Google Analytics Bootcamp -Beginner to Master | George Gill | Skillshare

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Google Analytics Bootcamp -Beginner to Master

teacher avatar George Gill, Business Optimizer

Watch this class and thousands more

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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

    • 1.

      Google Analytics Bootcamp Trailer Learn Google Analytics


    • 2.

      1 0 Why Google Analytics


    • 3.

      1 1 How Google Analytics Works


    • 4.

      1 2 How Google Analytics Works


    • 5.

      1 3 Limitations of Google Analytics


    • 6.

      1 4 Interface Overview


    • 7.

      1 5 Understanding the UI


    • 8.

      1 6 Advanced Search


    • 9.

      1 7 Reporting Options


    • 10.

      1 8 Admin Overview


    • 11.

      1 9 User Management


    • 12.

      1 10 Audience Overview


    • 13.

      1 11 Audience Overview


    • 14.

      1 12 Audience Deeper Reporting


    • 15.

      1 13 Active Users


    • 16.

      1 14 Demographics


    • 17.

      1 15 Demographics


    • 18.

      1 16 Interests


    • 19.

      1 17 Geography


    • 20.

      1 18 Audience Behaviour


    • 21.

      1 19 Audience Behaviour


    • 22.

      1 20 Mobile Technology


    • 23.

      1 21 Benchmark


    • 24.

      1 22 Benchmark


    • 25.

      1 23 Users Flow


    • 26.

      2 1 Isolating Your Data


    • 27.

      2 2 Segmenting


    • 28.

      2 3 Custom Segments


    • 29.

      2 4 Filters


    • 30.

      2 5 Analysis Fundamentals


    • 31.

      2 6 Template Goals


    • 32.

      2 7 Creating a Goal


    • 33.

      2 8 Goals Overview


    • 34.

      2 9 Goal Reports


    • 35.

      3 0 Ecommerce


    • 36.

      3 1 Ecommerce


    • 37.

      3 2 Ecommerce Marketing


    • 38.

      3 3 Aquisition Overview


    • 39.

      3 4 All Traffic Channels


    • 40.

      3 5 All Traffic Treemap


    • 41.

      3 6 All Traffic Source


    • 42.

      3 7 All Traffic Source Deeper Dive


    • 43.

      3 8 Adwords


    • 44.

      3 9 Adwords


    • 45.

      4 0 Search Console


    • 46.

      4 1 Social Overview


    • 47.

      4 2 Social Reports


    • 48.

      4 3 Campaigns


    • 49.

      4 4 Campaings Custom


    • 50.

      5 0 Behaviour Overview


    • 51.

      5 1 All Pages


    • 52.

      5 2 Navigation Summary


    • 53.

      5 3 In Page Analytics


    • 54.

      5 4 Content Drilldown


    • 55.

      5 5 Landing Pages


    • 56.

      5 6 Exit Pages


    • 57.

      5 7 Site Speed Overview


    • 58.

      5 8 Page Timings


    • 59.

      5 9 Speed Suggestions


    • 60.

      6 0 Site Search


    • 61.

      6 1 Events


    • 62.

      6 2 Experiments


    • 63.

      7 0 What are multi channel funnels


    • 64.

      7 1 MCF Overview


    • 65.

      7 2 MCF Visualizer


    • 66.

      7 3 Assisted Conversions


    • 67.

      7 4 Top Conversion Paths


    • 68.

      7 5 MCF Lag


    • 69.

      7 6 Attribution


    • 70.

      7 7 Model Comparison


    • 71.

      7 8 Model Comparison


    • 72.

      7 9 Custom Model


    • 73.

      8 0 Real Time


    • 74.

      8 1 Custom Reports


    • 75.

      8 2 Dashboards


    • 76.

      8 3 Automatic Alerts


    • 77.

      8 4 Custom Alerts


    • 78.

      8 5 Content Grouping


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About This Class

Now You Can Learn The Secrets of the World's Most Successful Online Marketers!

If you can't measure it, you can't manage it! ~ Peter Drucker

Track, measure and improve that which is working in your business, and the bottlenecks minimizing success. Understanding where to look, what to look for, and what to do with what you see will change everything you do in your business...

If you're looking for an “insider" shortcut guide to creating success online that will supercharge your business, your wealth, and give you your life back, then Google Analytics Bootcamp will show you the way.

To be successful in business and in life you must have laser focus, and consistent action towards what's working. The secret is to know what's working, and not be distracted one bit by all the blinking new channels, tools, and sites that beg for your attention.

Most people in business can get some traffic to their website, typically spend some time on Facebook or Twitter or any of the many social media sites available to them, and may do some basic search engine optimization. But when it comes to being “successful online", most don't have the time or direction to know where and what to focus on. So we try to do it all – “jack of all trades, master of none"

Look. Everyone has access to Facebook, Google, Twitter, LinkedIn, blah blah blah. The fact is your customers are there too. They're searching on Google, they're hanging out on Facebook. So why then do most businesses just spin their wheels and flounder around in search of success?

Think of it this way – anyone can own a set of golf clubs. Typically there's an assortment of 10 or more clubs in the bag – and you can whack the little dimpled thing with any one of those clubs.

But to play golf well…to be a master of the game and make the ball go exactly where you want it to go…then you need to know what clubs to use and when. You need to know when the #7 club will put you within inches of your goal where #8 or 9 will leave you in the rough, lost in the sea of all the other golfers.

… you need the inside secrets you will not discover casually on your own.

It's the same with analysis.

The advanced, mega powerful secrets do not appear to you magically, just because now you're in the position of having to sell something. You need a guide.

Google Analytics Bootcamp is that guide.

It guides you by the hand and leads you through the understanding of Google Analytics…

… past the explosion of reports staring back at you on your screen…… past the smoking wreckage of failed business and ruined dreams……and directly to action based steps that will produce ethical wealth and heavenly happiness that will bring you to tears.

This is the “insider" course we wish was around when we were starting out online.  Learning even one or two of these secrets would have short-cut our own success by… oh… five… maybe ten years.  Probably more.

Included in this best-selling eCourse Now Available On SkillShare are the secrets most businesses never discover… such as:

  • How to quickly and properly configure Google Analytics to reap the rewards of accurate data

  • The magic of tracking goals – and why you can't afford to not have this functioning

  • How to make advertising dollars go further with connecting cost per click results to your web analytics

  • A very simple strategy to know where to focus on search engine optimization – what key phrases are worthwhile and which ones are a waste of your time

  • Why your current data might be wrong, and a quick simple fix to solve it

  • How to navigate this endless realm of reports and crush the overwhelm – (Looking right over our shoulder we guide you on our screen)

  • How to analyze in lightning speed by looking only at the data you need to see

  • Why potential customers immediately bolt for the exit on your web site – and you didn't even realize you had a problem!

  • How to look at the information visually if you're not a numbers person – or just hate the endless numbers

  • The insanely effective secret of marketers and what they're looking at

  • How to explode your offline marketing results through measuring strategies – yes even newspaper advertising can be tracked

  • What is really driving sales or leads to your business, and what's just wasting your time (and money!)

  • How to spy on your prospects and see what's working with them on your site

  • How some marketing affects other marketing and whether it turns to sales or leads

  • How to discover why your web sites failing within minutes of scanning the data

  • How to measure a social media strategy immediately – we're talking the second you hit enter on that tweet or Facebook update

  • Why certain pages on your web site are killing your business

  • What content on your web site you shouldn't touch – or risk back-tracking months or even years of progress

  • What the search engines really think your business is about and how to fix it

  • And… the mystery behind online success, how some marketers seem to do everything right, and how you can apply these priceless observations to your business

…and this is just the beginning. Once you have the basics down, taking actionable, measurable steps towards marketing improvement is easy.

That's just a small sample of what you'll find in this premium member's only eCourse. There are over 5 hours of video training, watching our screens as we guide you to becoming an analytics master. And give you the roadmap you need to start creating your own ridiculously successful marketing campaigns. 

The training lessons are on average 10 minutes in length. This is a powerful way to learn… watch the video, then apply the learning to your own business! Progress at your own pace or cram all weekend long and implement everything. Whichever works best for you.

In addition, there are over 3 hours of special video case studies for online business management included... This is where the rubber hits the road and we apply all you've learned to real businesses, real data, real lives!

When you think about it, this really isn't a training course you purchase, rather an investment into your business foundation – a membership that will continue to give back for years to come. And because this isn't just what we teach, but what we do – if you get stuck, we're just a comment away as our Analytics team monitors the conversation area.

I don't care if you've never looked at a single page of web analytics in your life. Or if you're a veteran just trying to get further ahead with your results. Or if you've tried every shiny object that's come along and failed.

None of that matters.

The ONLY thing that matters…is your desire to get started. To start measuring ALL YOUR efforts and with laser focus, start taking the right actionable steps that bring in sales and new customers in a flood, fast and furious.

This is the course we would have killed to own when we started out.

One Last thing...if you're brand new to google analytics, and numbers scare you...fear not! We start at the very basic beginnings, and move you to mastery! Enjoy!!

Meet Your Teacher

Teacher Profile Image

George Gill

Business Optimizer


I'm George Gill, the founder of GILL Solutions, a marketing strategy, and technology company dedicated to helping businesses grow. I've been teaching business development and optimization strategies to entrepreneurs, marketers, and businesses for over 10 years now, with students in over 65 countries. 

I'm passionate about helping people grow and reach new heights of potential!

