigned conversion. So I do not recommend you to evaluate commercials from ed serving plate firms because they are far, far from reality, and they always assign more conversions than they actually bring you. So if, for example, your freelancer or your agency is sending you reports about conversions from at serving flat platforms, not from Google analytics, please send it back that it's far from reality and you do not accept it. So yeah, it's it's still very common. Problems shouldn't be that often as it is, but still many, many people report conversions the way we just described from the conversions platform from the answering platforms instead of Google analytics. So keep that in mind and, if you can, always always evaluated from Google Analytics. 14. 3 - Scopes INTRO: If you agree with me, that attribution is fundamental knowledge, then scopes are probably the second most important thing to understand. Without this knowledge, it's very likely that every report, custom or calculated metric you built or create will be wrong. To understand it correctly, it's necessary to know how the data is collected in G. A important thing to understand is that session is calculated metric. 15. 3.1 - Scopes theory: okay, Yes, we're going to talk about scopes. I wanted to focus right now because this is definitely the most difficult topping during the whole course. The knowledge gained here will be necessary for upcoming lessons about custom dimensions and metrics, custom reports and evens. So what's copes? Actually, our scopes characteristic off every dimension and metric we have in Google analytics or translated into more human language. It tells us for how long, in time particulary information is valid. We have three sculpt abs in India. It's user session and hit and ah, it can have multiple types like page you even or transaction, and there are three or four more, but they are used very rarely, so we won't work with them in this course on. If I go to next slide, we have here on illustration that will help us to understand what scopes are. So let's assume that we have ah, green eyed guy and every day he wakes up with green eyes, which is quite normal. Ah, every day he is varying. Ah, different T shirt. Ah, red, yellow and blue. On on. During the day, he eats three different meals, so so far quite simple. Ah, if we now try to use scopes here ah, user scope information would be here. Color off his eyes. Regardless, How many times he's waking up? He's always waking up with green eyes. Ah, session scope in this case would be color off his shirt. This information is valid for every day. So we have, ah, three information here red, yellow and blue T shirt and the hits Cope here would be, ah, meal He eats every time during the day. So it will be three different hits for every date. If we now go to Google Analytics terminology from ah real world ah, user scope them engine will be for a Gumpel browser, which is really nice in real world. It's not changing regardless how many times we come to a website. Uh, what session scope can be in G A, for example, is a traffic source. Every day I can I can come to website from a different traffic source and it's valid for the whole session. Ah, and what hit can be in Google and Electric six, for example, a page which in real world can be a meal I eat and it can change multiple times during the day or in case of G a multiple times during the session. Eso This was, I would say, pretty simple example, what scopes are about and we're going to dig much more deeper, deeper in in upcoming video. 16. 3.2 - Scopes and data processing: as we know what scopes can be from real life. Example. Let's now have Ah, closer Look, what's copes are in Google Analytics. In order to understand is properly we have to look on what is technically happening when we're sending data to Google Analytics. This is just a quick reminder what is happening once tracking code is loaded on your website, it just calling you are l that might look like this. Let's have a closer look on it and strip it. Ah, so in the beginning of it, we're sending some data to Google Analytics server. Then there is information about hits type, which in this case, is spades view. And we know it can be, for example, transaction. Or even then there is information into which g account eyes this information sent. Then there is ah important information about the client i d which is identification off a user. Ah, And I hope you all know what it consists off. If not, go to my first course home where I explained it in detail. And then there is information which page was viewed. Ah, if I simply fired Ah, important information to remember. Is that what it basically sends there is that some user has viewed some page at certain time. This is really important to remember off course. There are much more information. Sand there. Like, what was your traffic source? What was your browser? What was your device type and so on and so on. But for understanding schools, this is enough. So if we now go to another slide, we're going to talk about what are building blocks from which Google analytics, which is not nothing about huge table is built. It's built from something called hits. Ah, don't miss. Match it with type of them engine. In this example hit IHSAA ball cough information which are sent every time Tracking code is loaded. So this are are building bricks. Ah, let's assume that we have the first hit sent their Ah, where there is Ah client I d 456 which we know is the identification of a user. Ah, who viewed Page be one on 10th off, February at 10. 40 on Right now, we're going to show the full data processing flow in Google Analytics. Ah, let's assume we have Ah, a couple A couple more hates there. I'm using the different colors for different client at ease, which are users and also different colors for different pages. Ah, right now there are ah rough hits. They are not order. Nothing happened with them. We're just collecting them. The second step Google Analytics does ISS that it's ordering this hits chronologically, which means from the first time stem to the last one. So the 1st 1 is stem February than 30 and the last one Eastern February 10 45. So this is the second step. They are chronologically ordered. All of this hits this building blocks. Ah, the third face is filtering. As we all know, it's possible to filter some of the data out or in for every view or prosperity. And Google analytics ah, assumed it for purposes off this example, we only want to filter ah, hits that are coming from the pages starting with a So this first hit where where there was page be one and the 5th 1 where was also be one will not be included in this view, so we only have four hits left and the last thing or the last face in this data processing is grouping. So finally after these three phases, some of the hits are grouped into something we call Sessions, and I'm sure you all are familiar with it. So after grouping the hits into two sessions, we have a user number one who prefer will use the number one with Client I D 456 who performed a session starting at 10 32 on a page a one. Then he viewed Page 82 and that was end of the session. And then we have ah, second user with client I d want three who started to hiss session at 10 34 and also started on a page a one and then Beijing A to So this is how how data are being collected, processed and group in Google analytics. And what is important there is to remember that the building blocks always include information about client Addy, which is, ah, user scope them engine and then information about ah page, which is a hit scope dimension. Everything else is calculated, including session eso. It might be a new information for you. That session is also a calculated metric. Ah, and there is no such a thing as a session. I D tied to every hit. Its everything calculated. So please remember this one. We will need this information in next video. 17. 3.3 - Scopes application: So the last video about scopes I really use a final slide from the previous video on particulate early two groups Off Hates, which are grouped into two sessions for two users. What is important there? That there is a client I D which is Ah, user scope them engine and then ah, base. It was viewed, which is a hit. Scope them engine. Both this information are send with every hit, and I stress out with every hit there is no session idee included in hits sent to Google Analytics on This is why there can be clashes when we combine Ah different dimension scopes and it will give us the numbers that won't make much sense. Let me show you what I mean. Let's have a look on this simple table where we have all three scopes we already know use their session and hit. And for each of them we have one dimension in one metric. So there's a user scope, that mention device category, which I assume you all know it has values like Desktop Mobile and that let and the metric is users. We have a session scope them engine, which is a source medium again. I'm sure you all know it. It has well is like Google organic Google, CPC direct, non and so on in the metric sessions. And then there is a lost scope hit Ah, where the dimension is Page and demetrick iss Baidu's. And here comes Ah, the most important part about scopes. Let every use this structure where we have one user who can make multiple sessions enduring one session. Ah, he or she can make multiple hits, for example, page views. Ah, and and the way this structure works when it comes to creating custom reports or custom dimensions or custom metrics is like this. If we do, if we go from top to bottom in this structure and we combined them engines in this way, we'll never make a mistake. And the number we will see will will be the numbers we actually want to see. Ah, don't worry about the default reports you have in Google analytics because the way they are designed, they will not allow you to create invalid combination off them engines and metrics. So it only applies for custom reports which will be covered in the next lesson. So, for example, if we go from user decision, and if we look to the left, our user scope them. Engine is device category. It's quite normal and makes sense that we would like to know the number off users frump, articular device or number of sessions or number of pages. If so, if we would design our reporter this way, it would work and the data would make sense. Exactly the same would apply if we if we designed the report where primary dimension would be sourced medium and then the number of sessions or a number of page views. But for Page on Lee for the hit scope them engine, we Onley can use metric pages. This is the way it works. And this is the the structure of Google analytics. Ah, scopes and dimensions. The problematic part comes if we would design our report vice versa, which, which means bottom up. If we would use a page, our primary dimension and use sessions as a metric, unfortunately, interface would return. Return us some number, but it will make no sense. The reason for that is that there is no direct connection between hit and session sand in hits we send by loading it by loading our tracking coat. This is the way it works. So if we will design it exactly as we described with the primary them engine page and metric sessions the number we actually would see would be the number off sessions in which particulate er page was the 1st 1 And I stress the 1st 1 Exactly the same would happen if we would go in the structure, bought him up if we would use primary them engine which which is a session scope on. In our example it would be sourced medium and we would add their metric users again. Exactly the same thing would happen. You would get numbers from from G a interface, but it won't make sense. It won't be the number off users that came from particulate source, which is ah, valid information would like to know. But the technique for that a segmentation not custom report. Ah, And if you would design report this way, the number of users you would see there would be the number of users for which particulate traffic source was the 1st 1 in selected time period. So this is the way it works. You can go from top to bottom when combining them engines metrics. But you cannot go bottom up because the numbers won't make sense. There is one exception, and it's this one. If you would combine hit, scope them engine in user scope metric. So in our case it would be, ah, them engine page and metric users. So I assume your, ah, the information you would like to know would be the number of users that viewed articular page. And if you would design the report this way with Page as a primary dimensions in users s metric, it would give exactly the number you were looking for. And again, The reason for that is very simple and is described on the pictures about because in every hit sent into Google Analytics, there is information included about the page that was rude and also about the client. I d that view to this page. And as we know client I D is a user. So this is why it is so important to understand what we can and what we cannot combine in Google analytics. It happens way too often, Ah, that people don't have this knowledge and design reported. Unfortunately, returns them a numbers, but they won't make sense at all. So please go bore that mistake. Ah, And if you're now thinking about how to find out, What is the scope for particulary them engine do Very simple exercise. Uh, ask yourself a question. How often particulary information can change uring the session if multiple times. Then there is ah, hit scope and then do exactly the same for ah, ask, ask yourself exactly the same question. How often particulary information can change uring multiple user recessions. It multiple times then, is a session scope. And if there is information that that does not change in time for user than there is, ah, user scope. So this is the only way it works. And the only way to find out which scope iss for every dimension and then worry you're not alone in that you will find the link in the resource is and in description. Ah, but please always do this exercise if you will design a custom report or you will prepare on implementation of your custom dimensions and metrics which will be covered in one off upcoming lessons. So these were scopes. I know it wasn't easy, but it's fundamental knowledge once we want to go a bit further than just evaluating simple , simple traffic sources or or our device getting reports. 18. 4 Custom dimensions INTRO: when you're serious about Web analytics, sooner or later you'll find out that they were missing something. What I mean discussed in later G eight allows us to send their both custom time engines and customer tricks to enrich data We already have. This feature gives us unlimited options, and we can measure anything we want to. 19. 4.1 - Custom dimensions - what it is?: This is the lesson we're going to talk about Custom them engines and metrics s stated in their name were custom means that it's something that it's not sand by default. Tracking code to Google analytics. It means that we have to attach this information to every hit center. Google analytics if you then want you see and analyze these data in India interface. Ah, this lesson isn't about implementation. So I'm not going to show you how togethers information to ever hit send to Google analytics because this is something your G a developer should help you with. But don't worry. You'll find links on tutorials in Resource is off these lessons, So feel free to go and click there. Ah, what I'm going to show you is, by my opinion, more important part. And it's ah, how to think in terms off business and how to set this these dimensions and metrics in Google analytics. So let's do a first quick recap how data is getting to to Google Analytics Server. So here we have example off your address, which contains all information sent to Google Analytics. Ah, we already used this example in a previous lesson about scopes. So if you if you don't remember it, feel free to repeat it again. But what is important part here is the last one. Ah, where we add it to the end off your address to more parameters and the values The 1st 1 is CD want equals, have a spender which is custom them engine is or example of custom them engine and then see em. One equals 100 which is example off custom metrics. Ah, the number after CD one and after cm. Also on is something called index. Don't worry if you don't remember right now what it is. Ah, we're going to explain it later in Google Analytics. But just to give you an example, how these data are attached to to the hit, which we already know is ah, the building block from which Google Analytics table is built. This is exactly the example off it. So it's nothing complicated. And this is something you should keep on your mind during all these lessons. So this was just a brief intro to to custom them engine and metrics. And right now we're going to look on a couple of examples and information about how long everybody off every dimension is valid. 20. 4.2 - Custom dimensions examples: Let's have a look on a couple of examples off custom them engines s we know from previous lesson We have, ah, three scopes in Google Analytics hits session, new user and exactly as default. Them engines has one of them. The same applies for custom dimension. So this is important to remember because it it affect the way we will see future data in Google analytics because, ah, every damn engine or set up off every custom dimension and its scope is done in Google Analytics interface, and we will show it in the next we dio. But for now, we're going to have a look on a couple of examples. So let's start with the user scope them engines. The 1st 1 is a gender. So in a moment you will recognize that some user is either male or female. You can send this information to Google Analytics on it Will. It will be attached to all upcoming hit with this user. So can imagine couple of businesses were knowing generous, very valuable information, and the same applies to age. So in a moment, to recognize that user has particular age Ah, feel for descended there. If it makes sense to you and it can move your business. Why not to do that? Then? We have three quite similar examples. The 1st 1 congee we I p membership. So in a moment, user fulfill certain conditions that he is becoming, For example, Golden Member or a similar member. Send this information in Google Analytics. And from this moment on ah, all upcoming hits will be Also died to do his membership for her. Sorry, then, uh, another example can be repeated Customer. So once your customer buys for 1/3 or fourth time or any other time, you can mark him as a repeated customer Very similar to repeated customer can be heavy spender. So once your user buys, for example, for $5000 you can mark him as heavy spender. And why do we do that? Um, if we look on ah, loss of the last three custom dimensions examples we I remember she repeated customer and heavy spender. They are quite similar, but sand slightly different information into G A. Ah, once we will have this information in Google Analytics. We can either do custom reports, which is something we will show in next lesson. or we can do segmentation based on this data. And this is, I would say, the best value it can provide you because, for example, that you would like to know who are your golden members or who are your heavy spenders. And by who? I mean the which country or city they come from, or how old are they? Or how often the day By how often? Today with your website, through its sources do they come from, um, what are they typing into into your side side search and so on and so on in which products they are interested in. So they will help you to understand who they are and send them very, very specific offers once you know who they are. So this is why you should want one. That another example and the last one for user damn engine is acquisition source. Uh, what I mean by this, you might thing that Okay, I have acquisition data India already? Yes, you do. But not based on the user. What I mean by this is that in the moment you recognize that you some user is coming to a website for the first time and this is something you're developers should be able to do. I would store information about perfect source or medium or both of them. Oh, our keyword or campaign or ad content or any traffic source them engine and tied to user, as the users called them engine. It would help you to know which traffic source brings you the most valuable customers in terms off highest revenue per user or highest frequency off purchases and so on and so on. So it will help you to Teoh understand into which source you should put a lot of money because you know that in a long term that brings in the most valuable customers. So this this work out a couple of examples off custom dimensions. Then there is a second example off custom dimensions and ah, it's scope. This session something that became very popular recently, is information about whether a so we all know. Whether determines us on every step every day, and it also determines how people are browsing websites and how do they buy or interact in general again, your developers will be able to get this information to Google Analytics and let me give you example how it may work. Ah, I had a client who has a food delivery business, and we started to measure this information to Google analytics. Whether it's a cloudy, it's raining, it's sunny, it's hold or warm. And from the data we found out that once. And it actually makes sense that once where when there is a bad weather, which means raining and cloudy, more people are at home and more of them are ordering food, Which makes sense. On the other hand, if there was sunny and very warm, a lot of people were outside and then converting rate will swear their low. So based on this data, we started to boost our campaign. Once they're one ones that sorry once there was ah ah, very bad. Ah, weather forecast because we knew a lot of people will be at home and they will order food. On the other hand, we stopped it or almost opted ones. There was a good weather. So this is something you you would like to know on Ah, session level scope. Then there can be information about they since last session, so or sessions frequency which both of them would help you understand how frequently users are are visiting your website. And then there is, ah, lowest level or or the lowest score, which is a hit scope that mention there can be information about product availability, about payment type, article, author content section, content length or logged in user and and many, many more. Ah, there's pretty much unlimited number of options when you can send to Google Analytics s custom dimension. So ah, yeah, this will just couple of examples. And on the next slide, we're going to show for how long this information is valid. So maybe let's start with something up. Ah, users code them engine. If you remember on the previous slide, one off examples waas about Ah, we I p membership. Which means that at certain moments of time, if User, for example, buys for that no, the third or fourth time. Ah, he's gaining. Let's say Silber membership. Let's assume that in this scenario we have a one user homemade three sessions and uring ever session. He made three hits on for understanding how long this information is valid. Let's assume that during the session, number two and hit do Ah, he actually became a silver membership. Remember, How are again silver membership? Uh, what? It means that all upcoming hits from this moment on No Bost, it's on Lee for upcoming hits. All of this upcoming hits will also be ties to silver membership. So if, for example, he would come three more times and both five more products, all of them would be also ties to silver membership. So this is how it works in terms off user scope, them engine. So it's valid from the first moment we send it to Google and analytics until we did not update this value. So if, for example, uh, during the third session and again hit number two, it would buy five times more, for example, and he would gain a golden membership. So from hit number to Session three, all upcoming hits would also be tied to golden membership. So again, just to repeat how it works in terms off user scope, them engine, it starts from the very first moment we send this information, which was hit number Do your accession to So it was a sealer membership and was valid for here is not for hate do and hit three Session two and hit one session three. Ah, and from hit to session three, this user gained golden membership. So all upcoming hits from hit number two, our tides to golden membership. So this is how it works in terms off user scope, them engine. Ah, another example. I would like to show you ISS. It seems like it's a bit broken, so let me restart this slight in. Okay, here we are. Ah, let's assume that we want to know that user was either logged out are locked in a particular part off the session. So let's assume during the transaction, and what people often tend to do is to sad this information as a session. Scope them engine. Let's assume this scenario. We have a session number two and the user is coming and he's logged out. Then he's logged in during his number two, and then he is again locked out during hit number three. The way it weighed works in ah, in, um, sessions. Scope them engine is that it remembers the last known value, and then it ties its two whole session, which in this case would be the last known value is information sent with hit number three , which means that the user is logged out on it applies to all heads during session number two. So if you wanted to know whether user was logged in are logged out at articular hit, we wouldn't have this information if we would set it up a session, scope them engine. So ah, if there is a part of information or type of information which can change many times during a session, I always recommend you to send it as a hit. Scope them engine. This is the way it works. Because, for example, if you would then try to set up a segment based on all the users that were logged in and you would have sat this that mentioned as a succession scope, you actually wouldn't include this user or a session into log in sessions. So please set it up as locked as ah hits go them engine. Then you can easily segment it and see what actually happened at hit number two. Because you would know that it set at his school s hits called them engine. And you have this information tied on Lee with this hit. So we're not losing any information or it's not really written by the last known one. So please keep that in mind. It's very important because, as we will show in the next video once, we will, because we will show it in the next video when, well, so how to set it up in Google analytics. Ah, the last slide has only a couple of examples off custom metrics. There are only two types either products or hit so much easier to understand comparing to custom them engines on. In general, there are much less custom metrics used than custom them engines. So what can be examples off custom metrics? If you're an e commerce business, then definitely transaction margin. This is something you who wants to have in your G A. And it will really help you to to understand which products or which traffic channels or anything tied to ah user recession or hit scope there mentioned, generated the highest margin so heavily recommend to sum this one. Then, for example, nice example off hit scope metric can be shipping revenue or a coupon value. Ah, I'm Britisher. Both of them are straightforward to understand. What do they mean? So just to give you an idea what you can measure us as hit scope, custom metric. Ah, and then a different scope is a product scope. And, for example, it can be product margin or insurance revenue, which is something that again it's tied to mostly e commerce businesses. And and keep in mind that once you set up a metric, it's something that is changing in time, and every time you send it there, it adds to a previous value. So please keep in the mind. Sometimes you might get Ah ah, slightly slightly confused, whether it's a dimension or a metric. So keep in mind that if you send something as a metric, it adds in time. So this this waas example, these were example about custom metrics and custom dimensions, and right now we're going to show how to set it up in Google Analytics 21. 4.3 - Custom dimensions setup: Okay, guys, we're going to show what it's necessary to do if we want to use our custom, them engines and custom metrics. N g A. It's not only that, we will send these data to G A. We also have to do a quick set up on G A site. So let me show you what is necessary to do. First of all, we have to go to Admin Section, which is on the bottom left park. Okay, and here we are, every dimension and metric iss set on a property level. So this is where we have to go. And there's a custom definition Spartan. First of all, lads have a Logan custom dimension. So we click there. Ah, and here we are. We can either create a new dimension by clicking on this red button or use one of this. Let's assume we don't have any of them. So we will start with the 1st 1 which is already called we I p membership. Ah, Before we begin, this is important thing. And it's called Index. If you remember the first video of this lesson where we had ah quick reminder how server recall, which is a You are Old Dress, which is being sent to Google Analytics and represents all information that are that are then collected. There was a CD one equals, have a spender and seat, and one 100 on exactly that number after CD. And CME is index, which in this case is one it's not. Telling us that one is better than two or three is worse than two adjusted index, which is basically a primary key based on which, if we want, sent information while that server call to Google Analytics, it knows that everything that is in CD one, for example, is supposed to be measured into this dimension. Where are the values off? For example, V. I. P membership in this case. So this is what indexes used for. So if you for example didn't have any of it, it would click new custom them engine, and we would see and empty Ah, empty for uh So, first of all, we have to name it. Somehow, I recommend it to you something meaningful that even if you will look after a couple of months ago, still know what it is, what it means. So you can either call it. Ah Ah Damn Engine one. But it won't help much, right? Eso should close something meaningful. So in this case, let's assume that we will We will want to see on to collect the data about we I p membership into them Engine one. So I will call it we I p men there ship. Here we are. I'm selecting a scope which you already know how to select it and think of it because this is very important. Otherwise we can see the data, but they won't be data we were expecting. So selecting scope is a 2nd 2nd step and then you have to check this check box toe active. Otherwise the data won't be collected once we click safe. Ah, from this moment, we are able to use and sorry not to use to collect the data into Google Analytics table and then see and uses them engine in any report available in Google analytics, not Onley in custom reports, but also in a default default Once s o. This is the way we set up a custom them engine ngh. So it's not only an implementation park where your developer has to ensure that these data are sent to Google Analytics. But also, we have to set the primary key, which is called Index here. And based on this, the data will be mapped in Google Analytics table. So what your role is here is to tell your developer that okay. And custom Dimension number one, I want information about we I p membership. This is what you should tell your developer. The second thing we're going to show is to how to set up a custom metric. It's very similar to custom them engine. So again, if you don't have any of it, click on red button. New custom metric already have one example here. So again, the same principle with indexes as in ah, custom them engines case. So if I click here, the first thing we have to do is to name it. So can be either metric number one, but again do so or use something meaningful, which will ah help you to understand on the very first moment you see what it is. So let's assume I'm going to send here transaction margin on again. I'm selecting a scope which can be either hit or product, which in this case would be hit because I want to send it in the moment off transaction and this is the way I want to measure it. And then there is ah, one more field called formatting type, which gives us an option. What kind off number, Which is a metric Is it supposed to be? So it can be either in teacher, which is Ah ah, just a number that it can be currency which will then display us also Ah, currency abbreviations or dollars, pounds, euros or whatever else. Or it can be a time if you're using Ah, special kind off time metric. This is very, very advanced. So if some of you will want to use it, feel free to being me and I will explain in details. So in this case, I believes currency because it's a margin on what is also available to do. One. Setting up a customer trick is to pre filter the values that will then be showed N g A interface so we can filter it by a minimum and maximum value, which might help you to filter filter possible out flyers either extremely low or extremely high value. So feel free to do that like at least Dan and maximum, I don't know, 10,000 Just giving you an example. Uh, and again, as in previous case, you have to check this box active. Otherwise, the data are not collected than clicking safe. And And from this moment, you're collecting the data. And after a couple of days, you can He used his metric in custom reports. So this is a small difference comparing to them engines because metrics can only be used in custom reports, whereas there mentioned also in the default ones. So this is this is it. And keep in mind that the your role here is to a terrible tell er developer and index into which he or she should send you information and select proper scope off every dimension and metric. 22. 5 - Custom reports INTRO: G A is truly powerful tool, and we all know that from time to time it happens that we reach its limits when it comes to default reporting. And that's the moment when custom reports feature comes very handy. It's possible to basically build any report you want to necessary knowledge for that our scopes, which we have already mastered. 23. 