See full profile

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1. Google Analytics Bootcamp Trailer Learn Google Analytics: Google Analytics on your website, tracking every visitor where they came from, what marketing attracted them, where they landed and what they did when they arrived. The ability to know, without a doubt, what's working on your website? What's hurting performance and that steps you need to make to grow sales. But how? How do you go from an interface full of data to making actionable decisions that drive sales? One of the biggest challenges for businesses small and large online is where to focus their attention and investment. What marketing strategy will work for the business? Should I update my website, or is it holding success back? Do I have to be on social media or my wasting my time? And unfortunately, most businesses are simply guessing at these answers. Our training program is designed to take any business owner or marketer step by step through a sequential order of learning that's easy to follow and effective. Imagine in your business if you could wake up today knowing within 30 minutes how to group sales to mark and grow them further than next day, and the next day after that, knowing, not guessing, where to focus, marketing and designed to drive the results you truly desire. But most importantly, and this is critical, it's not just knowing the interface here that will do this. It's clearly understanding what to do with the information that you see. That's the power of our boot camp. It's are tested and proven. Three step approach to training we've developed over the last nine years of training students in over 61 countries. Step one. Learn the interface You need to be comfortable with Google Analytics. Step two. Apply the information to your business while you learn. Step three Support the user as they grow. All of our training programs include one year of unlimited support. Obviously, Google Analytics is a powerful resource, but the ability to grow sales and make better marketing and design decisions on Lee happens when you clearly know how to use the information. Before you learn the Google Analytics interface. Know how to apply what you see to your business. Reach out to our team at any time for the professional guidance you'll benefit from. That's the power of our Google Analytics boot camp. Join today and grow your business 2. 1 0 Why Google Analytics: Welcome to Section One of Why Google Analytics Basic training Before we get started into taking a look at Google analytics and the power that it has and and all of the different features and specifications, I want to begin by talking about what is Google analytics? It's rather interesting. If we take a look at Wikipedia's definition, we see that Google Analytics is a Freemium Web analytics service offered by Google that tracks and reports website traffic. And although this is true, that really isn't the power of Google analytics. Yes, it does pull in all your different website traffic, and we're gonna talk about that in detail, and we're gonna go into how it's doing that and what have you. But the real power from Google Analytics is being able to take the information that it collects and base actionable decisions on that information. And the more you develop your experience at analyzing that data and how to filter that data to get the more precise answer that you're looking for, the more powerful Google analytics is going to become for you. At its core, Google Analytics is simply what Wikipedia describes is a. It's a application, a software application that's running the cloud that collects information from your website . We're going to talk about it a little bit. How Google Analytics works in a minute, when it's collecting that information, it takes it into their services, servers and processes that information. Then, after processing that information, it's sent out into their databases and displayed through the glue Google Analytics platform . And that's what we're seeing is the reporting. Once it's in that database, it's able to be manipulated and refined to see the data as we need to see it for our purposes and whether you're a business owner or a marketer or responsible for a marketing team. Whatever the case may be, you may use the information and display the information differently. Now Google Analytics as a interface. What we're looking at today at present time of this recording may very well change 30 days from now, 60 days from now, etcetera, Google Analytics is constantly updating their interface. But what's important understand is that as we dive deeper into this training and as we dive deeper into the nuances of the reporting, is once you understand the core of what you're trying to achieve and pull out of Google analytics. It doesn't really matter how the interface changes at that stage with changes, it's just a matter of re navigating the new navigation to find the data that you're looking for. Potentially. There's new features that might come into play, and that would be fantastic. But overall, once again, you understand the core for ability and how you want to see the data. It's just a matter of digging around to find it and pull it. So if you're watching this video and there's some nuance changes in the interface that are slightly different, don't be concerned again. It's it's what we're going to accomplish as we go through this course is a deeper understanding of the power of analytics. The reality is we're just using Google Analytics as a tool. It's really that data that it collects processes and database is allows us give to have that in a way that we can filter it and define it for best, for our needs. Okay, so let's move into the next section. Let's talk a little bit about how Google Analytics works 3. 1 1 How Google Analytics Works: okay. In this session, we're going to talk a little bit about how Google analytics actually works. And to do that, I need to introduce you to a couple of the navigation components of Google analytics. Obviously, we're logged into what's considered a demo account for Google analytics here, and we're actually in the actual software now. So we're on the overview screen, and we're going to go through all of this in detail. But what I really want to draw your attention to here is the top menu bar. Essentially, analytics has three different components to it. Major components. And that's reporting where you're going to spend the majority of your time customization, which will get into more of the advanced training section and then the admittance section. Now I'm going to make some assumptions under the admin section that if it isn't already in place, you're going toe. Want to get into place? The first thing, of course, is you need to have a Google account. This is the top level, if you will, of the Google Analytics interface. So we have the account level and then we have different properties. If you have multiple websites, you can have multiple properties under that single account to you might you might separate , for example, sub domain sites in two separate properties. Okay or completely different brand sites that you might have under different properties, but it might be one single account that you have. You then have the view level, so at each property level you can have multiple views. The assumption that I'm going to make is that you already have a Google account set up and you're logged into your Google account. I'm also going to assume at the property level that you have a development team or a programming team that's actually implemented what we're about to discuss. And that is how Google Analytics works. The back end the coding, if you will in behind Google Analytics and the reason why I'm going to assume that is because when you start dealing with the actual set up, it's absolutely crucial that analytics is set up properly. And whenever you're dealing with the back end, of course, you're dealing with code, and you want to make sure that whoever is installing this on your website on your Web properties, wherever you have access to be able to install back in tracking information, Um, that they know what they're doing and that they've installed this properly. We're going to start by talking about the tracking info, which is right here. If I go under the property, I've selected the property here, and you can see we only have one property under the demo account. And if I go into the tracking code, this is the code that would need to be installed on your website. If you're running a wordpress website, you could do it as simple as a plug it. If you're running a full HTM l site, it's going to be have to be added to every single page on the website. And I say that with emphasis. Because if you miss a page, imagine how that would affect your reporting when you're looking at, say, for example, navigation or the landing page where somebody actually arrived on your website. If they arrived on a page that didn't have tracking code, that's going to change the reports to communicate incorrect data to you. So it's really, really critical that it is set up properly. Okay, now, often, programmers will use what is called Google tag manager to put one single piece of code similar to this script on your website and add all of these cat these scripts into basically a been within the tag manager. See, you can have one place that they can go to an at upload Google Analytics tracking code Facebook. Ah, pixel code. Whatever the case may be in that tag manager, that single piece of code that they've put on their on your website pulls in all of those different tracking code. So this is a nice way to go. You don't need to know that per se to be able to use Google analytics just like to know that it is set up properly so and how that set up half happens so that when you're actually using analytics, if you're seeing some disconnects in the information that you're reading, it might make you question the set up to make sure that everything was done properly. And I'm going to show you how you confined this code on your website in the very next session so that if you again, you run into that disconnect in the reporting that you have the ability to go in and check to make sure that the code is present on your website 4. 1 2 How Google Analytics Works: up over to the measurement doctor website here, and this could be any website. This is our our measurement website, where we run blog's and post on a regular basis regarding his measurement. But what I really want to show you here and this could be accomplished on any Web site in a browser. If I right click, I get the option to view page source. When I do that, I get this back end code of what's happening in behind the page. They don't get overwhelmed by this because it really doesn't matter about all of the different lines of code and you can't hurt anything. You can't change anything here. It's simply a read on Lee view that we're seeing here. But what I want you to do is do a find. You can do that on a Mac by holding command f um, or on a PC by typing control F. And what you want to do is simply type in you a dash, and if you're lucky, you're only gonna have one of those. But, you know, depending on the content that's on the page, you might have more, and you might have to filter through them. But what you're looking for is this right here, there's you a tracking number on the back of the website. Okay. And this means that on this particular page that Google Analytics is working in tracking on this particular page. So if we go back to analytics, we can see what we're seeing there. Is that you a number right here on Lee, representative for that web for that particular website. Now you're you. A number is going to be unique. And for each property that you have, you will have a unique number as well. So it's really important that it matches yours. And it doesn't really matter that anybody can see your you a number, because there's no real purpose in them putting your you a number on their particular site . They wouldn't be able to see the information. So it's not like its top top secret confidential or anything like that. Okay, so that is the critical aspect of the back end installation. And if that is not done properly, if it's missing on pages, well, it's like garbage in garbage out. You're not going to get the right data coming into Google analytics, and you're going to start making decisions based on incorrect data. And that's when problems really, really start toe happen. So take the time to make sure that that is properly configured. Okay. The other thing that I want to point out is that you have other linking in the products category here under the property. Other linking that you conduce to pull data into Google analytics. So in a lot of cases, external applications like, for example, AdWords if you're running AdWords campaigns has their own data, which you can push into Google analytics, and it's important that you actually create those linking account. So if we go into the AdWords linking weaken, see that there are two links to two different AdWords accounts here that this demo account is linked to. Now, chances are you're probably only gonna have one account, but you may have to, because you can group them separately. But if you're running AdWords data and you want that to show up properly in analytics, you have toe link it here. So that's really, really important again. If you don't have that data coming in, there's chance for error in the information that is being reported with in Google analytics . Even if there's no errors that you're seeing, you're not going to have the full picture. And we'll get into that as we start to look at the reporting for AdWords. But just know that these links have to be made. I'm going to show you one other link that has to be made so that we are sure that Google Analytics is working properly in the background. And to get to this link, we're going to go into the reporting section. And don't worry about what we're going into here is much as just checking to make sure that you do not have an issue here. When you go in tow acquisition, you're going to go down to the search consul and you'll click on the landing pages. Or when you click Search Consul. It may have gone into ah Page, which I'll show you an example of in a moment that basically says that you're not linked properly, and what you should see is this kind of data being displayed here doesn't matter what the data says at this stage. Like I said, we will be going into that, but just make sure that you're going, Teoh, that you have this data showing up. If you don't, Then what likely has happened is you haven't linked your wed master account to your Google analytics. And this is going to bring in your search data so again, very important that this is set up properly. Okay, let me show an example of what that would look like. Exactly. Here I am, in an account that has not had the link set up properly, although it has the break out of the pages under search. Consul, you'll see when I click on any of those pages, I get this notification. This requires search Consul integration to be enabled. Previous call It really previously called What? Master Tools now called Search Consul. Um, most people all identified as Web master tools. However, So again, if this is not set up, have your programming team go in and link these accounts. You can click this and set it up yourself. If you have access to your web master tools where your search consul Ah, lot of people will not necessarily have that. If your role isn't involved in the S e o side or the optimization side of your website. But it's important that again this be set up properly. If it's not, it's not that the reports won't be inaccurate. Without this linking, it's that you won't get the data that you could have from Google analytics so very important again. 5. 1 3 Limitations of Google Analytics: Okay, let's talk a little bit before we go into the details of each section about the limitations of Google analytics. And I kind of hinted at this. In the beginning, we talked about what is Google Analytics really? Well, essentially, Google Analytics is a reporting tool, nothing more. So it's taking the data that has been collected because of tagging on your website or any properties that you own that you can add that tag to. And it's processing that data and putting it into a database, which feeds the Google Analytics software, which you're able to filter and toss and turn and mix. However, you'd like to see that data presented to you at its root. A lot of people think of Google Analytics is as a counter. Oh, how many people came to my website and and how many pages that they visit and why all of that is good. That's not really the power of Google analytics, but Google Analytics isn't going to scream out and say, You need to do this to your website or you need to change this in your marketing campaign, or you need to adjust this in your S e O strategy. It is going to give you clues and hints, and that's really what we need to focus on. So knowing this up front, what I hope to eat, that evolves as you go through this training session and as you go through this course, is that you start to identify the nuances in the components that you can basically filter and slice and dice and segment to get the information that you're looking for specific to a goal. And we're going to talk a lot about goals. But again, this isn't going to scream out at you. So you need to think about how you would apply each section as we go through it into your own business or your own job role, and that is really, really critical. A lot of people come to me who have Google analytics installed on their website and they say, Yeah, you know, I look at it once in a while and that's great, But if you're not looking at it for the purpose of making decisions, actionable decisions, then you're really missing the true power of Google analytics. And again that limitation is it's not going to just scream out answers to you. You have to learn how to become a detective when it comes to data analysis and learn how to view the data to get the answers and actions, the next steps that you need to take from that data. Now that leads me to why Google Analytics is a marketing game changer. When you develop this skill, when you develop and continue to nurture this skill of data analysis, you're able to take your campaign, your marketing strategies. Your website designs everything involved with your growth of your business, and you're able to filter it down into the most micro view of the bottlenecks that are hurting your results and be able to test different strategies on those little bottlenecks to improve the overall results. And this is magical. This is really, really magical. It's the difference of working hard versus working smart, and when you have the data at hand and you know how to analyze that data, it empowers you to work smart, and it empowers you to make less effort and produce greater results. And I know that that that line doesn't necessarily, you know, make sense at the surface level. But when you start Teoh really dive deep into Google Analytics. You're gonna notice things about your data that is gonna surprise you. Now we're using the demo data for this training session. But hopefully what you're doing as you follow along is going through your own data and starting to discover some of these nuances that I'm speaking about. 