5.1 - Custom reports - Explorer: Okay, guys, this lesson will be about custom reports asses. We now know how scopes works and how complicated it might be to go across schools them engine. Now we are ready to show how to set up and create custom report. There are three types of them in Google analytics, and we're going to cover all cover all three of them. So how to get there? We have to click to customization tap. And then there is ah, custom report. Step. So this is something you should see One together. As you can see, I already have one custom report here, but I'm going to build one with you from the scratch. So the way it works s you probably assume we have to click on that button, create new custom report, and ah, this is this is the interface that helps us to create it. So, first of all, it's always good idea to name it somehow. Try to choose something reasonable, so you don't have in time 20 new custom reports because it's not easy to orient it in it, then. So, for example, um, my first some report on this video will show us how could create Explorer one. Ah, this type of report is something you are very familiar with because most off the reports looks like this. So there is ah graph. And below it, there's ah, table s. So let me show you how easy it is. Uh, I always recommend it to start with selecting Ah, them engines and then metrics on Always Please keep in mind. Ah, the waist copes works. So, um, let's create a very simple one where relieves, for example, device category as them engine and then, for example, sessions s metric. So this is the very simple one. Don't worry. We'll get Teoh. Ah, a bit more complicated Report or not complicated about more granular, I would say so if I would created like this and click safe. This is what happens, right? You're familiar with how it looks and we only have here one them engine us category. In my one metric sessions, we see its development In time. We can use second the rhythm engine, which is very similar or exactly the similar ass in any default report. We can filter it if it has more lines. We can also use advanced filtering so pretty much all all off functionalities we have in default reports. We also have this one. So this was just, ah, brief example how it works. And now I'll go to at it. Ah, and I'll show you what happens once you go across scopes and you don't know how exactly does it work? So what's quite often is that people would like to know how many sessions have viewed articular page. So what they do in custom reports is that they select ah page as primary dem engine and they leave sessions as a metric, and they expect that they will see the number of sessions that view particular page. And that's exactly is not going to happen. Because, as we now know, the way Scopes works is that if we go across it and include session ah, sessions scope metric with hits called them engine, it won't give us the proper numbers. So let me show you how it is. Ah, for example, we have ah, the first page it home on Intel says that there was 29,000 sessions in period off the 1st February 28th of February, and I already have here report ah, with from from standard reporting. And I'm going to change the date range from the 1st 2 28 So we have the same one. Ah, and I assume you all know that Ah, actually, metric unique page views Tell sauce how many sessions viewed particular page. So if we go back to their custom reporting created and we we were assuming that the okay if we created in a way that we have pages primary them engine and sessions as a metric, it exactly gives us the number of sessions that view particular page, which in this case, is 29,000. But if we go to standard Report, we can see that there's a 37,000. And actually, the number we got is exactly the number off entrances, which is, in other words, number off sessions that started with Home s a landing page. So this is the number it returned us. So just please keep in mind that as you now know, how scopes works, Priest, please reflect this knowledge in building any off custom reports, any of them. So there was just an example why scopes are important. And now we're going to show where so where on this kind of report Custom report Explorer is very powerful again. I'm going to add it. But maybe information for you. Once you create any report, it saved forever until you delete it. So this is one off. Ah, positive things off that once you created, you don't have to create damn engines and metrics again. And ah, added value there iss that you can combine many data for many default reports which you normally have to click report by report to get all the data at one place. This is why custom reports exist. So you can you can get all the all the necessary data on one place so that the main purpose off it. Ah, and I'll let me show you Very nice functionality. It has a so you can see. Ah, once I created the first game engine, which was page and sessions. Now I will clean it. So we start from the scratch. Ah, very nice functionality There is that it can work as a tree. And what I mean by this is that, for example, if I will again use vice category as a primary dimension And then, for example, I would use another one, which might be, for example, operating system. You can see that, actually, it's, um, slightly more on the right side, this one, which actually means that all the data will be first group by the first dimension, which is device category. And then once, once we click on, it would only see it pre filtered by the by the dimension. Really, we choose. So you might be slightly confused right now what it is. But trust me, it's very simple to understand. So let me just create it. And then we will show how it works in once. It's once it's done. So let's And there another dime engine, for example. Um, yes. Are you not terrific? Source source Medium on another one. What can be there as a nice night? Them engine. So let's assume campaign. We can add one more so it can be up to five ah, levels off over them. Engines drill down, and now we have to select a metric. So again, keep in mind how scopes works. So I'll just use very simple one. Do their sessions and conversion rate. Yes, we're person. Right. Ah, let me find you. Hear this and I will click on Safe. It also can be pre filtered here. So if you, for example, wanted to see on Lee report that that will include ah, Windows Sessions or Google Organic only feel free to proof illiterate here, as you wish. But what I want to show is something different. If I click on it like this, let's assume we have a scenario that it would like to find out where our weak spots or weak places on the Web sites are. And this is exactly the reporter will help you to find it very, very quickly. Or, in the other words, we don't have to look for ah, week place. But maybe for ah, the opportunity place. Let me show you what I mean. Let's assume we would like to find out where is our potential for conversion rate optimization. So we would like to find a place where the conversion rate right now is not as good as it should be, or as we would expect it to be. If we now have the first level of breakdown, which is a device category we have, that's the mobile and tablet, and as you can right now see, it's a blue, which means that you can click on it and go one level deeper. Ah, we can see that in general it's 0.9% and lowest one is on the desktop, which has the most of the traffic. So this is for us. There's the first place where we know we can definitely optimize our website and what happens right now we'll click on it. We're going one level depot deeper exactly to the dimension we selected as the 2nd 1 which , if you remember what operating system on right now, we can see whether it's a global problem. If it's 0.4 for all of the up wording systems or for party particular one, and we can see that the lowest one is for a Windows, which is on me 0.1 which is like terribly low, heavily recommend Google guys to do something with it on. We can go another another level deeper, which will tell us if it's a problem off all traffic sources or only for a particular one, and we can see that the most of the traffic is from Google organic, and it has zero conversion rate. So 10,000 sessions during the month of February and not even one convert that this Ah, I would say very huge red flag for for Google guys, and they should immediately do something with it, or at least try to find out where the problem can be. So ah, you can see where exactly we are in that in that tree. So we selected desktop as, ah device category than the Windows operating system and then Google Organic on. Then we got here and can see that the Google organic is definitely a place we can do some improvement. So it doesn't take you more than I know 23 minutes to get exactly to the dimensions combination that will tell you. Okay, this is your problem. You should do something with it because there's a lot of people coming from that particular combination desktop Windows and Google organic, and they do not convert at all. So that was a very simple exercise. How to use this report and again, as I said, select up to five off that five of them engines and then, by simply clicking on it, you can very easily and and fast Get to the point eso that waas that waas Explorer custom report time. We're going to show another one. 24. 5.2 - Custom reports - Flat table: the second reports that we're going to show flat stable. So we're going to start again from the very scratched by clicking on the new custom report button and starting with again naming it somehow reasonably. So let's assume my first flat table. Ah, first thing you will definitely notice once you switch reports type from front fled stable to explorer, the fields for metric and them engines will swept. Ah, and it has its reason. I would say it would fit better also for Explorer case. So we at first like them engines and then metrics. Not wise words, huh? Ah, And as it's stated in its name, the difference is that there is only a table. So there's no graph or chart on Lee a table. And the main reason why this kind of report exists is that we should export this data and play with it outside Google analytics, either in axle or some third party visualizing to such s tableau or power bi I or anything else you're using. Let's start with typing them engines name. We're going to use the same one as in case of explorer, just to give you an idea how it looks like. And then we're show another one that I'm using very frequently and then library like it. So the first time engine was device category. The 2nd 1 operating system, the 3rd 1 was source medium in the last one was campaign and use up to five of them. Just please keep that in mind and again is in previous case. I always think about how scopes work so we don't go across some of them and getting the wrong data. And now, selecting the metric we're going to use, for example, sessions and conversion rates exactly the same one. We had an Explorer one. Let's save it to show you how exactly flat, stable custom report looks like. As you can see, this is it. So, as it's stated in its name, it's only a table, and it's not easy to orient in it or to do some analytics. So the main reason, as I said, is to explored it. You can select any off files you have here and play with it outside creative people tables or charts or graphs, or whatever else you want to on what is important to see here that, for example, here we have 365 lines, which basically means that there is 365 unique combinations off this damn engines that had at least one session during this period of time. Ah, as you can imagine, if we would add even one more them engine, we would have many, many more lines. So interface of Google Analytics has one limitation, and it's that it on Lee can give you up to 5000 lines in the interface. But don't worry if you will get to the point where there's more well used in 6000 you can still get these data through online spreadsheet and exported and play with it. We're going to show it in one off upcoming lessons, so don't worry and run right now. I want to show you something that it's more reasonable than this kind of the imagines combination, which read now doesn't make much sense to me. Just wanted to give you an idea how flat table looks like, and they use very often is that I can use, for example, a date as a dimension here, which is very often because most of the analytics is about seeing some trends. So if we don't put that they dimension here, it's not that easy to spot sound that something has changed. So would I recommend you to do is to always start from the scratch, because if you would, for example, leave some of the metrics here, it would not give you all the dimensions you want to, because it's tries to give only the one that are compatible with the metrics already selected. So it's always good starting point. You start to delete all of them and start from the from the scratch. So what I often use and I play with it is product analytics. So let's assume I would select us first damage product, then product category we are. Then I would normally select also a product brands. But since ah, Google merchandise store is not sending these data into their Google analytics account, which is a shame, guys, you should you should have this, and you should want to have this, so we'll just to give in that year. I will select the product sk you and then date, and here we are when selecting some particular product related metrics so it can be for example, unique purchases and brother revenue. Ah, he's going to use revenue because it won't give you the numbers you are looking for. Revenue is a transaction metric. Product revenue isn't material 82 products, so please keep that in mind. Let's save it, and what I then will be able to do from it is to do any combination off them engines I have here so I can see how some particular care category and brand, for example, let's assume sq is a brand eyes evolving in time because I also have a day dimension year, which is great. Eso This is something I'm playing very often. You can use many more metrics here like it's two car trade or by to detail raid ah or, ah, removed from car trade and so on and so on. So this is just a very brief example. What, what everything you can use. I think you can use up to 10 metrics here and see it in time, which is great and gives you amazing Data said you can then work with outside Google Analytics. So this is this is the difference between explorer and flat table. You might ask okay, I can also export Explorer. They? Yes, you can. But it on Lee gives you the actual them engines you see which you don't the only can see up to two dimensions. Whereas here we can see up to five of them and then exported. So this is the difference between explorer and flat table. So please use this report. It can give you a lot off a lot of useful leader. 25. 5.3 - Custom reports - Map overlay: the last custom report type, which is available in Greenville analytics. It's map overlay, so let's have a look at it again. Starting from the bird scratch and reasonable name my first map overlay. Here we go. Uh, selecting Ah, meh. Poorly as, ah report type. The first thing we can select is a zoom level. We actually can leave it up to world because in general, this report is pre configured in a way that it's clickable so we can go that weaken drill down to any dimension that is available here. So I would leave the world here, and I mentioned, can be either continents subcontinent, Country, city. So I will leave us. It is, uh, and what we have to select here is the metrics we would like to look on. So let's assume, for example, I'll select the sessions and revenue and let's click, save and see how this looks like. So hopefully all all are familiar. Familiar? What? This is so Ah, yeah. What it's basically is trying to tell us is based on any damn engine which right now is a continent. Ah, Is these lying utilizing us? Ah, which geographical part brings us the most session or any mess we have here. So if we switch from sessions do revenue again, we can see that America's are bringing $30,000. Europe. You work, for example, only 100 so on and so on. So hopefully this is easy. Easy to understand. What I think will be a bit more interesting is if we switch a primary dimension from continent to country. Right now it's Ah, Widmore changed. So we can see the United States are generating the most off the revenue. So this is something we might be interested. Ah, but maybe what we can be interested or one of the use cases might be Okay. Ah, where's country or ah? Or a city or a continent where I have the most of the sessions, for example, and which one is the second? The second top one? And it's not bringing revenue and so on and so on. So this is kind of analysis thesis. Custom report allows you to do on. As I said, it's clickable, so it allows us to drill down. So if we click here in United States will only see a map off United States and again the same visualized visualization for Okay, here we are. Yeah, for sessions and revenue. So again we can do the same exercise by trying to find out OK from which ah, state is the most remedy revenue coming from or sessions in this case and to see whether there isn't some opportunity to, For example, grow your your ah pickup points network or to start campaigns or start out of home campaigns and so on and so on. Right, So this is something I hopefully I hope you all are familiar with, and this report will help you visualize where potential for your business is. And again it's it's clickable, even more so every time something is blue in Google analytics, you can click on it and go one level deeper. Deeper, I think. Yes, you can also click on the map so you can interactive. They go through through the's geographical part On now we have a city, and even we in some countries it's available to go even deeper. So if we click on San Francisco, we know it Zigoni. So in some cities or countries, there's even the lower level. I would say Metro, but it's like I would say to granular Ah, but if it makes sense to you and you are very local business, feel free to use it. It can give you Ah great data. So feel free to use any metric you want to and play with this geographical Ah type off custom report, which is which is amazing. So this is what map overlay is and in general, all custom reports which we now can master. 26. 6 Assisted conversions INTRO: we already know that attribution isn't easy. And for some time it's probably won't be. But don't worry. There are ways how to be closer to reality when it comes to traffic sources evaluation than just looking on the last click attribution model. The ways I'm talking about are assisted conversions and multi channel funnels. Both of them give us why. Their perspective, how are traffic channels interact and give us opportunity to understand the matter and their position in convergent baths. 27. 