6. 1 4 Interface Overview: So now it's time to start taking a look around the interface of Google Analytics, and this is kind of an overview tour, essentially of the interface and the different components to it. We're going to start at the top left here under the account level. If you have multiple accounts at in your, um under your ghoul Google account, this is where you're going to see those list of different accounts. If you move to the right and you have multiple properties under a single account, then this is where those will be listed and then to the right, your views. If you have multiple views and we'll talk about the views and ah, very shortly. But essentially, this is where those will be seen. We will also be going into why you might want toe have multiple views. You'll notice that we're working in raw data view here. OK, but I could switch between views if I have access to them right from that point. There, over to the right, we have a notification string screen where analytics will give us different notifications and suggestions as we go along. You also have the Google products and then your own account that you're logged into the top right is the period that you're looking at the current period. So if you do the drop down there, you can select a specific range, or you can customize that range in manually, select the range that you want to look at. So if I want to look at say, for example, the last seven days, I can click right there where I could have manually selected them seven days on the calendar. I can also select a compared to range here, which Google Analytics will automatically to default to the immediate prior period of equal length. But I may want to compare that to the prior year in this case of the first week of January , and to do that, I would simply change that to custom. So it stays selected, then choose custom and now go back just a little finicky on the way it operates. That's OK. We'll go there. So now I'm comparing the same period Onley in the previous year, I had apply, and all of my information then compares that that period to simply turn that off. Just uncheck that box over to the right. We have email export. Add the dashboard and shortcut. We're gonna be talking about this in future lessons as well as the segments. That's where we're seeing. This is a very important section of Google analytics, and we'll be talking extensively about segments. Down the left side is your categories and your menu options. So by default you will open up in the overview of audience. Okay, so again we're under the reporting section. I mentioned that in a prior session, and you have those four sections. But reporting is where you're going to spend most of your time, so we have audience above. This is more customization. So dashboards, for example, shortcuts, intelligence events and excluding real time. These three are all programmable, and we'll be talking about those in more advanced sessions as well and how to use thes features within Google analytics. Real time is exactly that. It's really time what's happening on your website. As I scrolled down, we go into acquisitions, and if I click on acquisitions, it'll fold it down. Same with audience. Then we have behavior and then we have conversions. So if we look at this from the perspective of your website, what we're talking about here is acquisition. How did they get to us? How did they find us? How did they come into our world? Okay, it's attraction behavior. What did they do when they found us? How did they behave on our website? Okay. How did they navigate around? What did they look at? What did they engage with? This is under the Behavior section audience. Who are they? What can we learn about them? Where they mail where they female? Where they were they from the U. S. Where they from the UK Were they from Italy? Where did they come from? Okay, Were they using a Mac where they were using a PC? Were they on a mobile device where they on a desktop? This is the audience section describing who that user waas and then conversions, often ignored in Google analytics and probably one of the most important components. Were they accomplishing the goals that we needed them to accomplish? OK, so these are the different sections and will be going through these in great detail over to your right. The main screen is your reporting section. So in most reports, although you can shrink it, you will have a a chart, so a visual indicator. And don't don't minimize that. That chart can be very powerful in showing you trends of what's occurring, an overview of what what's being reported on the particular report that you see, and then the details of the report that you'll see and we'll go deeper into that as well. By default, we're looking at a day view a day's breakdown. You can adjust that hourly weekly monthly, depending on the period that you're looking at. You can also manually force different metrics that you want to compare in the charting view there as well. Okay, so that's essentially the interface at a very high level when you first log in to Google Analytics. 7. 1 5 Understanding the UI: before we dive into a little bit of detail into the reporting and explore it. I should mention that when you're hopping around here, when you're jumping around between reports and you're looking at different data and you're changing the default dates, etcetera, you can't hurt anything. OK, so don't be afraid to just explore. In fact, I encourage you. Now pause this video, hop around, jump around and look around at the different reports. And just with the curiosity, sees some of the data that's being shown back to you. The worst case scenario. If you get messed up and you're in 2010 and you can't even figure out how to get back to an overview screen, you can always close your browser and re log into Google Analytics, and it will reset itself. So don't be afraid to jump around and explore. Okay, In fact, we're gonna jump into a report right now. Take a little bit more of a deeper look at the interface and some of the details that you can look at here so under audience, and if thats not open, just click on audience there, scroll down to the mobile section this is a really interesting report which will surprise a lot of people about your own data, and we're gonna click on the overview. And what this report tells us at a high level view is essentially the traffic that has come to our website that is, using a desktop or a mobile device or a tablet, and your numbers are going to be different than obviously what we're looking at. Everybody's numbers are going to be unique, but it is often interesting toe. Look at the percentages here of your traffic. So this is overall sessions. OK, overall sessions that have occurred on. We'll talk about the definitions of each of these metrics within the reports as we go forward, but just so that you know, this is actual sessions within this seven day. Actually, let's look at a 30 day period. We're gonna go 30 days and apply that. Don't forget to apply the date or it won't change, and we'll see that 70% of site visits was desktop. So it was using a desktop or a laptop off ah, full computer to visit the site. 25% was on a mobile device and 4% on a tablet. Okay, so let's say, for example, your numbers are reversed and you find that 70% of visits or sessions to your site were mobile. Then you better sure make sure for sure. Make sure that your website is mobile compatible, Right? Very, very important. That's just a quick little report to actually see that. But what I want to show you in more detail is if we go to the right here, over to the right of this report, you'll see these different options for how this report is being displayed. So right now it is on the data mode, which is very much a table mode that we can see here. But if I go across here, I can look at things from a percentage perspective in the pie chart mode, and this really puts a visual to your information. And by default, it's It's defaulting to that first column of data, which was sessions, but we can look at it from a bounces rate. We'll talk more about bounces in detail, but bounce it just quickly is essentially no action was taken. A visitor came to your site and virtually immediately left your site and we can see here now that the bounces on a desktop are much higher as a percentage of bounces, then say mobile, So that's kind of interesting. Okay, we're starting to see a story evolved. Okay, so that is a percentage view. Let's hop over now to a performance view. And again, this is a percentage. But it's another way of displaying the overall information is a very visual way. I can Then look at the next section, which is a comparison, so I could compare, say, sessions to bounce rate. Okay, so ah, the bounce rate in this particular case on a desktop is 9% to the ah, negative on a desktop versus 23% on a mobile. And we'll go into this detail as we go further into the reporting. Right now, what I want you to see is these different ways of displaying your data. And then the final one here is considered a pivot. Okay, so a pivot chart essentially, and we're looking at the data from that perspective. Now, on this particular report, the pivot report doesn't really benefit us, But other reports it absolutely will. Okay, so that's a different way of actually displaying your data and seeing your data. OK, the other thing I want to show you is the dimensions over here, and this also affects what we're seeing in the report down here. So let's say, for example, I'm going to show you a different report very quickly. Here. We were looking at the demographics of age. Okay, so here we have visitors by age category arriving on our site. Okay, so just so you know, that's the kind of information we can pull. Let's go back to the mobile here back to that desktop. And now let's look at a secondary dimension. I'm gonna actually type in a G to filter the results so that I can see age. And when I click that I'm adding that dimension into my report. So now I'm breaking desktop and mobile and tablets down to actually the age categories as well. So it's adding that second dimension into my reporting so very, very, very powerful because I'm not seeing all my data here. I can actually drop down to the rose section and expand it. We can see that it goes 18. So well up the rose to 25 and now I'm getting my tablet data in there as well. Okay, 8. 1 6 Advanced Search: adding the extra rose, we were able to capture all of the data. But as we go deeper into analytics, the reporting you're going to find that you can end up in the thousands of pages and rows of data coming at you. So being able to filter that data even on the simplest level, will be very, very useful to your analysis and being ableto zone in on the components that you want to focus on. So, for example, let's say this was a much larger report, and I wanted to see all the data that was related to Tablet on Lee. Well, what I can do is I can go up to the search bar right here and simply enter the word tablet into a search on that. By doing that, it removes all it. Google Analytics filters out all of the different rows of reports except those that are tablet related. So now if I was analysing tablet performance on our website and the behavior I'm can easily zone in on that information by removing all those rows. So that's one way to actually filter your data, and it could be very, very powerful if I change my report at all. Now that stays in place. So now I'm looking just at my tablet view. And isn't this an interesting report? When I'm seeing it in a pie chart for this particular report, it seems so much more powerful to see it visually, I can very quickly see the difference between you know, these three levels. So the blue, green and orange, which air 18 to 24 basically 18 to 44 are the majority of users and heavily weighted, like over half of the graph that are using a tablet coming in. But anybody older than that 44 so 45 above very quickly drops off in tablet usage. Okay, kind of interesting. Anyways, let's go back to the data side and let's take a look at something a little more advanced bar. Here we have the advanced function. If I collect click on the advanced here, I then get options toe. Add either dimensions or metrics. So let's say, for example, we're looking at those two dimensions that we have categorized. Right now, I'm gonna add the age 18 2 24 into the category, and I'm going toe. Add the device category of just Tablet, and I'm going to apply that. And then it filters out all of the data except tablets at the age demographic of 18 to 24. So it allows me to zoom in in detail and take a look at my the information that I need to see to analyze. So that is one great way of doing more advanced filtering is going into that advanced menu and noticed that the search function now has changed so that it actually displays advanced filter on. So if I need to even make a change and I want to look at some other data, Aiken simply hit at it. And let's say I want to now look a 25 to 34 instead. And apply that. And I'm not having to change out or do a full brand new search that continue to add addition variables, whether it be dimensions or metrics. Okay, the actual metrics here. So, for example, maybe I'm going to take this out. I'm gonna take it the age I'm gonna add a metric, and I want to see anything with a bounce rate. Let's go bounce rate. Ah, greater than oh, well, say 50% and apply that. And we're seeing that these air, the age categories that have a bounce rate greater than 50% on a tablet. And that's that advanced filter being ableto edit that data either by ah dimension, which air these two categories here that we see displayed or a metric, which is the information we see being displayed over here in the chart. 9. 1 7 Reporting Options: Well, we leave. The overview section of this training is one last thing I want to focus on. And that's the different ways to actually view the reporting as well as we could see just by changing from data to chart view. Looking at the Thea usage by device category was very, very in your eyes, very in your face as to what the data was screaming and saying actually was bound trade, I think we looked at. But there's a couple other things that you need to be aware of. One is the conversion section over here that gives us an option if we have multiple goals set up and we'll be talking about this more as we develop through the training and add goals to our reporting. But essentially, I can change whatever goals I've set up to report this data. Right now it's showing the e commerce data here, But I could say, for example, engaged users the goal that has been set up for engaged defining what an engaged users is. Ah, and Aiken, substitute in that report data right here. Now, we're gonna go up here to the chart section and the Explorer section. This section will change depending on what report you are on. And we'll see that in future reports where we add, say, for example, in navigation to have etcetera. But under each tab, there are often options which we can see right here. Actually, before I go into that, this little warning here there's some data in this report has been removed When when threshold was applied. What that means is because we're looking at demographics, right? So we're looking at age here in this case, um, Google Analytics is putting some thresholds on there so that you wouldn't be able to identify a particular user in particular. Okay, it's a privacy concern. So that's what's happening there. In case you're curious why we're seeing that in the report. And if you get that in one of your reports, Okay, so right now we're seeing this summary view, and I mentioned that we could add a second metric here, So let's say, for example, we wanted toe add ah, bounce rate into here. We could actually add that to the chart, and we could see a new line has been placed identifying the bounce rate because we have it separated by day we can see the effect on a day by day basis as well. So that's a functionality that we can put into the chart right there. But I can also dive a little deeper into the visual meaning of the data here by simply selecting, say, site usage. And when I do that, it's going to change not only the reporting down here, okay? But it also gives us different variables that we can add to the charting as well. Okay, so it just displays. It almost does a pre filter, if you will, so you can look at your data a little different way. So here we're looking at it from mawr of a behavior perspective. You know, these air how maney sessions. This is what happened in that session. They arrived. How long they stayed, how many were knew what the balance right was. If I want to look at it more from a ghoul perspective, it's gonna filter at that data and say, OK, let's list all the different goals that we can up to. It looks like five that it's listing there. Um, and this is all based on that goal information and same with e commerce gets its own section if you have e commerce set up and again, if we go back to the initial set up, E commerce should be set up by a developer. It is far more complex to, ah insurance set up properly on e commerce sites as well. But it filters out that report and gives you the e commerce data. And again, this is going to change depending on what your report that you're on. So if I go into safe, for example, um, the let's go acquisition and I go into source medium okay, um and I go into No, let's use behavior, actually, so I content country drill down. I'm losing all those. There we go. I was looking for another tab. So under landing pages, I get entrance paths as well. Still, get these summaries break out so I can change the data that I'm looking at the chart. But I'm also adding other options into the reports. And like I said, we'll go into that as we experience. That was reports going forward 10. 