6.1 - Assisted conversions theory: As we said, that attribution isn't easy. The data about assisted convergence will help us to understand more close to reality. Ah, view on our channels performance as we know that the last green model is very far from reality. Exactly. This data will be very helpful. Let me show you at least the bit of theory before we get into data which is necessary to understand it. So let's assume we have a color in Bath where user starts with display channel for the first time. Was it in your website? Then he or she is coming while bait search than newsletter and then finally, while Organic Channel and he is converting as we know how lost Good Channel works. Last Retribution Model works on Lee. The organic channel will get the credit for conversion. And if we speak about assisted convergence, all three previous channels will get a credit assisting one. So this play paid search and newsletter will get a credit assisting channels an organic as last gig one eso This is pretty much the whole concept. Don't worry. We'll get much deeper into it. Uh, and as you may see, just from these examples, there will be much more countings for assisting conversions than the last one, because every single channel before the last one will get the credit for it. The number we will operate very frequently when it comes to assisted conversions is the mention less number, which is defined as the ratio between assisted conversions and lastly, conversions for particulate channel. So if we look on on this play channel we have here where there waas 500 assisted conversions and 100 last click conversions. And if we put this numbers to formula, we have 500 divided by 100 which is five on this is this is the number we will work with. You may ask right now. Okay. Is this number good? Isn't that what doesn't mean how to interpret it? And this is exactly something we're going to show on the next slide. If this number is less than one and I would say significantly less than one. So about 0.5 or 0.6 that in this channel is primarily last click. So in the most of the cases is on the very end or very close to the end off converting path thistles, mostly this mostly works for retargeting or product search campaigns from nature off off this channel. Ah, Then if the number is that mentioned, last number is approximately one, which means 0.9 or 1.1, then this channel is equally last click and assisting one. Uh, this is very, very typical for organic channel or direct channel. Any of this number is significantly greater than one. Then this general is primarily assisting one, which was also the case off off a display channel from the previous life on. Even though this is hypothetical example, it's not very far from reality because a sui think off a display in most of the cases. This channel is suppose to open a convert path to get user for the first time to our website. So it's not that far from reality. Ah, I've seen multiple times being even even larger number than five eso. This was a brief theory, and the main goal off assisted conversions report will help us to understand what's position off other channels in Converting Path is in mostly opening channel. Is it somewhere in the middle, or is it mostly in the end and the goal of it will be to understand whether we really communicate the right message. Ah, why a particular channel. So this was a brief theory, and we're going to the interface. 28. 6.2 Assisted conversions GA examples: So let's have certainly assisted conversions. We have to go to conversions, Multi channel funnels into overview depth. This is the 1st 1 and will cover three of them. Overview A state conversions and the bath flank. So here we are. The first thing we have to do when we're going to explore What data we have is that we have to select Onley one conversion, the that the one we use for evaluating our business, which, in case of Google merchandise store, will be transaction. So please try to select only this one. Otherwise, your data would be quite distorted. I would say so. This is the first that we have to do. So we select transaction on Lee and click apply on. The second thing we have to set up is a look back window. What this is ah is written here is basically a period of time for how long to the past channels will be considered. What? It basically means that for example, here we have 30 days and if we assume that the conversion occurred on the 31st January, it would look back for 30 days, which means up to the first of January and we'll count all channels that were from the first general up to 31st of January. So this is well, this number number is telling us Ah, and hell to find it out. If you made it through my first cars, I expect you to know it. Ah, and if you're a nod, let's do a quick recap. We have to go to time like report. Ah, and the rule of thumb is well again. We have to select only transactions here. And the rule of thumb is to select up to or at least 85% of conversions. And then use this as salute back window, which here, in case off merchandise store is something between Let's prolong it if we see that Ah, between 12 and 30 days, they're still 22% of conversion. So if we take four or five days more, we have 85% of commercials covered, so in engaged off this account, it would be approximately 15 16 days. So this is it's I'm not saying the only approach you could have, but this is something I'm using when I'm when I'm looking on assisted conversions. So in this case, it will be 15 16 days. So if I'm going back to two overview tap, Uh, I already selected transaction as commercial, and then I shoot short on this window, do 15 days. So this is what I would do if I would do serious analysis. This is just the car. So just for the sake of having more conversions, I would leave it. I will leave it. Ah, on 30 days. But if you're working on your real data, please do this exercise before we start looking on the eso. Ah, you know why I'm leaving here 30 days. And what did they do? We have If you scroll down a bit, we will see this by chart or bubble chart, I would call it. What it tells me is what is the overlap between the channels in convergent baths, we can select up to four. Yeah, four or 54 here. Four channels to see how big the overlap piss off this report is about is to give you the sensitivity. How many channels are involved in party clerk unlearn baths? In this case, it tells me that in the almost 26% auf converting parts, there's both direct and referral in another 10% Darigan Organic, all three of them in 3% and referral. Inorganic in three point for if we also check paid search. Yeah, you can see that it's not that big. Knocked another huge. But it's the specific off these Google analytics account because obviously Google is not investing that margin bait surge because most of this traffic is brand one. So I can imagine, in case of your account, Bater will be on second or even on the first place. But what? This this bubble chart will tell you how big attribution problem is in your case s so we can see if we some of the numbers which are overlaps off these bubbles it's 25 plus 10 miles, 37 loss to 3%. So we can see that that almost 40% of conversions are when it comes to evaluation, heavily affected by last click Channel. So this is why using slightly advanced approach, which which assisted conversions are definitely makes sense because otherwise we cannot evaluate properly our channels. So this is what this report is about. So feel free to export very brushes data and now we're going to assistant assisted conversion steps, so Ah, here we are. Perfect. Uh, again. Please check whether you have selected the transaction or any other main conversions you have here and then select or sorry. Reset either prolong or 14. Your book bag window. And here we are. What this report's tells me we can use many off primary them engines. I assume we know most of them like multi choe Ah, default grouping source, medium source, medium Onley or a couple more of them, or your custom channel groupings, which is something we will cover in one off upcoming lessons. So don't worry. Ah, and all these data tell me we have five columns here, and the most important is definitely the last one. It's that the amended last number, which we explained in previous video and is the ratio between assisted and last click conversions And why is it useful? It will tell me whether particular channel iss more assisting one or the last leg one. Ah, And as we said, if it's less than one, it's mostly last big one. If it's approximately one than it's both assisting and last click. And if it's ah higher than one or the higher the more assisting it is. So, uh, here we have Ah, multi shell funnel. Ah, Challenge Grouping. Which tells me, Okay, the the most lost 31 is a direct, which in case of Google merchandise store isn't much of a surprise considering the huge amount of brand traffic coming there on. For example, the social network tells us. Okay, it's twice as much assisting channel as the last big one, which is interesting information because if you start to consider it, you have to ask by these I would say, a re evaluation of your channels whether you communicate the proper message in social networks. So if you if you, for example, know that it's mostly assisting channel Ah, try to communicate the message in social network that it's not, I would say to sell sea or two, buy, buy, buy something or give me lead or something like this. So try to have a proper communication based on what's the channel role, because this is all. All this report is about Teoh To understand was the role of your channels and based on this data, design your channels communication. There are, of course, generals. You can't do much with it like direct or organic surge. But they're still, I would say at least bait and and display and social networks where we can do much with it . So this is what this should help you to do with on the 2nd 2nd the main purpose off it. ISS Ah, basically, the stars do proper evaluation of some channels. Ah, we When we do evaluation off traffic sources, we basically shouldn't try to judge fish by its ability to climb a tree on. Let me give you a simple example. It happened a couple of years ago when I was working in agency and a colleague of mine who waas responsible for PPC campaigns. Ah came to me telling me, Okay. Ah, we have a problem because we had a campaign for car maker and I only see four conversions. Okay, so I asked him. So is it good? It's bad. It's very, very bad because my c p a is like hundreds off dollars. Eso ask them. Ok, what kind of campaigning? Loss? Ah, and he told me it was a display campaign. So So my another question waas what was the communication there. And it was purely the message in style. Off. Find out what's new for car ex wives. That so it was nothing like going to upside or arranging. Test tried nothing like this. So we opened this report and we found out okay. There was just four lastly conversions, but approximately 150 assisting wants. And that was the main reason off that campaign it wasn't supposed to like. Bring users to the website and assume that they wield Arrange a test right immediately, because it was like opening message. Okay, guys, here's something new. Come to our website, read couple more lines about it, and then maybe in 234 a week. Ah, come again and maybe arrange desk. Right. So this is what it is. And I'm sure you can find plenty of these examples also also in your data. So this is what this report is about. Andi don't only have to stay by this multi channel grouping. You can, of course, go to basically any acquisition than engine. There is. So here we have a bit more uh, Heinz 40 and you can see even larger or even much smaller numbers here. So for example, a line number seven, which is groups Google Com Referral is three times more assisting one than last leg, on the other hand, directly 0.62 only. So it's almost purely are not purely. It's 6000 conversions comparing 10,000 but it's mostly elastic channel. So So, yeah, please use this report. It has various full data which will help you to understand what's the position of your channels and help you to understand. I am helping to evaluate it based on their role. So, yeah, please use it. 29. 7 - Events INTRO: evens are something that can move your analytics abilities to a different level. As we know, all core information that are send into GE interface are that some user, which we already know is cookie. Viewed some page at certain time. Evens are specific user in directions on website that are tracked independently from page views. And if I simplify it, it can be anything that happened on a website and by anything I mean even hover over some element of website like banner or bottom. Ask your developer to implement them. We're not going to explain how to get there, but you'll find the tutorial in this lessons. Resource is It, of course, doesn't make much sense to measure everything. But there's plenty of evens that can help you better understand users behavior and what is more important to find possible problems or opportunities to name couple of them. Former error tracking to find the most problematic foreign fields category filters scrolled wrecking toe. Understand how much website content is actually consumed. Pop up window striking interactions with image gallery on product detail. Advanced car data like how users behaved once they selected some payment or delivery methods and the many, many more. Another nice evens feature is that you can set up a goal based on them or use them in segments. 30. 7.1 - Events theory: again a little bit off theory. Before we get into G A S O. There are four parameters in which we can send information as even in Google analytics. Ah, the 1st 3 of them are them engines which are category, action and label. And then there is one more parameter value, which is a metric. Which means that any information we send there should be ah, number, and it's additive in time. Ah, the 1st 3 of them are vertically ordered. We tests its reason, and it's because we should use them as, ah, tree structure. This is something we're going to show right now in the next life. So we have freedom engines and one metric, which we can send their as an extra information. So such something except page views we normally send to Google Analytics by trucking coat. Uh, this feature isn't available by the N g. A. So we have to set it up as a custom thing. Ah, but it's it's it's basically limitless. So any information you want to get there, we can. Let's assume that you would like to see which of these four buttons are most clickable, which are most attractive to users. So we have. They differ by the text on the button, which can be either by or add to cart and then by color. And this is exactly something we won't see in standard G A configuration, because we only count page views. So exactly this is the place where evens are very, very useful. And and by by using this one, we're getting to next light where I'm going to show you what I mean by three structure. This is how it normally should work. There's, for example, one category, which can have multiple actions as parameters in every action, can have multiple labels if we now switch back to the example with our blue and yellow buttons will get to something like this. So if you would like to track it, the information I would sound in the category parameter would be button click, so I would see the total numbers how many times users clicked on any button, so some up off all them together than inaction Perimeter. I will send information whether it waas by or at two cars tax so I can defer which one. It's more clickable and then in the label parameter. I would send information about the button color. So either blue or yellow eso This is what I would amend by the tree structure. It will allow us to see every information, a different level of granularity. So to recap it in the category, I would see the total number of button clicks. Then I would be able to differ between but by its two car text. And for every every button ever text I would able I would be able to see which color is more clickable. So hopefully this is pretty straightforward and easy to understand. And right now we're going t J interface. 31. 7.2 - Events examples: a set. Evens are separated, hitched up in Google analytics, and they have separated report. We have to go to behavior tap. Then there's evens. And then there are for subtypes and the most important want. It's about top evens. So let's have a look. What Google Merchandise Store website is sending their as an evens has an extremely information we did not get by default to Google analytics. Eso There are two even categories. Send their Here is something that will help us to understand what is this tree structure? If you remember between human category, action and label, which are that mentions, we can send as well with evens. And then there is even Valley, which is a metric. So let's have a closer look on the 2nd 1 which is contact us as it's quite obvious from the name they send this information to Google analytics every time someone is trying to contact them. So let's click on it, and by clicking there, we can see that we, ah went from even category them engine to even action, or where there's ah belly of this there mentioned on site Click, And if we click one level deeper we get even label and there are two will use email and phone, which is obviously information every time someone clicks either on email or the phone on the website. So this is, ah, the extra information they they send their uh I wouldn't say it's a lot and ah, let's maybe go right now to their website and I will show you what I would measure or I would like to see Ah, if I would be responsible for their data and their ah website business Improvement. So let's go there on and let's maybe try to buy something. Uh, I will go to some off category, let's assume to apparel and man's. And the first information I would like to see is how do they filter? Ah, which filters do they use the most? Which values day either input there or the use check box to see what they prefer to do to filter it? Prize is it Brand is some specific category. Ah, or how do they held the order? The result today they have is it by product name by price from lowest to highest or by the used items or what do you how they behave, but it's important for that. And based on this data, I would try to change how I how I display the items in my shop. So this is definitely the first thing I would like to see us even and Google analytics. Ah, I would have to basically in the land methodology for what to send in category even and label. But this is our job, the people who used the day that we should define what we want to see to our developer. So this is something I recommend you to do. Ah, and let's assume I I want to buy this joggers. I'm going to dio product detail and I would like to at some to card. So by clicking here Ah, I didn't feel in quantity. So there's a pop up window which, as we said, um, isn't isn't measured two g A. By default because it's a pop up window. So you are all address isn't changing changing, which means that the tracking gold isn't loaded again and we don't see the thes information in G. A. So definitely this is something I would like to see us human in Google Analytics. Ah, maybe let's at some quantity so we can go do the next step and we are getting to basket. So I like to go to basket, actually, so I'm clicking on view basket and here I am. Ah, you can see that there are two items there Onda and going to check out again. This is, Ah, pop up window, which I cannot see whether people actually go to this step or not. So another opportunity to measure and even which makes a business sense on. Let's assume that I will uncle there a dummy email address and check out as a guest. And by going there, we'll see something. I guess you are familiar with multiple form fields. A user has to feel in one's he or she wants to, uh, enter card details. I will not feel any off it. But click enter card details on again another pop up window telling me that I have to feel in Ah, billing address, company, address line down, City postal code and fault. Um, if we do not send this information as even into Google analytics, we won't be able to see ah, which form field is, for example, the most problematic one, Once we start to will be able to very easily find which one is problematic and trying to find out why is it so? Ah, so just by going very quickly through merchandise store upside there are three or four, Maybe even five examples will definitely make sense to sex, to measure as an even on if we now go back to Google Analytics and see what numbers are available connected to them engines getting or even and label there are actually two of them total and unique evens on. I assume you know what uniqueness is on. How is how is it defined in Google analytics? It means that something occurred. Maximum wants procession. So, for example, the same information is sent their multiple times. You're in one session. It's only counted, counted one in unique evens and in total evens every time we sent it there. Ah, in case off evens, it's even more specific, which means that unique is the information with sand and and by uniqueness here we mean a combination off category action and label values there. So this is what uniqueness in terms off even mean Ah, And by only having these two number. It will either help us to find out where we, for example, can have a problem in form fields because the most problematic one will have the most unique and total evens. Ah, or when? When we speak about filtering, we'll see which filter speak. People prefer the most, and only by comparing these two numbers Ah, we'll find out whether users do not do something repeatedly if they shouldn't. If it's something that we want people to you to do repeatedly on the website, then it's probably OK to see, for example, five times more total evens than unique, even depend on the even. But if now this is the indicator that there's probably something wrong with this with this , um, not day today. Tastes hopefully always Greg, but there there might be something wrong with, for example, some Fort feel foreign field. If you would see that people are unable to fill in, for example, postal code because you want them to fill it with blank space, and every time they try to go to next step, there's a validation telling that there is a wrong format. This can be example where people will constantly make the same mistake which waas by your wrong design. So this is what what evens are about? There's, um, possibility to use almost any second the rhythm engine there, like source medium. And what I find very useful is to use a secondary them engine page which will show us on which page particulary even occurred the most time. So Ah, yeah, very, very precious information. And ah, I'm sure sooner or later you're OK. You'll get to the point where seeing the data based on Lee on page views will not be enough and even are one of the first places where we can start to enhance your measurements so heavily recommended to use them, and they have a very, very huge business impact. 32. 8 - Regular expressions INTRO: regular expressions are something that can be a nice time saver. It's sequence of characters we can use, for example, for filtering. Some characters such as dot asterisk or plus have special meaning, which loss us to create search patterns. Have you ever wanted to filter only two or three traffic channels or landing pages, so you can compare them? Then, improbably, you found out that it's not that easy. I can imagine. This can be pretty painful exercise where he probably exported eight up and played with it outside G. A. Unless you know how regular expressions work, they come very handy for for such a case. And don't worry, it's quite easy to use them. There's a lot of usage off it. N g a. On filtering in reports is just one of them. Another one. A segmentation view filters especially huge i p Addresses Range or custom channel grouping 33. 8.1 - Regular expressions theory: So here we are. A regular expressions can be a huge time saver when it comes to filtering off pretty much anything in G A. It can be. Any report you use can be segment. It can be filter. We will show how to set up in any view or for any of you. Ah, some characters in the Syntex off regular expressions have a special meaning, and they help us to fill their thousands off lines we have. And it help us to filter it very effectively, to give us to use only couple of them to filter just couple of lines instead off necessary to explore, to export all these day there somewhere and then try to filter it. There is 12 off, most off used of them. There is a bit more, but I'm sure that this 12 or 14 I think I'm not sure about the exact number, but they will cover. They will help us to cover at least 90% or maybe 95% off regular expressions filtering we're going to use in Google analytics. And here they are. It's a dark asterisk blast, carrot pipe, dollar sign, parentheses, square brackets, backslash and hyphen. So Ah, let's have a look on a bit of theory before before we get to to Google and meetings reports . So here it is, the first off them that it basically means any character, including no character. So if we, for example, used this example s h dot rt, it would filter all the lines, including shirt short T shirt s age, Artie. Only because it also means no character, but it won't feel there s age double i rt because it represents Onley. Single character, not multiple of them. So this is what Doc s Then there is an asterisk. Ah, which means zero up to N repeat off previous character again. Let's let's have a look on this example s h asterisk rt would filter. Ah rt s h r T s h h rt body won't filter s h d because it means zero to an repeats of previous character so it can be also excluded. Ah, so, uh, then another one. It's a plus. This one is pretty much similar as Esther Risk with only one difference that the previous characters previous character has to be at least once. Ah included in ah result So this is the only difference. So if I If we would use S h i plus Artie, he would fill their anything shirt s h multiple times off i rt but it won't feel there s h without i rt So this is the only difference. Ah, important information here is that the combination off dot and then either asterisk or plus is a very strong combination off do special characters in the regular expressions. Ah, because it helps us to create basically unlimited long sequence of characters we can use, especially in conversions, bath reports. So it might seem it's not something useful, but trust me, if we get to the next lesson where we will talk about top conversion paths basically, without this combination or knowledge off combination of these regular expressions, it's basically impossible to do any any, like, further or simple analysis there. So, please, we're gonna remember this one. Go practice it very, very frequently there. Then there is a carrot would help us to filter only the lines that start Ah, on a specific sequence off letters. So, for example, us carrot and then car would filter us all the lines starting for example on car cars, carpets. So anything, anything off this would be filter if we would use this example. What? It won't feel there is weaker or scar because they start. They do not start on C A r ah, sequence. Then we have form or the first of them is a dollar sign, which is exact opposite off scar off. Sorry off character. So in this example, if you'd waas ah, car dollar sign, it would filter all the lines ending on car instead of beginning, which was the case of carrot. So it would filter weaker scar. But it won't filter cars or carpet. Pretty simple, right? Then there is my probably the most use one. Yeah, I can see that. And it's a pipe. I'm sure that you, at least once or twice in her ah analytics carrier, tried to you to fill their only 23 or four lines from the report. And then you finally found down that it's not that easy. Ah, and it's not that easy. Unless you know how Pipeworks on is the logical or so. If we would use this example London pipe Barry's, it would filter us all the lines containing Onley London and Paris. So yeah, this is how simple it is and we can use many more of them. It doesn't have to be only too. It can be almost unlimited number off characters there there is a limit. But I think it's ah up to 512 character. So I can't imagine you would need longer one, but but it's very rare. Then we have another one parenthesis. Ah, the way they work that if we use some sequence of characters inside them, it will filter all the lines containing these characters in exact order. This is important to remember. So even filter car. We curse car, but it won't filter KBR. So this is how it works. Then we have square briquettes, you might think, OK, this is something very similar, but the way it works is completely different. So if we if we would use the same sequence of characters, see, a are in square brackets, it would filter us all the lines containing on Lee. One of these characters please remember this one on Lee one off this character so it would fill the word because it contains are, you know, filter a goal because it contains a But it won't feel their car, area or orange because all three of them contains two or car, all three of them. So this is how square brackets works, works. It has its importance when we use a hyphen, which is something we're going to show right now on the hyphen. As a special character. Help us to create arranges s O. For example, if we would use 0-5 in square brackets, it would filter us all the lines containing at least one of these five for six numbers. So this is the way it works. And we can also use Ah, not only not only numbers, but also character from alphabet. So, for example, if we would use from J two, I dunno, de it would filter us all the lines containing at least one of these letters or sorry characters. So this is this is how the hyphen works, especially in square brackets on. Then there is the last one, which is also important to remember. And it's a backslash. If we use a backslash in front off any character, uh, help us to basically cancel its special meaning. So uh, what are how it makes sense to use it is to use it before character that has a special meaning. And if you want to cancel it, especially when we use a dark, this is the most frequent usage off it. So if we if we use this example as backslash dot com, it will filter us amazon dot com. But it won't filter us intercom because Dot is not anymore represented a special character here if we use the backslash. So ah, thesis were a couple off special characters using in regular expressions filtering, and right now we're going to the interface to show, ah, a couple of examples where it can be very, very useful knowing that such a thing as the regular expressions exist. 34. 8.2 - Regular expressions examples: Okay, guys. So we're in the interface and we're going to show couple of examples how to use regular expressions in Google analytics interface. I'm sure that if you've already spent some time in Google analytics, you've probably written hundreds or maybe even thousands off regular expressions. Uh oh. Do I mean by this? Is that every time we use this default filtering field, anything, anything we type there is automatically taken as regular expression. So this might be a new information for you. Ah, but just to give you an idea even have been here, a Google is automatically taken as a regular expression. We, of course, do not use any special character. So it returns us all the lines containing Google. But just to let you know that this is by default regular expression, syntax. So let me clean this field and show you a couple of examples. Ah, important information is that Ah, this filtering can be used in all hours. I would say every report in Google Analytics where so, for example, if I would type Google like, for example, partners, which I can seize in the online number five, it was simply return me all lines complaining either Google or partners. So this is how Pipeworks it's Ah, logical Or then for example, another one you were showing Waas carrot again. My quite favors one. So if I use something like this carrot Google, it will return me all line starting Do go on. Nothing else on Lee on Google So very frequently used in my case Ah, the opposite Off carried waas if you remember Dollar So if I would, for example type something like this I would like to see all the lines ending on Google which in this case probably will be zero results. Yeah, and that's exactly it. So, uh, let's feel there may be something that and on ah, some some tax which can be a CPC So this basically returns me all lines ending on CBC Ah, if you remember, I was mentioning that there is a very strong combination off special characters which can be dot and the asterisk or dot at plus, don't worry, we'll way we're going to show this one in the next lesson about top conversion paths where without this combination is basically impossible to do anything. It's report. Ah, In this lesson, we were on Lee Export exploring the were a simple one. Another one watts using briquettes. So let me show you what happens if I will filter or something like that. So I have a hyphen B ins in the brackets. Ah, and it will return me all the lines containing at least, And I stress at least one of these characters A, B, C or D, which is here written as a range. So as you can see everything line contains at least one off these characters. When you when you're playing with regular expressions in Google analytics, you don't have to use only one special character in one filter, so we can use basically all of them if you wish to. It doesn't make much sense to use all of them, but just to give you an idea with a very simple one. Ah, let me show you what happens if I really use Google Organics for a double end or giggle organics. Noller. It happened that it only returned me one line because I specified it in the regular expressions intact that I only would like to see the lines starting on Google organic and also ending on Google organic. So this is something you can use just two. Or this example is only supposed to show you that you're allowed to use multiple special characters. They're not only one of them, so feel free to play with it. It will take you some time to get familiar with it. But I'm sure it's a huge time saver. And it'll help you to filter thousands or maybe tens off thousands off lines very effectively and very easily to get only couple off lines, which are necessary at the moment for you. So Ah, let's go to to next lesson about about stop conversion paths where we'll show on much advanced techniques or usage off regular expressions, So see you in a minute. 35. 9 - Top conversion paths INTRO: Yes, we know what regular expressions are and how to use them. Top converging paths is exactly the report where this knowledge is almost mandatory. The data there can help us understand which traffic sources interact together and direct is truly direct here. What I mean by this is that it's not over return by previous known direct traffic source. It contains nice additional data about precise could learn path, and you might be surprised how complicated they can be. 36. 