1 8 Admin Overview: that on overview of the lay of the land of the reporting, I want to go back into the adminsitration and just take a little bit of a closer look at this section. Now we did. Ah, I did describe the basically, this breaks down into three hierarchies of breakout. So you have your account level, which is, you know, the overall account that you have set up, and in this case, we're in a particular demo account. You can go further back than this. This is based on an account that you've set up for a grouping of website property. So it's not quite the highest level. The highest level is your own personal account that you're logged into. So if you had multiple websites, you may have multiple accounts here. And you saw that when I hit this drop down, you could see at the account level. I have different Web properties listed there, so that's that's the second highest level. But for analytics purposes, when you're in an account, presumably year, in most cases only going toe have a single account notice that I can control user management at this level, Okay, but I want you to know that anybody who's added as a user at this level has access fully down. Okay, so, again, hierarchy thinking the terms of hierarchy. If I go into user management, I can't see any cause I'm in a demo account. But I'm obviously at this stage. I can only remove myself from this account because I don't have access at this account level. So then we move into the property section and under the account understory under the property section, you can actually have multiple properties. Remember, we've mentioned that in prior session you might have your main account. You might have a store if you're stores broken off into a separate account, might have a membership section if you have a membership component to your site. This is where you would separate out those properties. It's also the level that you set up your linking that we discussed. Um, etcetera will talk about audience definitions in a later session view, which is really where I want to focus in the ad. Minced Action has a couple of components that are really important. Teoh to point out the first is goals and will be coming back two goals later. But This is where you would define and set up all of your different goals. You also have the filter section. So remember I showed you originally that under this demo, can't we have a master view, A test view and a rod data view? Raw data view tends to not have any filters set up The one of the purposes of stepping. Setting up additional views is to add filters. Now, here's the thing about filters once you set up a filter. So if I go into right now, we're in raw data view. If I go into filters here, um, were renaming AdWords campaigns and we're including a host name. So what that means is we're including the actual domain name in the actual reporting. Let's go back here and look at the master view, though. And let's check out filters. Okay. There are no filter set up in the master view. Let's check out. Other than the same, okay. And no. Okay, so they're all the same in the demo account. But one of the purposes of having those of different views is, let's say, for example, you wanted to remove your own companies. Um, usage of the website from your reporting. Well, if I added a filter to exclude our I p, then that data is forever lost. So by applying a filter at the view stage here, Okay, I'm gonna gonna say this again by applying a filter at the view stage here. This isn't a filter in the reports like we were doing in the prior session, but a filter at the view stage means that Google analytics is throwing that data away, never to be collected again. Okay, you cannot retrieve that information. So if I create a view, say, a master view that excludes our I P. From that view, the actual numbers that you see reported in the reporting they will differ from the raw data view because that filter is in place. Okay, If I were to remove that filter from the master view, my number's in the past would still be different. I can't retrieve that data back. I can't get it back going forward. It would match the raw data view because I would have no different set up a Sfar as filters go. But going back in time, my data would be different Because of that, it is really important to always keep a raw data view. Very, very important. Always keep a raw data view because that is all of your data collected and none of it being lost. Really, really important. Especially when you initially set up filters. In case you do something wrong, you always have that raw data view to go back to and build new views from. 11. 1 9 User Management: filters here again in just a minute. But let's let's ah, let's talk about user management again. Now, I'm not seeing user management in the demo account here because I don't have access to that . Under the demo account, I can just remove myself as a property. But in your account, you're going to see as long as you have the highest level access user management at the view level, it's gonna look very. It's gonna look identical to the account level where you should be able tow add users. Okay, In fact, let me just change accounts for a second so that I can demonstrate this better. Okay, so I'm in a different view, opened up a different view here, and we're going to jump into now. You see that? I have the user management at each level. I'm going to jump into user management under raw data here, and I could simply add a user to this particular view. Okay, And then I can give them read, analyze, manage users, edit, collaborate, type of access. All I want them to be able to do is read it and analyze it thing. Great. That's that's what I can do um so this is really, really powerful. Somebody added at the view level would not have the controls available at the property level. If I add them at the property level, they won't have the controls at the account level. So again, it's it really comes down to where that person gets added. And if I go back to the account level in this case, they've all been added at the account level. But if I added them at the user level, it would identify that right here. Okay, so it comes down to access and control as you're giving access to your data. Okay, So besides filtering out your data and having a raw data set up Okay, that is important. Why else would you have multiple views? And this becomes really, really critical as you have different teams working on your marketing and your campaigns that you want to give access to. OK, so let's say, for example, actually gonna hop back into the demo account here. Let's say, for example, we wanted to create a new view, So I go into, um, can't create views in there, so I have to go back to our other account here, Let's say, for example, I wanted to create a new view. I can create up to 25 use when in the imminence section. But let's say, for example, I have somebody who is responsible in our team that works strictly on our social media and maybe even only on just Facebook social media. Well, I could create a view for Facebook social media. I would then go into the filter section and add a filter that filtered out all data except data that had anything to do with Facebook. So now, by giving a person access to that view, adding that particular filter whenever that person goes into the reporting, all they're going to see is Facebook data. So if that person came from search engine optimization and never looked at our Facebook page, never ever came to our website from Facebook, they would not see that data in there. The beauty to this is that person con's zero in and focus just on the information that they can effect. They have control over because they're working on that aspect of the business. The other beauty to this is is potentially. I don't want them to see the other data. I don't want them to have access to that so I can control it right at this stage, very, very powerful. The final component I'm gonna add to that is under goals when I set up goals, goals, air set up by view. So the goals that I set up and we'll get deeper into goals much deeper into Ghost later in the course. But the goals that I can set up there will be directly related to the goals of that campaign and those people that are responsible for that campaign in that view. Okay, so when I create views and I apply filters to those views, it becomes very, very powerful in that the access becomes tied to that view. As long as I do the user management at this stage okay, the other aspects to the admin section in the view, and we'll be talking about things like segments and annotations and ATTRIBUTION models as we go forward into the course, Um can also be controlled and set up here. There's other ways to do it as well, and I'm gonna be sharing that with you again as we go forward into the course 12. 1 10 Audience Overview: the audience section of Google Analytics. Reporting again, as we stated earlier in the training audience, is Who is your visitor? As much as Google Analytics will provide that information. So we're gonna go through each section here and kind of break out some of the terminology and start to introduce you to the metrics and the different demographics that you're able to explore. So as a quick look, we're looking at a 30 day period where, on the audience overview report, we're looking at sessions by the day, and this is the overall summary of the more detailed reports that we're going to get into below. But let's look at some of these metrics here. First of all sessions sessions is the amount of times a user engages with your website. So during that engagement, they may have different things they click on. They may engage with different components, like videos or reading blog's etcetera, but that is counted as a single session. If we move over to users, we're seeing the total number of users that engaged with your website again over that period of time that is outlined in the top right. The amount of page views is the total amount of pages which were viewed during that period . The pages procession is the average number of pages procession. So, you know, they may go from the home page to an information page to a more specific page over to the contact page, and then maybe to the about us page and then leave. So this is an average of all visits, these little graphs that we're seeing underneath these Oh, these, um, overview numbers are good for trending analysis, so you can sort of see that this is running pretty even with a couple of little dips. Whereas we're seeing some definite spikes here over the 30 day period in this little graph which is duplicated cause here's the sections in a larger view, right, We're seeing that drop down so these can act as, um, unidentified air to concerns. If I look at bounce rate, that almost looks like it's on a little bit of a client climb. OK, so actually, we've done average session duration, amount of time. I haven't talked about bounce rate. Bounce rate is a absolutely critical metric, which we're gonna talk a lot about as we go through the different reports. Bounce rate means that a person landed on your site, took no action and left immediately. So they hit that dreaded back button in their browser, where they closed their browser. But they took no action. And we're gonna talk about balance. Very like I said further in the training session. But let's say, for example, I wanted to see that I want to see if that was the case. If there was a bigger concern there, I just click on that little graph there, and it switches the metric up here. So I came to see in a larger size. And sure enough, we do have a little bit of an incline going on here in the bounce rate, So that might be an early indication of a concern or potential problem to come. New sessions. This is the percentage of overall sessions which were brand new Dearing that period. So what does that mean for the other 32.16% of visits? Well, that means that you had returning visitors during that period, so some of these people came back during that period is well, and that would classify as a returning visitor as opposed to a new session. In fact, if we look over here, that's what the graph is indicating 32% 320.1 is returning. 67% is new visitors. So if you're running a blawg or something of that nature, obviously that metric could be important, especially if you want your visitors coming back. You want more of a loyalty. You may be concerned with that returning visitor metric. 13. 1 11 Audience Overview: report. We have some summaries going on here. So demographics, for example, language. What languages were coming to your website? Now? These air controlled by the customer, the user's computer, their browser, whatever their default setting is so in this case, English, US, English, great Britain. We're seeing the total amount of sessions and the percentage of sessions that that accounted for. In that case, we go to country. We're seeing the country visits broken out by country in any of these summary reports. Aiken dig deeper by selecting the View Full report right here. Okay. If I go into city, it breaks it down literally to the cities that are coming. Now, here's our first view of the term not set, and you're going to see this through out the reporting as we go through analytics. It's the dreaded not set ah report or Metro variable. Now, the reason why I say it's dreaded B is because Google Analytics is not able to communicate in this case what city that traffic was coming from. For whatever reason, they might have been a using a incognito browser. They may be blocking that as private information. Whatever the case may be, Google's not able to communicate that to you through the reporting. This, unfortunately, creates some limitations, but it's a limitation that you just have to deal with. In that case, if you're finding that in a particular report, all of your data is coming in as not set, it's a It's a a new alarm that you need to investigate any of this set up that we talked about prior in this session and make sure that your code is properly installed. I would definitely get your developer involved, but it is normal to have a certain percentage that is going to display as not set. We go into browser now we're talking a system were being on demographics there. There are additional demographics, though, and they fall under this section here where we have aged and gender. We're not seeing that here in the summary, but you can dive into it as well. Under system, we're seeing browser, so that would be your operating system. Are they using the chrome? Are they using? Sorry, none operating system. The actual browser that they're coming in on. So chrome safari, Firefox, etcetera OK, type of browser. This is important because if You see, for example, that you have a lot of users coming in on chrome, but you Onley have tested your website. Say, for example, on Internet Explorer by browser, your website Ken and often does perform slightly different. So if you're seeing, say, in the top five, a browser that you have not tested, that would be a good kind of reminder to say, Hey, I need to go check this browser and make sure that my websites displaying, as I expect operating system So Windows Mac users enjoyed devices IOS devices, etcetera service provider who they're using as their Internet service provider. Not sure if that has him is a metric that would be beneficial to know for your business. But if it is, you can have that type of intel from Google analytics and then they actually break out Mobile into its own independent category. And you're going to see that happen a lot more in the future, as Mobile becomes the dominant force in Web traffic. Okay, it's it's very common to see Mawr and an increase in Web traffic coming in from mobile devices today over desktop. In fact, it's now surpassed desktop, so they actually break it out. But these are the same things as you're seeing. Overall, here is a system. So we got operating system and separate segmented by mobile operating system. Same with service provider. But this one is interesting. This one is screen resolution. So if I go into that, it will display the resolution of the devices that are coming into my say, this is very much similar to the browser concern as to what does my website look like? How does it perform at these resolutions? And that's a pretty small resolution screen. 3 60 by 6 40 You definitely would want to be concerned if this was your site and it was number one and antiquated for 26% of all your traffic as to how it was display. Okay. And we're going to dive into this a little more detail as we go forward in the audience section of how you can look for alarms in this particular day. Uh, in this particular demographic, okay, 14. 1 12 Audience Deeper Reporting: reports and and breakouts that you see on the overview screen you actually won't find. As you dive into the sub categories, you actually have to access them well, you can access them through digging deeper into some of these subcategory reports, but it's actually easier to dive deeper right from the overview screen. For example, even though we're looking at the overview, if I go into the mobile section, I don't see Screen resolution here now. I could bring it up under devices as a second dimension, but it's just easier to come back to this main screen, go to screen resolution and view the full report right from here, and it will dive into that report rather than having to navigate deeper into other reports to get to this information. In fact, once I'm in this report, you'll see as primary dimensions multiple different types of segmentation that you can do right from this report screen that you're not necessarily seeing as a category. So just keep that in mind. Okay, so now that we're in this report, I just want to take a quick second and this is the first, the first tip at how to start looking at analysis in a different way. But what I want to really focus on here is we want to go into site usage on the narrow it down by site usage. We have that screen resolution which we're looking at from a mobile device perspective. Okay, I went to site uses so I could clean up my data a little bit here, and I wanted to focus over here at the bounce rate. Now, I'm gonna change this. I'm going to change this from the, uh, standard data table to a comparison report, and we can then change sessions here to bounce rate. I'm jumping ahead a little bit, but what I'm really trying to show you here is by using the tools of the reporting system, I'm very it's I'm having an easier time identifying potential problem areas. Okay, so we see here right away that if we scroll down to number 93 20 by 4 80 has a massive spike in bounce rate compared to the other resolutions. Okay, I'm gonna go back to data for a second, and we're going to see that that basically follows and is in line with the overall bouncer here It's almost 30% higher than the majority in some cases 40% higher than the majority of other browsers here. So by using this report and diving in, I can quickly identify potential problems just by doing that comparison, switching it over to bounce rate and looking for the experience that's happening for that audience. Okay, and what I would do with this information now is communicate that onto our development team or your development team. Whoever you're programmers are and say, Hey, listen, we need to take a look at this resolution because we have an abnormally high bounce rate at that resolution. Okay? So again, that's how we dive into this report, who is much easier to get to it from the overview screen. And that's how we can start to actually analyze some of that data as well. If I had gone in going back to the overview and I had gone into mobile devices, okay, I still have it here. I can go under other, and I have screen resolution. It's just not a direct access, so don't be afraid to use the overview toe actually dive into some of the more data that you want to look at. That's present right on that overview screen 15. 1 13 Active Users: dive into some of these more detailed reports and start to analyze some of the data we're gonna begin with. The active users report Active users is really important to a site that wanting toe have daily engagement or engagement that is repeating on a regular basis. Essentially, how this report breaks down is it's based on the last day so of the report. So we're looking at a period of December 9th to the seventh, and we're looking at how many active users on a day by day basis on this chart that we're seeing here. So we see 1635 is the average, um, of the one day. If we look at these page at the this chart, we see 16 35 on the seventh Food back a day were at 22 41 this is the engagement for that day. We look at a seven day period, then we're looking at a much higher number because it's encompassing an entire week of engagement or active users on the particular site. So again, we're looking at here of a seven day of that seven days. As of the seventh, we had almost 13,000 12,958 active users. So, like any business, you want to keep track of the level of user interest. If the numbers air consistently in line with your expectations, then you've kind of found your sweet spot right, and you want to continue to do that now. You may have seasonal trends where this happened. You have dips, but overall, you ideally want to see a steady incline. If we go 30 days and activate this number, this is probably more seasonal again what we're seeing here. But we're seeing a compile elation of a full 30 days. So if the numbers are below your expectations, you need to re evaluate your marketing efforts to see whether you're targeting the appropriate audiences. Maybe whether your ads or winning, you know, the auctions that you want or or your blog's or engaging enough. These are the kinds of questions that you're going to start to ask yourself when you see this data jumping into cohort analysis. Ah, cohort is a group of users who share a common character. If stick that is identified in the report and it's identified by a dimension. Okay, so for example, all users with the same acquisition date as we see here. This is a cohort type. Our belonged to that same cohort. Okay, The cohort analysis report allows you to isolate and analyzed based on that dimension or that behavior at groups, everything that you're going to see this report develop over time, as it is just in beta at this stage. But you're going to be able to hopefully be able to select a lot more by default acquisition types. Essentially, right now, by default, you have acquisition date as a grouping, we can see the cohort size by day bye, week by month. Let's switch it over to a week. Just so we get some larger numbers. The metric you were currently you're looking at user retention. So coming back into the site, But you could look at goal completions, maybe revenue per user, etcetera. You can change the date range right now we're looking at because we're looking at weeks. We've gone two weeks in the date range. So the last six weeks, and then if you start to look at the details of the data down here here you have the overall, um, date range with the bottom being the most recent weak. So in the last week we've had a 0% retention because that's what we're looking at here. But if we look at the prior week, we had a 4.5, so just a fall off in the first week of January, we go back another week here and look three weeks and we're certain to see the overall decline okay in data over that period of time, and it breaks it down by weak cause. That's how we have it. The cohort size identified here. Let's switch it today we'll get some smaller numbers. But now we're looking at a seven day range again by acquisition date. Kosher cohort size by day and we're looking at Use your retention. Let's look at gold completions here. Just give ah different perspective. These air percentages. We're looking at less than 01 The we the day of January 5th 0 2/4 a one okay and so on. So it's grouping users together to analyze based on that grouping type 16. 1 14 Demographics: so jumping into now the user Explorer report. This is a report that I don't particularly use very often because the data is slightly skewed. And what I mean by slightly skewed is notice. We immediately get this warning up here when we go into this report. And it says the report includes a high card in ality dimension and some data has been grouped into other. And the reason why is this particular report tries to give you an idea by individual user of behavior. Okay, so by this particular user, 44 sessions average session time, 39 seconds bounce rate, 93.18 Revenue transactions. Goal conversion, etcetera. And we're seeing the sort done by sessions. This is a great opportunity, actually, to point out that you can click on any one of these headings to sort by that category. So if I wanted to see the longest sessions, it would turn out that the longest sessions come from single visits. I'm just going to increase this row. Ah, let's go here to 50. We're seeing a lot more data here. This is also, um, you know, just just gives you an idea of the sheer volume or size of the reporting and how it can be . But again, the point is going back to sorting by sessions. It's trying to give you an idea of individual behavior. But yet Google is adjusting it slightly to protect the privacy of those individual users. Can there be information basically extracted from this report? Yes, absolutely, you can. I would probably focus Mawr on doing a segment on looking at this report, and we'll talk about segments in a future future session. But looking at individual data here would be challenging at best, to make actionable decisions based on this data, however, it's there. And certainly if you want a micro down a little and maybe look at a single day, you might get a little bit more information from it. If you've made a particular change on your site and you want to see how individual users behaved, that might be a purpose where you might use this report jumping into demographics. Here's where we start to hit some really key information. If you want to analyze the different behaviors on your site based on things such as gender and age, so right from the overview screen. We see a huge, um, difference between the amount of visitors that are female versus male and right away from the overview. My mind, my analytical mind, is saying to me, Is there a reason why now if my audience is primarily male, then that's great. It totally makes sense. However, if my audience is not skewed towards a gender than why what? What is happening there? And that's where you can dive into a deeper report the gender report and start to analyze that from the other metrics that we're going to see in just a second same thing with age here. We're seeing that over there. There's a very large spike between that 25 34. Again, if this is your target audience, perfect. If it's not, then you need to dive deeper into the age detailed report and start to analyze this data. OK, so let's jump over to the gender report here for a second and actually take a look at this in some of the metrics that we may be concerned with 17. 1 15 Demographics: gender report under demographics were taking a deeper look here to see what's going on. We see that we have the separation of male and female, and by far as was shown on the overview screen, we have a much higher density visitors that are male over female. So what I want to do is I want to look at some concerns here. Is there Ah, higher bounce rate. Okay. And in this case, there's a small difference, but nothing really major there. Is there a difference in pages per session? Not much average session duration. Not really. There is a difference in transactions, but that makes sense. In fact, you know it's not bad when you when you consider the overall were more than double the traffic is male, and we're slightly more than only slightly more in overall revenue. So I'm not seeing any alarms here. I'm not seeing, for example, the female gender not resonating with the content that they're not bouncing they're diving virtually is deep as the Thea um male users and their spending about the equal amount of time. If I go into site usage and just kind of clean up this data a little gives a much larger view, but it's the same information, right? We're not seeing anything really concerning here. I want to If I go back to that overview screen I saw this spike. So I'm wondering I'm curious if I start to look at the age, I'm obviously going to see that information replicated that I was seeing in the overview. But what if I combine the two? So now I'm gonna go back to gender, I'm gonna select secondary dimension. I'm gonna add age and we're going toe. Look now for any nuances here in this report, and what I'm gonna do is I'm going to change the view here Before we do any kind of advanced filtering. I'm going to go over to the pivot table and I'm going to display the data is that way. Now, by default, it's going to set it up the way it was in the data, which means I'm looking at the metrics. Ah, the pivoting by gender pivot metrics is by session, and I'm gonna change that to e commerce conversion rate. And now I'm starting to see some really interesting data as opposed to just looking back at that previous table where it was male, male, male. I'm now saying, OK, who's converting on my site? And it's starting to tweak the data so potentially. What I'm leading to here is there might be some decisions that can be made here, and I'm seeing a lot of data. I have about 12 lines of data here that's converting, okay, but I see that there's some really strange nuances that are happening. Okay, we have 35 to 44 in male and 25 to 34 in female, which is of equal kind of conversion rate. And then it seems to flip in the 25 to 34 male range and 35 to 44 mil range. Might just want to clean this up a little and really zoom in on whose converting, as opposed to having all this other data. So I might go advanced and I might go e commerce conversion rate, and I want a greater than 5% and apply that metric. And now I can really focus in on who are my top converting people. Right? And if I had not done this if I had not dug to this level If I had just left it back at that previous table, I might have only focused on males because they're by far my highest audience. And they're by far, um, you know, owning those top three spots as faras traffic and sessions. And I may have missed this potential opportunity of a very high converting audience, which is female age 25 to 34. So now that I know this, now that I have been able to kind of zoom in on this data and it seems that 25 to 44 is really the female range because that's all that showing up above 5% whereas the males go extends right through to 54. I may want to adjust my content what I'm doing and how I'm crafting and really target a section of my site potentially to this female audience writing here and not worry as much potentially above my 45 aged female audience. Okay, so again, we're just trying to build stories. We're trying to look for clues that helped guide us to better decisions. Get your hot back to this chart graph, and I'm going to see if I look right here I might make the bad assumption. Of what do we have? 27 37 44 54. 60% of all. My traffic is male 18 to 44. And if I'm looking at that, I may have ignored this category here. Okay, Female 25 to 34. Right. So again, by looking at your data in a different way, looking at potentially a different chart and doing some filtering, you were able to see the day data in a different light and take that information and dig a little deeper and make some decisions. 18. 1 16 Interests: other audience, uh, demographic, and that is interests. So we dropped down under audience into the interest section, and we hit overview. And this is pulling in information that Google collects based on user behavior overall on the Web. So we look at affinity categories. For example, you know technophiles, people that are in the technology, movie lovers, TV lovers. And they pick this up not only through their behavior and Google analytics being installed , um, the majority of websites in the world, but also their social behaviour as well that it's pulling in in market segments such as consumer electron, ICS, travel, hotels, employment, financial services. You know, what are the sites that they're visiting and what are they talking about? And then other categories. Arts and entertainment online communities, news travel, etcetera. Okay, and it's this information can be used in a lot of different ways. One of the more popular ways is that you would use the interest section is when you start to look at where you're going toe advertise online if you find, and we see some consistency here. Technophiles, consumer electron, ICS, mobile phones, arts and entertainment TV, video, online video. We're seeing some consistency in that top category right off. Very technical, very engaged kind of media might be a good target for advertising, But of course we can dive deeper into this because we break out these reports by component or by I overall category. So let's look at the affinity categories to start. When we jump into this report, we're seeing some nice consistency. And that's good that you're going to see. No matter what reports that you jump into, you're going to see the breakout of how you're focusing on the data under Explorer. You're going to see a lot of the same types of metrics such as, you know, sessions, new sessions versus repeating visitors, ah bound trait pages, procession and e commerce data. And of course, we can filter that view based on selecting the Explorer break out. But right away, when I start to look at these kinds of reports, I want to look for anomalies. So I might, for example, in this case take a look and see if there's a big disparity between any category, from the perspective of some key metrics, and I keep going back to boundary because it's a really, really important one. But I'm not seeing anything other than music lovers being a bigger. And actually, it's not dramatic either. No Huge difference. I've switched over, incidentally, there to the comparison chart. And I'm looking at Palin Story. What about time on site? So average session duration. There we go. Okay. Again. Fairly consistent. So I'm not seeing anything really, really bad here. And conversion rate. Okay, This one's kind of interesting right away. I see that technophiles 13.58%. But I'm also seeing way down here. Music lovers. Okay, A much higher conversion rate. So do I want to be promoting two news junkies? Probably not, but these three categories are very, very interesting to me. Going forward on how I'm going to attract my audience on a go forward basis. So, again, using the power of the different chart types, I'm able to see a different view of what's happening. Okay. Next, we're going to jump into in market segments again. Very similar data, just breaking it out by those segments. Consumer electron ICS, travel and accommodations. We just want to do a quick comparison. Know that we saw that big dramatic difference there in e commerce conversion rate and see if it follows in here. So we got air travel, financial services. But there's a huge leap there in air travel. And yet we want despite these being technic files, you know, we're seeing a much lower in consumer electron, ICS and computer peripheral as well. A software in business productivity, types of sites. Engagement. Okay, still kind of interesting. Other categories. And under this category, we're just seeing another way of breaking down the data arts and entertainment TV, video, celebrities, entertainment and weaken do a comparison there and has just expected, actually, with the conversion rate we're going to see, well, isn't that interesting? Under other categories, we're seeing a much larger spike in news and political well springs up an interesting point . What makes these categories different? Normally, when you're making ad decisions, you want to focus in either affinity or in market, where other is more broad, more vague, if any, of the audiences these audiences air built for basically, for companies or businesses currently running a TV ad, who would like to extend the reach of a TV campaign toe, an online context for basically a in a cost effective pricing. So the that's where this audience is coming from. When you look at in market segments, these air, designed for advertisers focused on getting conversions from customers most likely to make a purchase in markets can help drive re marketing types of performance and re marketing is something that you can do in AdWords, and you can actually now create re marketing list. We'll be talking a little bit more about that when we get into the AdWords section, but you can actually create re marketing list within Google analytics. Where is where as other categories is a little broad, broader scope. So we know that if we focus on in market, we're looking at audiences that are actually driving conversions, and Google Analytics has his data. But it is interesting from the affinity side of people that are doing other types of marketing as well traditional media in this case, TV and using online to enhance that present. So if you're doing traditional marketing and you're looking to expand into the digital side of things, this may very well be in audience that you want to pay attention to and how they're doing and where they're where they're driving their leads from what kind of categories are they reaching? Okay, so again, this is kind of a higher level report, its its interest. So it's geared more towards advertising, and that's what you're using this data for. 19. 