9.1 - Top conversion paths - how to use it?: Okay, guys. So this lesson will be about about top convergent baths. We have to go to conversions, multi channel funnels and then to top conversion paths. So here we are, on what? This report is about to tell us how complicated some convergent paths might be. And you might be surprised how sometimes complicated they are. But the business reason off this data is to have much better view how particulate er channels interact with each other and how often they are in some commercial baths. This is what it is about. So the first thing we have to do is again too. Select Onley. One goal which in this case, would be transaction if you're not in e commerce business than your hard goal Ah, then selecting the boss length Ah, I have a recommend you to select two or more because if you would also select one than then there will be. Only most of the channels were most of the conversion parts. Would there be with only one channel and this isn't much of an extra information we can extract from from this data on again, you can play with look back window, which you already know how to use it based on the time lack report. So this is the basic set that we have to do. Ah, you might bother. There are pretty fine conversion segments like lost interaction is paid. Advertising first direct first organic and so on and so on. Feel free to use them or feel free to to create your new one. But as we now know how regular expressions work, it's fairly easy to create all of this in one report without necessity using a segment. So, uh, let's scroll down a bit and what we see here your your default report would look like this because you would have ah, multi channel final grouping bath pre selected, which only works with values on. I would say that the magic happens once we switch it to source medium path and then start to, for example, your second every damn engine. So one of these data tell me they tell me how many sessions have their bean and what was their traffic source for particulary volume of convergence. So ah, line number one tells me that 808 124 conversions ah were by the conversion bath where direct non was there twice. So user came twice to to our website and then converted. Ah, the second uh yeah, the second top conversion Bath Waas Ah, pretty much the same. But the user came three times. Why Direct channel and so on into one. And you can see that there is 881 unique convergent pots and I stress unique onward and boss. So that's a lot on I would say 5 5005 and 1/2 1000 conversions for period off. How long? I have four months. It's not a lot, so I can imagine that if you if you're in ah midsize business, I can imagine you have tens off thousands of conversions. So it wouldn't be a surprise for me if you would see here like thousands off unique converting bots on how to work with it. Ah, very simple thing you can do if you, for example, would like to find out in how many conversion baths particular channel lost. So let's just practice a regular expressions and see, for example, how many times Google organic was in a coma and bath. So right now I'll get a zero because I about this. So here we are. I can see that Google Organdy was in 886 converting path no matter whether on the beginning , in the end or in the middle, this is the information I can get from it. Ah, as I said, it's very nice to practice regular expressions here, so the 1st 1 would be on How many times was Google organic as the first general? Exactly the 1st 1 So by using this, we can get it in from 886. Convergence in 573 was exactly in the beginning. The first General eso compared to cities conversions, these are enriched information we have. So we don't only know that it was assisting. We know that in 500 or almost 600 conversions, it was exactly the 1st 1 So we know that it's ah, I would say opener or open their off conversion path. So we're important information. Ah, In this account, I do not have much of a bait data or paid campaign, so we have to work with what we have. But for example, another opposite case might be to see How many times is Google Organic Lots? General. So it only 101 130 cases. So it's mostly in the beginning. That's important information. If you find this about one of your channels, it's mostly opener. So so try to think twice about it. Whether you communicate, they're the content or the message you have there as an opening message. It's not to sales. See, it's not trying to push your users to buy or to give you a lead directly because it's mostly in the beginning off their decision making process. So this is the way you should think about it on If we, for example, would like to see how many times is Google Organic in the middle? Which means some something is before and something is after it. We can play with with regular expressions. If you remember, I I said that there is a very strong combination off two characters, and it's a dot and asterisk, which, if I would ah, not before it. I would like to say OK, I only would like to see conversion paths where there is something before Google organic, and if I used the same one after it and press enter. Uh, you might expect that I would get all the lines or a Google Google organic is in the middle , but I don't And the reason for that is very simple. I have the same number, 886 conversions, and the reason for that is that the dog also represents no character. So if I use regular expression like this with a daughter nest Eriks in the beginning and in the end it's exactly the same. If I would only use Google organic, nothing else. So if I would like to get this information number off conversions where giggle organic will somewhere in the middle Ah, I have to slap, it's the risk for loss work. Hopefully, it will be, Yeah, Seems like it is so in 227 conversions Google or getting lost somewhere in the middle, which means something was before and something was after, which results off this filter confirms. So So this is this is a very simple thing, how to play with it, how to position your channel, and the second I would say and probably the most business value can get from from this data is to find out with which channels. For example, Google Organic is in the most cases with. So if I will go back and on Lee, I'm here Google Organic Press enter. I can see that just just visually looking on it, that it's quite often also a direct there. So let's have a look from for how maney converging paths, this is a better and how to do that again. Regular expressions. If I would look, use Google Organic, then dot that's the risk, which means okay, and there's a Google organic. Then there can be anything. It doesn't matter how long or four it is if it's one character or thousands of characters. And if I will type direct and fresh center, I will see that from almost 900 cases in almost 700 cases, these two channels are in this exact order, which means that it's always Google organic before that. Right now, try to imagine that both off these channels are paid and you can easily affect them by boosting or stopping them. How important information it is quite often happens that you would only find out OK, Google Organic. It's assisting Channel. I should invest a lot in it. Let's assume it's not a Google or gunning, but it's, Ah, this play campaign on you would expect if you boost Ah, there's display campaign. It would also boost the sales because it will assist a lot. Uh, and it doesn't have to happen because you you would miss information that if there is a Google organic than in 90% of converting parts, there's also direct which, let's assume, is also some paid channel. So if you would do this kind of ah ah, performance budget experiments. What would be my advice for you if you find such a combination? I would also almost called it as a marriage between Google or Gaining and Aragon. You can't boost only one of them because you can see that they they are naturally both in converting box. So this is this is what you should do with this with this report trying to find a smartest possible about the position of your channels and and with with channels they do interact together. Eso This was This was the 1st 1 on If we, for example okay, maybe step back the way we use regular expression here is that we defined that piece. Two channels Google organic and direct have to be in this order. So Google, beginning in the beginning and then somewhere after it doesn't have to be directly. But after it there is a direct. So if we, for example, would like to find out in how Maney conversion paths are both of them. But it doesn't matter in which order Ah, we basically have to enrich it. This regular expression and it will be following. So it's the logic is very simple. I will just do the same thing as I have here. But I will swept the channel. So the first thing is I will use a pipe which is logical or no. And now I little type direct and then Google Organics. I hope you have it. I didn't exactly the same thing that swept the channels. Any five press enter, you can see that from 900 conversions in almost 800 which is almost 90% of cases. All both these channels are together. So this is what this report is all about, right? Looking for for were very clear. Bet earns between traffic channels and if you are trying to goose that some of them you have to boost not maybe not only one of them, but sometimes maybe two or even three off them. Based on this data and you're not limited only to use source medium, you also can use any of you tm ah parameters. There are so source medium campaign at content or keyword Ah, or a bit more which are hidden by this acquisition. Drop down. Eso can be, for example, lending page, which can be important there. Like I would say, you have very important information, but it was required to probably export this data and play with it outside Google Analytics . Ah, or many more Google ads. But on league lads Ah, them engines here. So yeah, this is this is what this report is all about. Try to find out what the position off every channel with which with which other channels and it interacts with on. Then try to play with your budget. Once you get to the point that you lost going is not enough for you. And also assisted convergence is not enough for you. Things will give you I would say more complex view how your channels are in converting parts. So good luck with that and let me know. How did it go 37. 10 - Filters INTRO: correct and clean data. A solid foundation for every analysis and filters help us to build the solid foundation by including or excluding part off the date. The very basic filter every account should have is exclusion of your internal I P addresses . This is definitely the most common filter used, but there are many more like including only certain subdirectory or sub domain. And I've seen couple of use cases where clients wanted to include Onley, internal traffic or excluding robots identified in data G A couldn't filter automatically. 38. 10.1 - Filters application in GA: so filters affect the data Web or then work in Google analytics. So this is why it makes sense to know how exactly filters work, what options we have, and it's important to use them wisely. The gold is lesson isn't to tell you not to use them. It's exactly to tell you to use them because you just don't want to have distorted data. And this is why filters are very handy. So if we want to, uh, pre filter something either not going or going to particle Irv, you and I stress view. Ah, we have to set it up for every view. First of all, we have to go to any in section on the left bottom corner and then here we are. So let's go to the filter Stap and we should see something like this a Z You can see I already have here five filters I'm using for my home sort not for my home. Ah, for my website. And if you want to create a new one and this is something I'm going to show you how to build it from the scratch. You have to click on this right about at filter If you can't see it, you don't have sufficient permission. So we have to ride the org a Adam into to add it to or asked him to create a new filter. So if you see it, you're lucky guys, because you can follow this lesson. So let's do this by clicking here. You should see something like this, which is a simple window allowing us to create a filter. There are two types of them. First off all makes sense to name it again. Use some, think reasonable. Not as I do my filter. Ah, a recommended to use something that will be easy to recognize or understand. Want to get back to it after a couple of months while this filter is supposed to do Because it's possible to create very advanced filters here. So yeah, just do something reasonable. Uh, do filter types we have here. First of them are pretty find. Ah, the basic quantify air we use is that we can either exclude or include something in a view . So this is the 1st 1 Then we have the four basic ones we can filter by witches. I asked the domain i p addresses subdirectories and host name. And then there is another quantify air, which has these four options equal to begin with and with and contain with me should be just very simple, one that we want to exclude. For example, one i p. Address. So one of the quantify IRS we want to want to select, let's assume, is that equal to And I would, for example, type this dummy i p address. If I would really like to exclude his I p address, which wouldn't be just a hypothetical, which it is, I would just click save, and from this moment on it would filter it out from Google analytics. Important information that filters do not apply Wheat reed retroactively. They only work from the moment we set it up to the future. So it's not possible. Once something gets to Google analytics, you cannot filter it out. This is this is important to remember. So this was just a very, very simple filter. Maybe lead to go to the custom wants where we can do much more things if you click there. The first and probably the most important information here is that anything we will type into filter patterns is taken as regular expressions. Important guys. Eso any doubt slash backslash hyphens brackets parenthesis we use are taken as regular expressions or characters that have special meanings. So please keep that in mind. Otherwise you can either filled or something. You can feel their big more than you want it to, or significantly less that he wanted to. Ah, we have much more fields to filter than in pretty fun month. If I scroll down of it, you can see there's plenty off content filters, campaign e commerce things. Ah, browser browser, things, location. So you can either filter in or out some specific country or region. Uh, some technical stuff here. Particular device category. If you would like to see only the data for mobile or desktop would make sense to you. Oh, are particular social networks or based on custom dimension. This is something that is also possible, so feel free to also do that. Ah, very, very popular are to feel very popular. Filters are based on campaign source or medium. Uh, I never actually found out why people do that, but it's quite popular. I just don't do that because I would like to see all data together because I can see that assisted convert and so on and so on. So yeah, the possibility is there. So if if you found if you find, ah, a business value in it feel free to do that, just letting you know that I just don't do that. So that's it. Maybe let's go back to what it allows us to. Let's assume you would like to filter a bit more I P addresses than just once a beauty will ask your i t guys. Hey, what are our I p addresses and they will give you a range of 150 addresses. So then you can say, Okay, how am I supposed to filter that out? And it's quite easy once you know how regular expressions work. So let's assume that they will give you something like this. And he knew that in the last part. Off filter pattern there. Is there r I p addresses form Wan koo 1 50 in this case, of course, wouldn't work because it's it is supposed to be a regular expression, and we can see that here are not here is in high food, so it wouldn't work properly. So the first thing we have to do is to escape by backslash knots because we don't want them to be any character. We want them to be dots. So this is what we do on We won't raise from 101 150 to be arranged off numbers. So it's no if you put it like this good parenthesis. This will take all of them about, you know, not finished the ad because we have to be fun that it has to also begin with this three numbers and it is supposed to end on these numbers. So this is how we would very easily and I would say in very elegant way, filter precise, 150 addresses. So this is again the magic of regular expressions. So hopefully you love it from now. Ah, so let's have a look on other possibilities. Off filters we have here a sui are here excluding something exactly the same way. We can include something so not going to show you. We can rewrite something to either lower case or upper case. So if we are sending, for example, specific at content data there and some of them are in came a case or just They are not all lower case or all or all uppercase. We can change it here by selecting some off. I know, for example, at content, little automatically rewrite all the values in campaign content. Dimension to lover case. Exactly the same might work with uppercase on. And then there is a search and replace filter. This was this would work in a way that it would search for particulate her value off some field, which, for example, let's just create a dummy from example where we would like re bright Ah, traffic sole source called Google for being. Don't do that, just showing you how it might work what it would do that Ah, all values of Google in traffic source will be replaced for bank. This is what it would do. So ah, where it might be used is the demand may be reverted Some some special strengths you're getting You're getting to Google Analytics in new TM parameters. I can find it. I can I can think of couple examples how to use, but they are very, very specific. So just to let you know if you want to replace something that is getting to your later. This is the place to do, and then there is the last one which is advanced on. These requires a bit more knowledge about what is possible to maybe the good thing. Always before you do some filtering is to look for help and, well, this this advanced filter is mostly uses to basically completely changed. For example, how we or Europe versus will look like If you look on this example that we have this u R L address, which isn't easy right than to do because we have bumper sounds a year. It's quite long, not easy to work with it, and we would like to looking like this without without the main name it stripped out. Ah, and then there's ah switched order off perimeters. Here. Number sound is replaced for slash and bid. More changes. The for example, this parameter is not there at all. Ah, advanced filter is exactly the functionality and Google analytics that will allow us to do such a thing. It's never a one filter. If we do such a complicated things, it's It's the sequence off multiple filters, so feel free to explore that and its possibilities. It's every time different. So case by case, it will be slightly different. Different configuration. But just to let you know that the option is here, what is important here to remember is that it matters on the order off filters folk. In this case, it would require to create four filters in exact order. So you can't, like, be create, for example, this kind of filter. And then this kind of filter you have to create this filter as the 1st 1 and then there, then this filter as the 2nd 1 and third and fourth ones would really matters on the order of the filter. Where to set it up If I will cancel this filter here, Yeah, this cartoon just if you are here in the in the main screen with the filters, there is about a asan filter order where you can change the the order of the filters, which is the top one second, third and last one. So this is the place to do that. So, yeah, these guys were were filters. Ah, play with them. Try to clean your data as much as possible. And keep in mind that your your ah, working with regular expressions there so checked do, or three or maybe even four times. Whether regular expression you're using, it's really doing what you're expected to do. 39. 