1 17 Geography: all right, We're now going to look at the audience from the perspective of geography. Where they coming from? What languages are they speaking? I'm gonna focus mainly on location here. Obviously, we understand language, Um, based on the language that they're speaking or their at least their computer and their, uh, their mobile devices configured for. But location is where I want to really drive into, because there's a lot of detail that you can go deeper into within the reports. And this is a great report to use. As an example, this detail can be found in many of the reports that we've already seen and certainly the reports that we're going to go further into when I first go into geography location. I have a nice big map, so I can see you know, the sessions where they're coming from the darker areas, the higher volume. The lighter area is the lower volume on the map. But if I scroll down, I get my same type of table view and I can see by country the sections in the other metrics that we've seen in the other reports. What's really powerful is the drill in components, so Let's say, for example, your market is Oh, I don't know, a small city or a small town. Even if I'm looking at, you know, by country, that's probably not going to be of any value to me unless I'm actually servicing the entire country. And this is where the drill down can happen Now. I have a couple of options here. I could go wider. By the way, I can go continent or subcontinent. I can select city, though right here and drill in. Problem is, if I go city, I'm gonna get all the cities from all the different countries. And let's say, for example, Mountain View is the city that I am actually doing business in and can do business in. There's really no point in me seeing all this other data, So let's go back to country for a second and let's drill in a little. So this is where these demographics or dimension story become clickable, and you're going to see this in a lot of the reports that we're looking at, where you can actually dive deeper into the data. So I'm gonna click on United States, and that's going to break it down by state. So maybe if I can do business in any of the states I eat say I can do business all over California, then this information becomes much more valuable. But if I have to go even further, Mawr Aiken, drill into this. And now I can see the breakdown of cities or regions within the state of California. And now, if I want to go deeper, Aiken do So why is this important? This is important because a lot of numbers that you're seeing here within Google analytics are averages. Okay, So, for example, what I want to do here is I want to go back to the main screen of location, and I want to see that my overall bound trait is 41%. I want to pay attention to these numbers right here. 41% 5.2 pages. Procession two minutes, 59 seconds. Average session duration. My conversion rate. E commerce is 4.46%. Okay, so I don't have to remember the exact just, you know, 41% and let's go 4.46%. But what if I can't sell in India in United Kingdom and Canada and Germany. What if I can only sell to customers in Mountain View or that maybe I can sell everywhere? But the majority of my focus is Mountain View? Well, even though that's the majority of my focus, it doesn't mean that's the only people coming to my website. There's many ways to find a person's website, so these numbers may or may not be indicative of my true audience. So unless I actually drill in or segment, which will be talking about shortly, I'm looking at skewed numbers. So again, remembering 41 4.46 if you can remember those other ones great will dive in here. United States. We're gonna go into California, and then we're going to dive into Mountain View. And let's say this is my audience will look at the difference here. My bounce rate is 20.56 My conversion rate is almost double my bounce rates Less than half . Um, am I e commerce almost double. Okay. Actually, just a little over double. I'm seeing the averages right there of the entire site. Okay, so my average time on site, almost double my pages. Procession. 36% more than the average of the site. But if I made decisions based on those overall averages, there be a good chance that I would be making bad decisions where when I'm focusing on the audience, that is my true audience, I'm more likely to make better decisions. Totally make sense, I hope. Okay, I could even then, at that stage at age, as a secondary dimension and now start to focus on Mountain View four different age categories and see how that compares. So you're starting to see hopefully how just starting to play with the data, you can tell a more detailed story, a much more detailed story. In fact, this one's pretty interesting. 45 to 54 bounce rates lower than anything any of the other age categories, and conversion rate is significantly higher than some, but definitely higher than all other age categories. Does that information help this particular business potentially? Very much so. 20. 1 18 Audience Behaviour: behavior in the audience. Overview. Now behavior is where we really start to dive into. What are these users actually doing? Um, although there's a whole behaviour section, this is more to do with whether they're returning, how frequently what toe, what level of behavior. This particular audience is engaging with the site. So when we dropped down under audience to behavior, we go to new versus returning. This is the first report that you see, and we see New Visitor 50,808 which, of course, is 100% of new sessions and new users. It's kind of repetitive data, but we see returning visitors as well, and that makes up about 32% of the traffic to this site or 24,000 visitors. New sessions. New Year's wouldn't apply because it's a returning visitor and we can see, of course, when a visitor is coming back, their spending a little more time on the site, in fact, almost double and they're going to a few more pages. Which is good to know what I like to spend a little bit of time looking Atmore detail as opposed to new versus returning. Although I like new versus returning as a second dimension when I'm analyzing other data is I will go to the refree Quincy and Recency of a visit. Now this looks at visitors a little different. First of all, how many sessions a visitor actually takes on. Remember, a session is one complete visit, okay from start to finish. So obviously the majority of you users will likely be one. Unless you're running, say, for example, a membership side or a blogger or something of that nature where you may get higher numbers in the larger count, but generally one will be the highest number because we're dealing with a period of 30 days here. What I do like to look for, though, is anomalies. Is there spikes? And as we go through here, too, there's a little bit of a draw, a significant drop off, but it's still fairly high, and it continues to drop right up till we get to about 9 to 14 visits. So what's interesting is if I use this as a guide to put in a second dimension of 9 to 14 it will be interesting to analyze based on those users that come back that many times, if they convert higher than users that come back, say to toe eight. And the reason why that's important is because that tells us that a user may need a continuous feed of information or reaffirmation that they're going to make a good decision in dealing with your business. So we're looking for these spikes that we see here, and that's really quite interesting. The other aspect that's quite interesting in this report is the days since last session. Notice we have a different set of options under the report tab up here this time. So we're gonna look at days since last session, and this tells us how frequently they come back. So again, obviously, the majority of users only come ones. So the day since last session the majority will be zero. But then we again start to see a drop off. So 2200 come back, usually within a day, 1300 within two days, etcetera. And then we see this spike 8 to 14 days, 15 to 30. There's this a spike of sessions of a visitor returning after that period of time. If I'm thinking about this in my marketing aspect, This tells me that whether I'm email marketing or I'm running re marketing campaigns, this may be a magical time frame to be retouching my users to come back and engage whether lead, capture or purchase, depending on the site goals. This seems to be a magical time frame and using that in combination with the count of sessions, I can actually start to control some of my time frames and frequencies of contact. 21. 1 19 Audience Behaviour: the engagement report, and the engagement report has again to separate tabs that we can look at or sub reports under the tab distribution. The 1st 1 is session duration, so we see a breakout based on how long users stay. This can be very, very interesting when we start to incorporate the second dimension of conversion. And again we're going to talk about conversion a great deal more in future lessons. But understanding how long a user is actually engaging on your site and tying that to your angles can be very, very powerful in how you craft changes to your site. When you have this knowledge, okay, so right out of the gate, we see the majority of users only stay 0 to 10 seconds. If we know that, and we use conversions as a second dimension to understand that maybe 0 to 10 seconds is not converting traffic, then we should probably filter out that traffic before we make decisions on any of our marketing or design changes again, just kind of tying the different data together. And like I said, we'll explore that further, but we can see that a very big spike happened in around the 61 2nd to 602nd. Right in here we have some significant jump in amount of sessions, which totally makes sense. Page depth is how far a user actually goes into the site. So how many pages deep do they go? Do they just click on one page or in some cases, less than one, Which is very odd statistic there. But the majority is one page, so they land and they never leave. If you have a blawg, this will often be a very large number. Two pages, three pages and so on. If you remember back from the geography audience metric, we noticed that Mountain View, which was converting the highest, had, I believe, almost double the amount of page depth as faras sessions in their sessions. So knowing that we start to see some information here that can lead us to how do we get this traffic into that eight or six page range 6 to 8 page range? That Mountain View was actually spending on the site. So again, little clues that were guide you to making better design changes and potentially marketing changes, depending on the tab to going forward. Okay, now, we're gonna head into technology and mobile, and we're going to start to look at what devices are actually coming into our site as well . 22. 1 20 Mobile Technology: It's in technology and mobile. These are the two sections that we're gonna look at next. We look at technology, browser and operating system. This report tells us the browser that people are using when they come into our site. Aziz. Well, as we have different primary dimensions or secondary dimensions, if we choose that we can look at up here, Okay, so let's say, for example, we wanted to see browser, but we wanted to break it out by operating system. First, we can go into browser or operating system, so we see that almost uneven split, actually between Windows and Macintosh. That's pretty wild. Um, and then we get into some mobile devices, etcetera, and then we can hit secondary Dimension Select Browser, and we can start to see that chrome is obviously dominating, and it's dominating between Macintosh and Windows in a big way. But IOS Safari is also a big user, about 11% of the site. So we better make sure that safari on IOS device is rendering as we expect for our users. And a good way to tell is when you separate this way is to look at nuances in the bounce rate and right away I see some big alarms. We have IOS under safari and noticed the page. Drop the time drop. Okay, average session length. The conversion rate drop. Be interesting, actually to compare now that I see that mobile versus desktop as far as a a, um um device and see if there's a big drop off there. But now that I'm into this, I might want to do a comparison and look for big problems. Okay. Oops. Yeah, there we go. And look at the bounce rate. Windows, Firefox, massive jump. We have a jump there, but this is probably even a bigger concern Windows, Firefox and Windows Explorer and making sure that these browsers are operating properly from a Windows based machine. So this will guide us a lot more into as far as design changes that we might have to make as opposed to marketing changes. But remember, the experience in achieving the user experience in achieving your goals is very, very important. If a person can't navigate your site there, obviously not going to accomplish the goals that you want. Okay. Under network, we have the Internet service provider that they're coming in from okay, this could be useful. If you're doing any types of audits on your site for security reasons and you're running into any problems, you may look for nuances. Might set up a change month over month to see if there's been any spikes from particular provider. That's generally where we'll use this type of report. However there there could be other reasons. It's not a report that I use very often. Overall, I would go in Mawr. So to the host name notice Thea options up there, um, the primary dimensions. We have host name as well, and then I can actually see where that traffic is coming from. Misfires a host name again, not extremely useful in most cases. But, uh, depends on your business. Really. When we go into mobile, we have an overview and we see that we break down the desktop versus mobile versus Tablet. This is really, really critical. You're gonna find in a lot of businesses that the emphasis is on mobile and tablet. It's actually this is a unique situation now, today, where 70% of the traffic is coming in from death stop. But you want to pay attention to this report you want to understand what's happening to the audience that's coming in as far as the experience that we're receiving, and we're gonna be able to go far deeper than what we're seeing with these three metrics under audience when we actually start to go into the behavior section. But it gives you some insights in some warnings, essentially, and one in the warnings I see very quickly on this site is the e commerce Conversion Re is dramatically different between mobile devices to the desktop experience, So that's an immediate alarm that I would be concerned about going further into devices. Now you can actually break down to the type of devices that are actually visiting the site , whether their iPhones, Google phones, ah, Windows operating phones, which whatever the case may be, and again here, you're just looking for nuances in the experience. In general, there shouldn't be anything really dramatic. But as we saw earlier in the course, when we looked at resolution, we did see a dramatic difference. Okay, um, so just something to be aware of again 23. 1 21 Benchmark: going to jump down into the audience. Section two. Benchmarking Now benchmarking allows you to compare your data with industry aggregated data from other companies who share their data. Within Google analytics. This provides valuable context. In other words, it's it's helping into seem or set meaningful targets for your own your own type of traffic . Essentially, the very first thing that you need Teoh understand is that up here is the basis. So in this category, this section of the of the reporting is the basis that it's doing the comparison on. So you want to make sure that you've selected the right category for your industry. In this case, we're comparing two shopping, but there's over 1600 different categories available for you to compare to next. You want to set the region that you can actually provide your products and services in. There's no point in comparing to, say, an, uh, an international audience if you're simply servicing one region or one country, etcetera. So we're gonna change this. Ah will change this to United States all regions for the purpose of our example. You then want to compare to comparable size sites and Google bases this on the amount of traffic sessions that occur on a daily basis. So by default it sets 1000 to 5000 daily sessions. But you can go smaller. So if you're dealing or larger, for that matter, if you're dealing with a much smaller traffic site, maybe you might want to set yours to 500 to 1000 and compare against that particular data. So just make sure that you're choosing the one that best suits, um, your your situation. So after we've made our selections here, Google tells us that there are 217 Web properties contributing to this benchmark, and the benchmark again is an average of those particular sites. Okay, so in the report, as we look down, first of all, we can see the charting. Of course, we're looking at our sessions versus the benchmark sessions, etcetera. But more importantly, we're gonna drop down here into the basically the channel grouping, and this is the default channel grouping. You can set up your own channel groupings in the admin section, but for the most part, Google does a pretty good job of separating how we base our marketing, the situation where you may want to set up custom channels is when you get into really targeting your different marketing strategy. So maybe instead of social, you might break out Facebook if you're doing a specific Facebook strategy from Twitter, for example. But in this case, we're looking at a full grouping by the default channel, so we have referrals, referrals, air sites that are referring to your particular site. This could be say, for instance, another blawg on article directory could be a press release you distributed etcetera. Direct traffic is traffic that punches in or types in your your l directly or uses their internal bookmark to basically come to your site directly without going through any other channel. Organic search will be S CEO so organically optimized traffic from the different search engines. Google being Yahoo etcetera display would be display advertising if you're running to any kind of display advertising or paid search. If you're running any kind of paid search advertising social would be social media ah, site. So like Facebook or Twitter or a Pinterest etcetera. Email would come from other from email links that you put in emails that you send out. So any marketing that you do that way. We then have other advertising, which would come from any advertising. The Google doesn't have a direct link relationship with but identifies as advertising, marketing. And then finally is other any other category? Essentially. Okay, so when we go up here, we're basically looking in this particular report by channels at these different channels, and we're looking at how many sessions and underneath you're seeing the comparison. So, for example, referral traffic that our particular site has 11,543 sessions versus the average of this category, this region this size of about 2100 and 40 sessions. OK, and this is over a 30 day period. So we're above that. The average by about 439%. Let's scroll down to say, for example, so show where we see the average is about 33,000 sessions over the course of 30 days were at about 1695 so about 44% below the industry average. This may very well be in area that we may want to set a new target for an objective when we see that kind of traffic information 24. 1 22 Benchmark: okay. As we continue on here, we look at new sessions, new users. Let's take a look at the behavior that's going on here. When we look at pages per session, Well, I'm gonna use the social, since that's a struggling category. Pages procession were at about 3.1 versus the average of 2.96 So the quality of depth of traffic that's occurring there seems to be the same. However, the time on site average session duration is slightly lower, although these air not dramatic numbers a minute. 