11 Calculated metrics INTRO: calculating metrics. It's another powerful feature in Google analytics. You can use almost all the G M metrics to create calculated ones to create it properly. It's necessary to understand how scopes work, which we already know. There are a couple of them I recommend using to everyone. I might have a good news for you. You're really convert rate is probably much higher than would you see in G. A. The reason for that is that all the conversion rates in G A are calculated with sessions as denominator, and if you think about it for a second, is not sessions who convert but users. So definitely the first calculated metric should be users conversion right, and there are a couple more that can have huge business impact. So let's have a look on how to create and use them. 40. 11.1 - Calculated metrics - how to set them up: so guys who are going to have a closer look out create and use calculated metrics in G A. First of all, we have to go to administration by clicking here, and all calculated metrics are created on a view level. So this is it. Ah, it has separated tab here, calculating metrics, which is still in. Better for I would say, two or three years, maybe so classically here. And this is what we should see. If you can't see that red call to action, plus new calculated metric, you don't have sufficient permissions. So ask your administrator to end you there and then you'll be able to do that. First important information is that you are able to create up to five calculated metrics so used in Bisley. Do not try to create many of them eso so you won't waste it immediately. Pardon? So let's look there. It's pretty easy and straightforward. The first thing is name. We're going to create a user's conversion rate, which we discussed in the first video on This is the metro we all should use. I will show you once we created ah how huge difference it can be. So Klux name it. Users version. Great. Here we are. Uh, 2nd 1 is creating a formatting type. It can be flowed. Indeed. Your currency time or percent if we think about it for a second. We were going to swap sessions for users. Ah, from from the standard calculation of conversion rate. So it will be a person number. Uh, and then it's fairly easy. You have, ah, quick formula here, and you can use a blast. Mine is divided by multiplied by. So here is the standard form of how to use it. And formulas are limited to 1000 and 24 characters, which should be, I would say, enough for even very, very long for formulas he would like to use. So what are we going to do? I only have here in my account one goal which is sending a form. So if you if you are plant created, calculated metrics based on transactions than your goal would be transactions, you would type here. So if you just start typing, it will help you to find what you're looking for. So in my case, it's form sent, which is the name of the goal. I want to have completions off these goals divided by volume. Sorry, I have to put their divided by and now I'm able to use another metric with these users. So this is it? Ah, don't worry about the brackets and parenthesis here because they are at it automatically. So you don't have to think about it on. This is how is defined right now. Don't worry. Once you created and you find out that it's not the number you were expected expecting to have, you still can change it. So So don't worry. You don't have only one attempt creating a metric. So this is it. No, I click create. And here it is. We can see what type formatting top it is. What? It's external name, which we will show in exporting the data lesson, which is, I would say two or three essence in front of us and we can also delete it. So, Phil, even we can delete it. Still think about it where advisedly don't try to waste all of them immediately on. And as it is right now, we only can use it in the custom report. So we're going to customization custom reports, and I will show you how to use it In very simple report, my dimension would be the last category. Yes, we would be the one I created. You can filter it now by the name he just chosen or you can go to other, which is a love calculated metrics you will create will be under under other tap. So just to show you that it's working also by filtering when I just abusers here it is and I will add there one more, which is the standard one. Which calculation is based on sessions. So is one from said sides were to go want us or another one? It's It's It's It's It's ah farm sand convergent. Read this one. This is the standard conversion rate I would see, for example, in source Medium report. If I would look on the very right side that that would be the goal I would see there. So let's save it and see what happens. Great. I only have couple of forms sent here because motive off the people contact me directly. Why email but just to do, giving an idea how sensitive this metric can be? A sad in the end of the day, its users who convert not sessions. And this is something we can also see here. If we look on standard conversion rate calculation based on sessions, my conversion rate will be 0.15% whereas looking on users convergent right, which means how many people are people. But cookies, which is still closer to people than sessions, is 0.1 to do so. It's about 1/3 higher than what I see normally. So this is just a very quick, quick example how huge different it can difference it can be once Onley switch users for sessions. So, uh, this is it, and you can create up to five of them on and go to Resource is I'm not going to show you how to create more of them because it's fairly easy. Ah, but go to resource is you'll find a couple off articles from various businesses ah, either from e commerce or lead generation with examples what calculating materials they are using in their accounts. So go ahead. This is something ah, very handy and can change your perspective on how your website performs 41. 12 - Custom channel grouping - INTRO: I'm sure that you have at least once click in the acquisition tap on channels report. You've noticed that there's Default channel grouping. It might be good enough for evaluation, but if you want to do deeper but still high level analysis, you will need to build Custom Channel grouping a quick example off what is not in the fortunate grouping a brand traffic, and I'm sure this is something you want to see there. Or he only wanted to divide your traffic on paid versus unpaid, or you want to see separately or generate campaigns with your ple campaigns or all retargeting channels grouped in long. I think you know what I mean, So let's have a look at it. 42. 12.1 - Custom channel grouping examples: OK, guys. Now we're going to look how to create and use custom channel grouping. Just a quick reminder what it is if we go in Stender reporting to acquisition all traffic and we use channels. Ah, what? We are going to see ISS default channel grouping, which is something created by Google automatically. There are set of rules which group our channels into a couple off Mexico. Seven or eight general groups organic search, direct referral and so on and so on. And this is sometimes completely enough. But I can't imagine you would like to have your custom one defined purely on your rules. And this is exactly what we're going to show how to build. So ah, in order to do that, we have to click again to admin. And, as in case off calculated metrics, exactly. Also, here we we created on a view level, so here is separated that poor it custom shall grouping. So let's click here. Ah, I already created one. Ah, very simple one which divides, um traffic onto into two groups paid and unpaid. Let me show how it looks like and then we will create ah one from the scratch so frankly here I'm basically creating here a set of rules by which my traffic will be grouped into particular channels. So I created one which I named bait. Ah, and the rules on which on which this channel is based is that the medium you 10 perimeter media matches reggae x CPC CPM fill it. So this is how I I decided to group this channel. It can be entirely up to you. Ah, you can use any criteria we want to. So it's It's nothing universal that can be used for all of the websites. So you will have to take your time and once you will create it. But it's definitely worth it. Ah, every channel grouping we create is not on Lee used in the report. We just showed Ah, but pretty much everywhere were our traffic and be groups of, for example, assistive conversions, reports, top conversion paths, attributions, models comparison. So So it's not only one place where we can play with it. So this is this is the first example off the first rule I created so done and then the 2nd 1 is exactly the opposite off the page channel. So the medium does not match Rex, CBC, CPM and affiliate on again done important information here. Regular expressions works slightly different here. So click on this link to find out what the difference can be on. And I have it here on the steps. So if we, for example, would like to this is important part for us guys, This one. So if we want to include anything that contains January, which could be like january 1st 2nd January or general only we cannot write on Lee General . This is the way it works in case off channel groupings. If we would like Teoh, set it as regular expression. We also have to ride data Asterix asterisk before and after it in order to be taken as regular expression. So please given in mind very important. Otherwise you will not be able to build Ah ah Chung grouping based on regular expressions. So yeah, important information. Um and we're going back. So we created only to channel definitions paid and unpaid. I'm going clicking done and safe. Don't worry in a couple of minutes will bit one from the scratch and right now we're going to show in which reports we can use it. So if we go back, Teoh acquisition all traffic and into channels. Um, here we are. Ah, right now we can change it from the default channel grouping to the one we just created, which is paid versus non bait on base. Sorry, Andi Onley will see two lines which groups all of our traffic on Lee into this to particulate her channel groups, which is purely amazing. Basically any analysis I do. Ah which is necessary to also use channels there. I use my custom channel groupings. I'm I have built for every reclined and every G account I'm using again to remind it's nothing. It can be universal because every website has slightly different naming conversion convergence conventions are naming conventions for you, Tim Perimeter. So it's not possible to build it universally. But as we can see here Ah, even even from from this grouping, it's obvious and easy to see that unpaid Ah, unpaid traffic has higher conversion. Right? The debate along on this is just a simple example. You're not tied to only use two lines. I think you can use at least 15 or I'm using Ah, some of examples Where there are 15 channels defined, so it's it's really a lot second report where we can use it. ISS only go to conversions, multi gentle funnels and some of them which we are already familiar with. The first of them is assisted conversions where this grouping is also available here, a spade and on bait. And again all the data will be group based purely on the conditions with we defined so again, do the filtering for only hard conversion on your website set properly or ah, look back window and so on all the steps we already know what will they mean and why they are necessary or for for example, also in top conversion box. This is also the place where customs union grouping is available and you can work with it, which is truly, truly amazing. So this was just a brief example how it can be used and right now let's go and build a custom one. Ah, from the scratch. As I said, eat weekend, we can create up to, I think 15 maybe even up to 20 various channel groupings. But again, we're going to show a very simple one, which is something I was talking in the introduction video of this lesson, and it's a brand traffic specific. So, in fact, we got a new channel grouping. First of all, I have to name it somehow A so you can see I already have here Brandon on bread, which is ah, grouping. I'm using a different project I'm working on. So let's, for example, name it as the brand versus naan bread and we're going from the script so defining a new channel. First of all, we have to name it. Let's assume it will be brand traffic. This is the first general group. I would like that now in defining the rules. So there are almost, I would say, all acquisition dimensions available in Google Analytics. We can select any any we want to on. I would say our Brent traffic should be defined by the keywords user stopped into such engine. So my name engine would be keyword, which, for example, let's assume we already know how to work with Reggae X, Uh, with would match, for example, work merch or work Google, right? It doesn't have to be true right now, but just showing you how it how is supposed to work and has said, If we want to have it purely, you are truly working as regular expressions. It wouldn't work work like this because it works with a full name. So if if you also want to take it just the part of the key word, which could be merchandised, merchandising and so on and so on, this one wouldn't work again. Tutorial about it is here, so we have to add also dot and that's the risk before and after every key word we want you . So if we assume that the our brand traffic is defined by users coming, why either merge merchandising or anything containing merge or Google? This is our brand traffic. You can select the color whichever way prefer really doesn't matter Right now, I'll take a black one and I click done. This is my first channel definition. If I, for example, would like to create another one, I could just name me like I don't know, known brands and again said a rules here. Some of them, I would say, like he were, does not match Rig X merge and and, uh, Google, which would be exactly the opposite condition. I'm using here. I'm not going to do it right now on its for for the reason. So if sometimes you only want Teoh Group Ah, one channel or one ones are channel based on on only one selected group. You only can use one, and all the rest of the traffic would be grouped into something that Google's call is calling other. So let me show you what I mean. If I click safe right now and go to acquisition, report ultra thick and channels back, I should see the new child grouping here, which I knew I likely gonna brand. I see that there's Brent traffic, which is defined by my rule, which is 7.5 1000 users. And then there's other, which is everything else that does not meet does not matter the conditions defined for brand traffic. So this is the way to work. So sometimes I don't even have to create Ah, another grouping definitions because one can be enough. So if you if you only want to do something quick, feel free to do that. What is important thing or why am I showing you that it's ah enough to create only one of it. If I will go back and go into the general grouping we just created, which is Bryant and not in a Brandon un brand. If I would create the second channel, which I will just type here, for example, test and at content containing past Big Done. Ah, I can change the order off. General definitions. Why is it so? It has a reason, and it's very simple. Ah, the wait worth it. It's like a funnel. So anything that meets the condition for the first channel definition cannot be considered or counted in the 2nd 1 So this is why it works. And this is why it makes sense to play with the order. Ah, and it has, um very, very good positive thing on it. It's that if we, for example, would not create a proper, um, condition based on every rule that can cover some traffic, it won't just get into two of them or three of them because everything that is counted in a higher channel grouping definition cannot go down and be counted again. So this is this is how it works, and it's ah, great feature. I will tell you because sometimes not now that easy. Teoh created conditions that would meet 100% off our traffic. So this is what channel grouping is have any recommended to use it again? Check Resource is with a couple of examples for various businesses and Ah, yeah, Feel free to play with that. You can group it by by Brandon on brand. By having display campaign separately by I would say retargeting having us as, ah one group off multiple platforms you might use for Ah, for example, organic traffic which can be again integrate public. There are two major players, not only Google. So again, this might be something you would like to see grouped under under one channel or, for example, various affiliate partners you're using and so on and so on. So they will again depend on every website would be slightly different. So have any welcome India, this one? It will give you a slightly different perspective on how your channels behave, especially if you go to assisted conversions or top conversion paths. So let me know. How did you go 43. 