30 versus a minute 36 The bounce rate is about 47% versus 52% Again, not to bad. The big opportunity here that we can identify from this particular, um, set of metrics is that there's a potential for a great deal more social, same with paid, same with display. But we're kind of crushing it in referral, direct and organic compared to industry standards. Okay, let's move on to the location benchmark and here because we've narrowed it down to a single country. We're not really seeing the other countries. There were only seeing the United States in this case. That's okay, we're seeing based on country, our traffic is much higher. Our pages procession almost double an average time procession but 42% higher are bound Serie of 39% lower. This is we're kick him. You know what? When it comes to country, comparison in this category based on the size is OK, but we're looking at just a single location here, all right. And for the benchmarking, that's how it allows as well By country. I can't drill in on this particular report further into city or what have you We look at divisive and again same sort of thing. We're breaking it apart based on device, desktop mobile and tablet and then doing a comparison again are are vertical our region. Our session size is the is theme metrics that we're using to compare, but we can see that desktop were extremely high compared to the average. And we're not getting the mobile traffic that the others in this same industry of this size are actually achieving. Okay, so that would be an alarms to be concerned about right there. That or an opportunity that we can go after to improve. Remember about benchmarking that this is just to give you an idea of the competition, okay? It doesn't necessarily mean that you have to match it or try and excel beyond it in every, uh, in your decisions to go forward. But it just gives you some comfort. Knowing what the industry is doing. Google for a long time did not allow this information to be shared in Google analytics. It wasn't for actually several years that people were requesting it. And the reason why is because it doesn't matter as much to what the competition is doing as much as it matters that you're improving on your current metrics. So certainly explore this reporting in the benchmarking. But be careful as to how much weight you put into it. It is far more important to improve your numbers across the board than toe worry about necessarily the industry as a whole, I can tell you that one of the big reasons why people wanted to see this number these numbers is because they really had no idea as to the metrics. If this was good or bad, it wasn't so much about the traffic as much as it was. Is my balance right? Good or Armagh is my average session duration good or pages procession. And this reporting section now allows you just to get that idea, and that's how you should really use this particular data. 25. 1 23 Users Flow: low under the audience section. When we go into users flow, it's a visual representation of the traffic that comes to your site by default. When we first go in, we we see the beginning point as country now a couple of ah specifications that we have in this report. First of all, we have a zoom function so we can make everything longer or bigger and smaller for detail. And ideally, just to get everything on the main, the main screen up here a top. We have level of detail so we can show fewer connections or more connections right now. The way the reports displayed, it would be very, very confusing. If we increase that, it just gets more detail. You see the lines being added as to the different traffic flow, whereas when we back it off, it tends to group Ah, lot more of the traffic together, so we'll start a pretty much in the middle there. But that's the level of detail. Okay, so right now what this breaks it down to is the entry point is based on country. So you have United States, India, United Kingdom, etcetera and then it's showing where that traffic goes. So the largest section 20 per 20,000 sessions or 26.8% of total traffic, goes on to the home page. Okay, If I go down here to the next one, I see that you know, four point 8000 sessions or 6.37% of total traffic, goes on to the sign in page. But again, this this is all very chunky. Very. It's all very chunky together. So I can't really work with that per se. Now, what I can do is I can click on that because we're only dealing in the United States. I can click on the and either highlight traffic through here, which will essentially dark in those lines, enlighten everything else or view on Lee this segment, and it will remove the rest of the components so that I could just see this traffic and how it's coming in. So now it's a much more you've, ah, useful flow visual flow of traffic, if you will. Okay, so now we can clearly see that that next drop down was actually the sign in page versus what looked to be like the YouTube page. Um, because we've narrowed that down because we haven't inch. This is the entry point. There is no drop off where at stage to the starting pages were starting to see some red lines, which are considered drop offs or exits from the site. OK, so again, if we wanted to say, for example, highlight this section of the home page, I simply click on it and highlight traffic through here. And it kind of dims out the rest of the traffic flow. When I just hover my cursor over that page, I can see that 14,000 or 67.8% of the traffic continues on deeper into the site where 32% leaves from that home page. So again, this is just a visual, um, visual map of how traffic is flowing within your sight. It's a nice way to be able to eyeball it and see where the stronger pages are. Essentially, if I want to come to step back and I want to see Okay, Nest USA, Let's let's grab one here. There's brand YouTube bread. Let's work with that. One will go back view only this segment, which clear highlighting. Here we go and we're going to focus on traffic just through here. Explore traffic just through the YouTube page. And you can see now from this session and we're exploring YouTube. Now, YouTube has become the first page, essentially, where that traffic has gone, okay, and what pages it's moved on from. And you can see that as you go forward. Okay, actually back because this is step zero YouTube. So here's some other pages that have led to that YouTube page. Okay, it's pushed it over one, and that's where it's identifying it here. So step negative. One means that traffic came from within the site, but from different pages to this page. And then we have a 44% drop off from this page. But if we wanted to see traffic that came just from the home page to this page, we can click there and highlight that traffic specifically, and then we see that the drop off is reduced dramatically. Okay, overall, compared to the larger percentage of drop off of traffic. Okay, so coming directly from the home page, you have this small little grouping as opposed to the entire drop off, which is much more significant again. It's a visual. I I like to use the visual map ings as kind of a visual guide not to make decisions on, but to go take this information and go deeper into the behavior per our reports and see the navigation broken down specifically. So I use the visual as a high level. Okay, let's refresh this page for a second. And as it loads here, I just want to show one additional component here. If I step back, step back, right to your mean. So we'll just go straight here and click back to the main user flow. I can also change the primary dimension of how this traffic is getting here. So rather than by country, I can say, for example, change this to traffic type and this may be far more useful than seeing it from a country level, but rather seeing it from a a channel of traffic source. And this will now break it down by organic traffic, referral, traffic, direct traffic and so on. Just like we saw back in the benchmarking report of channels. Okay. And same thing applies. We can focus in on one type of traffic channel and go through the visual steps of how the traffic progressives 26. 2 1 Isolating Your Data: All right, welcome back to Google Analytics training. We are now entering the intermediate level section of the training course, which really means that we're going to start to get a lot more analytical. Have we excuse the pun there about how we look at reports. We spend a lot of time in getting our bearings in the navigation down, taking a look at the audience reports, which is definitely useful. But it's not going to lead towards actionable decisions per se there. There are some exceptions to that much like when we were discovering, you know, browser issues or resolution issues, that kind of thing. But for a lot of what we're discovering in the audience is really about the audience and who's actually coming to the site. So we're going to start out by talking about segmenting and segmenting traffic. And there's there's a reason why we like to start here before we dive into the additional reporting like acquisition and behavior and goals and what have you. And that is because up until this point, we've been looking at all of the data equally. The challenge with that is, if we go back to and in fact, let me just jump right in there if we go back to the geography. Remember when we looked at the location report and we said Is nice is this is we can Onley deal in our little city of our asses faras sales or Leeds or whatever we do for our business in this example that we were using and we drove in deeper into the report, we went into the country of the United States, and that definitely narrowed it down. But even at that stage, we were dealing with states that we couldn't deal with. So we drilled into California, and we said that Mountain View was our prime target. So he said, Okay, no problem. Um, we're going to take a look at, say, for example, um, let's go mobile and overview. And we saw the breakdown here. But we said, Hey, we can do an advanced filter Justus, long as we've added the dimension. So we'll begin by adding that dimension of the city. So we had a secondary dimension, and then we can do a filter where the city contains only mountain view and apply that. And then we were looking at numbers that actually mattered because, frankly, why would you base decisions on your marketing or your website designer or any decision that you're gonna make if that audience doesn't really affect you or affect your business? Ideally, you want to make a decision based on your ideal audience. So when we apply that filter and we sort everything out, we see largely different numbers. Right now we're looking at traffic that is, you know, 6.45% of the total traffic. And it breaks down differently as faras desktop mobile and tablet because that 49 41 in the bigger picture, please, a very small effect on these different categories that we're seeing there. So by filtering, we were able to narrow it down and just take a look at the data that actually mattered to us. Okay, hopefully that makes sense Now. There's a problem, though, that we have with this filter. And that is when we say, for example, we want to go now and take a look at ah, the resolution of mobile. So we go into devices and we want to see how our mountain view effects is there. We lose that filter so immediately, we are again looking at all the mobile traffic. So in other words, it's no longer specific to our ideal client to make that happen. We would then have to go back in, imply another filter. Well, obviously this convict come very, very tedious. What we would like to do is to be able to create that filter, and we'll use the word filter because that's what we're doing here and have it travel with us throughout the reports. And the way to accomplish that is through segmenting, and this allows us to actually isolate the data that matters to us of segmenting is very, very important. And we're going to get into not only the default segments that come pre programmed when you log into Google Analytics, but we're going to show you as well here how you can create custom segments. So the data is broken exactly the way you need it. In the very next session, 27. 2 2 Segmenting: Okay, so let's start by first going back to this report that we're looking at in Geo at location . And so we have the breakdown here, and what we want to do now is scroll up to the top here, right here, into what we see as all users. It's 100% of the sections, which means l the data is captured. That is captured is right here. So what we want to do is we want to go to the right of that in select add segment. Now you're going to see some custom created segments here. You may not see that in your analytics if you've never created any segments, or nobody in your organization has created any segments at this stage, but the ones that are blank that don't have a creative, modified or actual default segments that were created that are provided by Google Analytics . So, for example, we have mobile and tablet traffic. Okay, And this will allow the segmenting of that particular traffic. So I'm gonna check box that one. As as one of the segments that we want to see now I say one because guess what? We can actually apply multiple segments at a time, OK? We don't have to be limited to just one at a time, so it's pretty, pretty powerful assed far as that's concerned. So I'm just taking a look here, What else we're gonna select. And in fact, I'm going to We're gonna change that. I'm going to remove that one, and I'm going to separate mobile traffic from desktop and tablet traffics. And now you see, we have mobile traffic tablet and desktop traffic, so we're basically breaking those apart and I'm going to apply those segments, and Google Analytics is gonna process that information, and voila! We're going toe have now presented with three different charts. Okay, on the mapping. So we have tablet and desktop traffic, mobile traffic as well as all users. So if I scroll down here, we're seeing a much more detailed report. We're seeing that immediately. All users, of course, is what we were seeing before. But we've separated out mobile traffic from tablet and desktop traffic to make things super easy to analyze. So I can very quickly see that we have mobile traffic, has a 0.47 conversion rate. Okay, overall, this is overall versus tablet in depth stop traffic at 5.79%. So hopefully you can see and I'm hoping you're you're sitting back going Oh, my gosh, because I know when I first learned about segments, it changed everything. It allowed me to control the data and be able to see exactly what I needed to see to make decisions. Now, at this stage right now, we've just applied to default segments, which is certainly powerful by separating out this information. But we can take this a lot further in the custom segments, as I mentioned earlier. But let's go down here and take a look at that in the United States figure now. So we're seeing a new interesting breakout. But at this stage, because we don't have that segment created for our location, we still have to dig in. Here's the nice thing, though. When I click into United States and dive deeper, I'm not losing those segments that are applied. So they're following me from report to report. Okay, so now I'm seeing California. All users are going to dive into that, and there's are a mountain view. I'm going to dive into that and there is all of Mountain View so nicely broken out. There's all of Mountain view. There's the mobile traffic and there's the tablet and desktop traffic. Look at that conversion re on tablet and desktop traffic versus the total right, the total that we were seeing, um, back on the main page, which encompassed all locations, right? So if I made decisions based on that information, I would literally be making decisions based on information that was flawed, not completely inaccurate, because that conversion is actually happening, but not directed at my ideal audience. Okay, so hopefully you can see the value to this and I don't have to stay in this particular report. Let's say, for example, I go over to demographics and I want to see a judge. These segments are going to follow me now. It gets very, very busy, obviously, because there's a lot of data on this report, but we can see that, you know, based on age were immediately breaking the information out into those segments that are applied. Now, let's say, for example, you know I don't need this all users information because, frankly, it's just adding confusion to the report so I can actually turn off the segment of all users. And just look at this separation of mobile and tablet traffic so I can take that and really knee shit down the exact way that I need to see it. Okay, so now in the very next session, let's talk about how we create custom segments. 28. 