13 - Custom alerts INTRO: custom wheeler think and sometimes save you a lot of money. Try to imagine that within 24 hours after your it's to CART rate decreased by 30% you would receive an email with this information, or you would get an alert. The number of your 40 force doubled uring past week. Exactly. This kind of alerts congee a sent automatically, so let's have a closer look how to set it up. 44. 13.1 - Custom alerts - how to use them: so alerting can be very helpful thing and can conceive you a lot of money. Ah, what I mean by this it's always nice if someone or something tells you that Hey, there might be something wrong with your website or with your business. And it's very nice if can be it can be a Robert and Google analytics can exactly do this kind of job for you. What I mean by this again, it's a custom thing. So we have to go to customization and then custom alert. Here, let me show me what possibilities do we have? First of all, managed custom alerts and new cost New alert. Let's assume that we want to create only a very simple one telling us OK, your brown trade has increased by ex wives that percent first of full again aiming it so in creased on trade I'm only you're using right now this this you. But if you want to apply to multiple of them, feel free to do that and the period that would be checking be either day, week or month, I would leave it here on the day. Ah, and I want to receive an email when something happens, you can also send an email to multiple email addresses so differently makes sense in case off that you're not working or you're out of office. Ah, it makes sense to send this information that that something happened to multiple people. Ah, if you want to feel free to set up your mobile phone so we'll refuel receiving on ah message if it happens. So very nice feature and out Dutilleux set up itself. First of all, we have to select on which, um, condition it would apply one of the dimensions year is all traffic, which is exactly something we're going to use here. And here are many more. You don't have all that mentions here. But don't worry. We're going to show the way how it's possible to use any dimension we have. So, uh, all traffic any I won't do. Ah, having alert or receiving alert every time, my bounce rate. And here we have conditions we can weaken, be less or greater that then something increased or decreased either absolutely or as a percentage. So let's assume I would like to receive alert every time. My my bound trade increased by more than for example, 20% as either previous day, same day, previous week or previous year. This will depend on your seasonality, but in general I'm using this one in most of the alerts I'm using is the same day in the previous week. So if I would click save right now, I can see its success. So from now on, every time I bound trade changes in week over week for the whole website by 20% I will immediately the first day it happens and I repeat, the first date happens. Ah, an email that that Hey, you should look on the rebound three that there might be something wrong with it. So a very nice thing to do. Ah, And now let me show you a slightly advanced one. If I would like to receiving alert every time my ah, that's two car trade or I would say not add to cart. Right. But the number of people who had added something to cart ah, decreased by at no 15%. It's not that easy to do. So let me show you what I mean. And if I would name my L'Art, for example, at you car, there's we could be people who added something. The card. Mm. Greece. The same set up is here for only four. I would I would like to apply this alert only on this master view on the beautiful B day. And here I have nothing I can. For example, I would say I would so like the traffic. And then the metric I would like to follow is to Cartwright, right? Or by to detail, right? Or two d card. Whatever it ISS. There's nothing like this because there are very little off equals metrics on Lee, the absolute one or here is commercial. Right? If you want to use it. Yeah, also an option. But I'm looking for a two cartridge which is not here on. I'm sure you'll find a couple of scenarios where he won't be able to build on alert condition on Lee from the dimensions and metric available here. So what is possible here and what can save you? Yes. Ah, custom segments. I'm sure you are familiar with it because you either made it through my first course or you use it on a daily basis. So this is something that can save you. What we have to do right now. If you again, I will repeat what we are looking for. I want to see whether my eyes to Carter. I decrease. I have to go right now to anyway, board I have and I have to create segment of users or sessions who added something to guard . So this is what I'm going to do right now. I can go to any report just back clicking on at segment, creating any new segment again, repeating guys you should be familiar with. That's what I'm doing right now. And I will name it, for example, at Carter's the way I will created Is that okay? I won't only want to include sessions where, um for example, quantity at its A cart per session is higher than zero. And this will basically define all the sessions that added something to guard, which I can see. It's 11,000 users, $13 or more. Moved 14 1000 sessions. Ah, quick save right now, which would create a new segment based on this conditions. And okay, here we are. And if I will go back right now to custom alerts set up, I'm going to manage and right Now I will be finally able to create a segment off that will check whether my editor cadre decreased or not. So at two car rate increase that appear on instead of all traffic, I'm right now selecting one of the custom segments. So I'm going to search for it, which is at here is at Carter's, and I'm looking for the number of sessions, which is exactly something that is here, or I can select the users if I want to feel free. Whatever fits you, Mother, I will select users. For example, on I want to receive a message every time, number or volume of the users who added something to card decreased by more than might. I know 25 percent as the same day in previous week because normally this is the most common seasonality we can use. So this is it. If I would read now, click on safe alert. From now on, every time something changes the first day it happens, I would receive an email. Hey, your rental car dry decreased by 25%. You should look at it. Maybe it's nothing, but maybe you have something wrong on the Web site So this is what L'Art are about. Um, again, it's not possible to create universal ones. Just make sure you follow your top metrics. Your top funnel from the sessions T bounce rate at two. Car security. Commerce Teoh did the funnel check out and so on and so on. So try to color the O. T. Rough funnel. Now, the very small things that can differ a lot. Ah, day over day or week or week. But this is something you should definitely use. Uh, it's still better to receive a message and look at it and look on it. Ah, and explaining. Okay, we know why this happened or it's not an issue that not knowing about it and no thinking noticing it. I know 23 times to three weeks or months later and losing a lot of money. So, yeah, feel free to use it. Ah, these are This is my very, very favorite feature I'm using N g A. 45. 14 - Automation in Google sheets INTRO: as we know how to work With custom reports, we still can feel a little bit limited. With only one custom set of data. Google Analytics has an A p I, which allows us to automatically EC structural data and do whatever we want to with it. And what is the best thing is that you don't have to write a single line of coat. Imagine you can build your fully customize dashboard with any dimensions and metrics automated every day. So any time you open it, you immediately see fresh data on one place. This is very easy to build, and once it's done, it doesn't require any maintenance. Let's have a look how to do that in online spreadsheets. 46. 14.1 - Automation in Google spreadsheets - examples : So, guys, the lesson about ultimate ing Google's data in Google Spreadsheet Uh, what we have to do is the first thing is to log into or drive that google dot com, and you should see something similar like I do here. You might see some different files here, but what we are going to do right now is to create a new Google spreadsheet. I'm sure that many of you have done it already, But let's start from the basic soul creating a new Google lock or Google sheet, and you should see, uh, on empty spreadsheet. The first thing we have to do is to check whether we have a Google Analytics add on here. I already have it installed here, but for those of you who do not have a deal, find a ling in the resource is or you can just go to manage, add owns and fielder Google Analytics, which is this one you'll find in there Anyway, you have a link in the resource is so don't worry about it. So install it on. Go back to the lesson and here we are, how it works, as we shown here on the the main tab there is Adul and Google Analytics and we're going to start from the very basics by creating by clicking here on Create new report. And right now we should see here it ISS of this step which will help us to build basically which will not build that to extract any data available in the Google interface. Here. We're going to do a P I call, but without writing a single line of code which is create guys, it really is. Trust me. So what we have to do? I'm sure this one is pretty simple. So we have to select account property in the view from which we want to extract the data. And next thing is report configuration. So I would start with selecting the damage. You can dive here the normal interface names and I'm stressing the word interface because off reason. So let's start with a very simple dimension. We could you can be device category we're going to build for very simply report just to show you how it works. And the metrics I would like to see would be users and sessions. So this is very OK and should name it somehow so let's say this report and this is it. So if I will now click on Create Report, what is going to happen? That there will be a new top created automatically called report configuration? And here we can see that there that this is something like configuration. This is a beauty of your Google analytics started and they and here are my dimensions and metrics. And they have specific name, right? It's not ah, device category with a blank space. It's this cable case naming off them engines because the these are FBI names off them engines. If you want to know what are exact mention names or metrics names you'll find again, a link in the resource is with this page where all the dimensions and metrics are available . So if you, for example, are looking for, um paid a dime engine and you have here both you I and a P I name, so if if you are used to use Bages a damn engine in you, I on a B I name of the game engine is G H G, a Colin page bath and so on and so long to have full list of them here available, you'll find the link in. The resource is so feel free to play with it, and we're going big here. So we have this simple report created. There are a bit more opportunities you can order it, filter it by any that mention in metric. You can also use the segments here, which is school on Dhere. A couple more options, which are report type sampling level and use resource. Quote us This one line number 16 is available on Lee. If we have Google Analytics Premium, which almost none of us have, then you can select assembling level, which can be large, normal or small. You'll find a lot of help on this length or feel free to click on it. It's very well documented. I'm going to you to show what are possibilities, so you can then play with it. So if we have it configured wrapped like this, if I would now click on add on Google Analytics and run report, let's see what is going to happen. We have to wait for a couple of seconds. Ah, and here we are, report was course successfully completed, and what I see right now is something that he probably expected. I see device getting arrested, them engine and two metrics, users and sessions. So now I extracted the role data from from Google analytics, which is pretty cool stuff on if we want to. We can add another one, which we don't always have to go to add on Google analytics and create new report. If we're sure what we are doing, which I hope you are, all we are are we all artery? We can just copy this configuration based here. Ah, renamed. Ah, poor name. Then you can change, for example, your dimensions in metric. So, for example, that the seem I would like to see report off my landing pages. So first of all, I have to find out was the name of the dimension When the debate which is g a call on landing page bath. This is what I do I normally just copied then based it here as a dem engine and us Ari is click. Uh, and as a metric I would like to see sessions right, because this is the proper metric for lending based baths we follow really? Did it. And now try to again around this report Ah, again we can see it was successfully completed. And I have another report with lending page as a dimension and sessions and metrics as metric, and that's that's pretty much it, guys, it's It gives you almost endless possibilities because again, use all axel pre build functions here, which is especially cool if you want to the automation on, for example, daily or hourly basis. What I what I thinking off is this one? For example, if we use cloaks today as a function and if we always want to have yesterday as a date, we just do this B minus one. We have yesterday's and, for example, if we always want to see the last 30 days, what we can do is just equal. They sell minus one four miners, for example 30 Sorry. Alone. Could you show you how to call for 30 days? And here, for example, I can use okay. Equals this one. This equals this one, right? Just it pretty is pretty simple thing again. Has to show that it works. Run report and yeah, here this Now I should see probably a bit more lines, which I do in both reports. So start nothing. This one, this is just a number, but yeah, this is it. Another thing possible to do is to schedule this report, which is absolutely amazing stuff. You want to configure this report and create a deck boards from it? You can do that. Then schedule it, which is by clicking here, schedule reports and yeah, enable reports round automatically and scheduled to re schedule reports to run either every hour, every day, at exact time, every week or every month. Really bent on you I'm using mostly are amusing the reports that are running every hour or every day. Ah, so yeah, that's that's it. And the goal is to basically extract all the data you need from here and then use the power off Excell functions here, which enable you to some of the day that too big only part of the data I want to and so on and so on. So then then under on the empty sheet, you can build your custom that board with exactly the day they want, you'll find again. Couple of links for the dead sports I'm using with the simple data just to give you the idea or sensitivity what? Everything can be built here. Uh, important thing to notice. There is possibility to use a segment here. Uh, what do you have to know is how to call for the segments. This is something that it's not that easy to do without reading the documentation, which I suppose we all will do because you're smarter guys. But anyway, if you want to find out, for example, on alias of your custom built segment, you have to go through this to again. It's g a deaf to zap spot com. You'll find the link in the resource is and what this thing us is. Basically, it allows you to also query Google analytics data y a P I. So if you cook, click on the choir Explorer here and select some Google Analytics account property and view , you can pretty much can do exactly the same. Report. Configuration is here in the spreadsheet, but you are allowed to do here. I will delete this one also, uh, easily filter a segment which were not allowed in a spreadsheet. So if you, for example, want some basic segment off paid users, this is what you have to die there, which is G A I d this one. So if you copy it here and based it here a segment than it will filter you. This data will also applied this segment. And these are the built in segments just with the number here. And if you will use some of the custom ones, they would look like this. Oh, yeah, this can be This is my custom. Second at two. Carter's. So this isn't something that you can easily remember? I guess this one if you do, you're You're lucky ice. But hopefully are not hopefully bra, probably none of us can. So you have to copy this one and basted here a segment off at two. Carter's in, In my case, which I used. So yeah, this is this was like a brief introduction. How can easily extract any that I have in Google Analytics. You can even go across multiple accounts or multiple views and then combine all the data into in one sheet at one place and schedule it almost on every hour. If it makes sense to you, you can also use ah g a date, which is ah day them, engineer. So we have this break now on, basically, create any and I stress work Any report you want to. So amazing feature, which is ability to excess all Google analytics data without writing a single line of code . That was it. Uh, you're only limited. Here will be the maximum limit off the cells in a spreadsheet in Google stretches, which is two million. So if you will create probably more than I would say 50 50 report configuration. You might reached his limit, but it still can be if you will. If you will create your reports wisely, you probably will never reach this limit. So yeah, that's that's, ah, automation off Google analytics data in the in the spreadsheets. And please check the resource is to to see what I am, what I am using as a spreadsheet and what kind of data can be easily created.