2 3 Custom Segments: Okay, so here we are, back in the Google analytics were on ages. Just clean this up just a little. I'm going to click here and add back the all users, and I'm going to apply that and I can drag and drop the sequence and order of these it in time as well. Just for charting purposes, to be able to clean up the data. I'm actually going to remove these segments before we get into, um, creating a custom segment. So we've cleaned it all up now. Okay, let's go back to let's go back to the location chart so that we see what we have here as countries and the total traffic etcetera. And what we want to do is we want to go back into add segment. But instead of selecting one of the custom or default segments that air here, we want to actually create a new segment. Okay, so Google Analytics allows you to are actually tries to help you in creating your your custom segments by giving you some defaults that you can work from, and in a lot of cases, this is going to solve your needs or facilitate your needs. You can also get into advanced conditioning creating conditions. If if they don't have the exact metric that you're looking for, you can create those. But for the majority of time, you're going to find that these little Lizzie wigs help you guide you through to creating your segment. So we're in demographics. But let's say, for example, we want to create a segment based on behavior we can talk to start talking about, you know, session duration or the amount of sessions had to reach a certain amount, etcetera. Okay, so again, it just tries toe toe, make it easier to create thes segments. Aziz, you go forward, okay? Going back to demographics. What we're looking for, of course, is location because we want to narrow down to that city of Mountain View because that's where our ideal clients are in this example. So we're gonna first of all, change the the, um, the primary condition. Ah, to I've lost my primary dimension. There we go. I've lost my train of thought. There we go. So we wouldn't change that to city and we wanted to contain. You could also do exactly match. But we'll see how contains goes and we just start to type it, and it'll narrow it down to all the cities that are currently in your reporting. Okay, So if we didn't have any traffic from Mountain View currently in our reporting in the period range that we have selected, it wouldn't show up like this. But because we do, it is. And frankly, you'd have to wonder why you were making this segment if it didn't, if you didn't have any traffic from there. All right, so we've entered Mountain View, and you see a summary being created of the segment. The beauty to this is you immediately know that you're doing something right. You haven't lost all the data, right? If it goes to zero, then you've probably created a segment rule that doesn't have any match. So there might be a problem with how you're creating the segment. So we need to give this segment and name. We're gonna call it City Mountain View Mountain View, and we can even preview it. And what that means. Google analyst is gonna process the data and give us a little snapshot of it. Okay. City Mountain view right there. Okay. And so we know that it's working. If we want to see it at the larger scale, I'm gonna go ahead and save that. So we've now created a custom segment City Mountain View. But I'm still looking at all this data and have a lot of numbers here. I have traffic from India of traffic from United Kingdom. Obviously, my city mountain view is going to be zero under those categories because that's not where the city is located. What I really want to do here is I want to get a clean view. So I'm going to remove the all users and just drill in to City Mountain View. Now, my data is very, very clean. Even if I drill into these reports, nothing's going to change because I'm on the location. I don't know why all these air a mountain view in Wyoming, Apparently there is. Apparently, there is. Okay, so I might want to clean up that condition and be exact and change actually add the state as part of the segment as well. But that's okay, gives us an idea. Now we're gonna go back over to the mobile. We're going to take a look at those devices and we're going to see that all of this information All we're concerned about now is Mountain View, and that is all that Google Analytics is giving us a sfar as data. That being said, you'll notice that underneath the totals it's still giving us our site totals. So we know that for the City of Mountain View, 257 sections on mobile devices, which is 2570.34% of the total 76,000 sessions. OK, so we still have that data. But then when we get into the actual breakdown of the data, it is strictly a percentage of are segmented total. So 119 on an iPhone, which is 46.3% of the 2 57 and so on. So hopefully you're seeing the power of this. You conduce pretty much anything you can imagine a Sfar as how to slice and dice your data to narrow it down so you can zone in exactly how you want to focus and analyze your data through segments. Super, super powerful. Okay, super powerful. Now there is another option to creating segments, and I want to show you that in the very next session 29. 2 4 Filters: Okay, I've refreshed Google analytics at this stage just to show you back at a clean slate. How you access that segment that we created now Because when you log out of Google analytics and you come back in, it's going to default you back to the all users. That will be the one way that it kind of gets reset. Or if you go into it, men and come back to reporting, Um, you will likely lose your segments. However, they're not really lost to get that segment back. Now all I do is add segment and you'll see that that custom segment that we named and created on today's day is now in the drop down list. So all I have to do is select that uncheck allow users apply. And I'm right back to status quo with that segment. Okay, Really, really nice way to ah to handle your filtering, if you will. That being said, I did say I was going to show you another way that you can isolate your data. However, this way comes with some cautions. We're gonna headed into the adminsitration at this stage and over under view. You're going to see filters. But if you remember from our prior are earlier training session, when we talked about filters and having several views having that raw data view because when filters are applied, the data is lost forever. So what I'm getting at here is you can actually create a view with a filter applied to it. That Onley includes mountain view traffic. So therefore, when you go into Google Analytics, it's going to throw away all of the other traffic that does not come from Mountain View. And when you go into the reports, you're all sessions are strictly going to be that city. The benefit to this is obviously, you don't have to worry about creating segments whenever you want to create other segments , such as maybe social media segments or traffic sources or campaign specific campaigns. You're not dealing with separate chart lines in your reporting, so there is a big benefit to doing this. Just please, please, please make sure that you create an independent view and always keep that rob view that Rod data view untouched within your Google analytics Now to set up the view. First of all, we go into filters, and, uh oh, we don't have access. We do not have, ah authority level to create filters in this account because of our user setting. Okay, Um, again, it's just you if you don't. If you this is what you see when you log in, it's because your access doesn't allow you to create filters. Now I'm going to jump over to another analytics account just so that we can see the difference. When we jump into filters under view, we have an option for ad filter. We didn't have that back on this other account, right? And that's just a user access thing. Once we're in here, though, it's really simple to create the filter. We're gonna go add filter. We're going to give it a custom name Mountain View city. Okay, I'm going to give it a custom setting, not a pre defined pre defines tend to be I p based host. Name that kind of idea to exclude your own traffic. Um, there several different pre defined options that Google puts in his filters. But we need to create a custom filter, and we're going to include, okay, and we're gonna scroll down or we can just type in city there it is the location and we're gonna call it Mountain View que sensitive, not important search and replace advanced. Ah, we could verify this filter and it will tell us what it's going to give us. Okay, before filter applied after the filter applied. Okay, so its knees particular cities, obviously it's not showing up, but, um, you're still basically getting Onley that only that information So all of these air going to be wiped out, in other words, is what it say. Okay, none of those cities are going to be applied. Okay, So and then at this stage, everything set I would hit save, and we will be golden. This filter would be applied. I'm not going to do that because I'm actually in click OK to discard changes. I'm actually in my raw data view, and I certainly don't want to apply that filter in this view, because again, any filters applied from that moment forward, all of the data is lost. It's not that it's, it's temporarily filtered, it's permanently filtered, so this is a great way to do it. Just remember to use one of those 25 views that you have and ah, do your filters in those separate views 30. 2 5 Analysis Fundamentals: Okay, we're back here in Google Analytics on the audience or overview. Now, before we move into talking about conversions in the next session, I want to talk to you about analysis fundamentals. And this is probably one of the most important sessions you need to listen to for a lot of people. And we we train people all over the world and Google Analytics. And one of the biggest challenges we consistently hear is I don't know what to do with the data. I don't know how to respond. I don't know. You know, I can see that. It's telling me there was this many sessions, this many page views, the average session today, uh, duration. I can see the bounce rate. Either it's good or bad, but I don't know what to do about it. And I just want to talk about this for a minute. And I want to look at these categories that that you see here we have audience acquisition behavior and conversions, and I need to make sure before we go forward that you have it clear in your mind about how we look at analysis to create actionable decisions. Okay, on a go forward. So I want you to look at thes sections as basically components to your objective. If you have a website online, you have an objective. I'm sure. Hopefully you do. If it's a blawg, maybe it's to build your audience. Build your try. If you're in the B two b industry, maybe it's to generate leads. If you're running any commerce site. Obviously it's make sales. If you have a traditional brick and mortar retail store, maybe it's to drive traffic to your store, so you want to build awareness and and supply additional information. Whatever the case is, you have a goal. There is a reason behind your website. There is a reason why you put the effort to sweat the money, the time into your online presence. It's really critical that you document those goals, whatever those goals might be. For the case of this example, we're going to say that it's a B two B company and the goal is to drive reads You can think of conversions as goals. OK, that is the end result that you want to achieve okay when you know those and they're clearly defined and in this case, created in Google Analytics. It makes analysis meaningful. In other words, it directs us to actionable decisions. Now I'm going to go through this in detail. Of course, as we go through each of these sections, so it becomes much clearer. But I want to paint the overall Ah, high level picture in this session right now. So you see where we're going with this? If I step back prior to a goal occurring prior to that person coming to the website, learning about your product or service and filling out that lead form Okay, Prior to that lead form being filled out, I should say they're doing all that stuff right there behaving on your website. So they're consuming that information about your product or service their reading, the testimonials. They're getting the specs on what you have to offer. They're learning about what you're what your company is all about. And then they're completing that more information form or Senate contact us form. However your lead capturing at that stage. Well, if before they actually got to your website and, you know, toured around and navigated your site and learned all about you, they had to hear about you. They had to find out about you. And if we take a step back, we call that acquisition. This is your marketing. This is how you're telling the world. Hey, over here. Take a look at me. Okay? Whether that's social media, traditional newspaper advertising, whatever marketing you're doing, that's how you're getting attention. And you're acquiring that business visitor. So when we look of backwards in the order of Google analytics instead of forwards, weaken start to evaluate based on the destination, which, incidentally, is the most important part, right? The reason why you're putting the time effort sweat money into your online presence is these goals. So when I start to look at it that way, it starts to make a lot more sense how we can run into challenges as we back through the process. So maybe your navigation is really poor, and you're finding that people are spending a very short time on your website because they're just not able to get around your site very well. Well, that's a bottleneck, right? Or what we like to refer to as a resistance point in your process, in your sales process, in your lead process, right? Or maybe It's an acquisition problem, and all of the traffic that comes to your website bounces from a particular marketing campaign. So there's a disconnect towards what's being expected at the marketing side, the raising of your hand and saying, Hey, I'm over here, take a look at me and what they land on and first see. And if there's one thing that we've learned about the digital world is keeping the attention span is very challenging of your audience. So you got to be very, very fine tuned to make sure your meeting expectations at each stage of the process. So fundamentally, we actually begin with the end, and we work our way through back through the process and from that were able to create actionable decisions. Okay, so I'm hoping that made sense because it's really, really important that you grasp of that for when you start doing your own analysis on your own data. That's gonna help you start to find those bottlenecks, those resistance points and make decisions on change. And we're gonna talk about when you make those decisions what you do about them in later session. But at this stage, I want to give you that overview that the fundamentals of analysis come down to that process, starting with the end and working your way back. 31. 2 6 Template Goals: Okay, so before we go setting up some goals here and seeing how that process goes, I just want to scroll down here to the conversions and show you the different categories. Here. You'll notice that we have goals, but we also have an e commerce section. Now there's also multi channel funnels, and attribution will be talking about those in later sessions. But it's important to know that you can and likely should, if you have an e commerce site, have goals and e commerce data, and you'll get to see why that is as we start to create these goals. But e commerce data has to be tied to an e commerce site that's producing that kind of information. Okay, so it's very, very specific. If we're using the example of the B two B site for lead generation, you would not be using the e commerce section. There'd be no point for it because there's no transactions actually processing. There's only conversions. A Sfar, as a lead form goes, you know, actually punching your sail through your website so that would eliminate the need for e commerce. But they are separate items you'll notice in the demo account that we're here that we have here, that we do have goals that are active as well as the e commerce, because it is an e commerce site. Okay. All right. So how do we set up goals? Well, we head up first of all to the adminsitration, and we're going to run into that same problem because of the limitations on our views. But you're going to see here basically the goals that are already set up for the demo account. We just can't add any because of permission. So we're gonna jump over to another account and another demo account to see how that's done . But you're seeing that essentially, we have different goal I ds and goal sets. Okay. Overall, you're permitted 20 goals to be created within your analytics view. Each of you has its own goals. Okay, really important. And know that if you create a new view, you have to create new goals for that view, if you want to track goals. The beauty to that, of course, is you have 25 use 20 goals per view. You can pretty much have a goal for absolutely everything you want. As far as that goes, OK, let's hop over to this other accounts so that we can actually go through the process of setting up a goal. And we have a demo. Ah, a goal set up here. Its goal, I d one goal set one. So we have 19 goals left. It's actually not recording, which means it's not turned on this particular goal. You actually have to turn your goal on. We're going to new goal at this stage, and you're going to see the option to either use a template or a custom goal. Okay, for the template, Google's giving you some hints as to common goals that are often created. So, for example, you might have a revenue goal even though this is not e commerce. Don't don't confuse this with e commerce. Maybe, for example, you have a, uh maybe you're a nonprofit, and you have donations that you can take online. But because you're not transacting on multiple products, you don't want to go through the cost or trouble To set up an e commerce site, you can simply maybe, except those donations via pay pal or, um, uh, an external processing agent. But on your website what you can track those goals still as separate goals, because they're gonna have a certain value. So, for example, there saying here, a reservation they signed up for a tour, a rental or a reservation. You can apply a value to that because they're signing up for it. Even if they don't pay online, maybe you have to call them to collect payment. You can assign a value to that so it goes into your data, make a payment maken appointment, become a partner acquisition goals. Maybe they create an account, they successfully sign up for an account or they request more information. This is the same as creating a lead goal. Now you can do it through the custom, But again, analytics is trying to make things easier here. So they give you this as under the template. As a setting inquiry view more. They viewed product or service details. They pay very close attention to what they're saying that they viewed product or servers details. Maybe you're testing a new product and you want to see the interest level to it show you apply a goal toe, a particular product page, and every time somebody actually looks at that page, maybe for more than 15 seconds. That accomplishes a goal. So that's a view. More goal. Potentially contact at school. Self explanatory. Get an estimate. Very similar. They're just giving them different names here. See available. Find location, Engagement goals. This is a media play goal. For example. They played a video on your website, or they clicked a JavaScript based button. These air engagement based goals so they don't even have to fill out a form in this type of goal. They just have to click taken action. Okay, like clicking on something. You just have to take an action, and that can trigger this type of goal. 32. 2 7 Creating a Goal: Okay, so let's take a quick look at what this all looks like. Let's say, for example, we're going to go with, Ah, contact us. So we're gonna look at it from the perspective of a lead for the business to business. All I would do is check that box and hit. Continue and it's gonna pre name it. You can change the name. As far as that's concerned, it's selecting Goal I d. Two of goal set one. Okay, and you'll see that there's five. Um, well, there's 20 goals. It doesn't really matter which one you use. It's only going to show you the available ones. It's then going to give you the options of how you want to set this goal up. Now I'm actually going to go and cancel this. I'm going to go back because I want to show you the difference between that and going custom. If I hit custom and I killed Click continue, I get the same information. OK, so don't sweat it if you don't pick one of the he's a custom is the same thing. It's only going to it's only going to make you name the goal up front so it could easily be contact us at this stage, and I stand still have the exact same options. Okay, so a little bit of Ah, um hide and go seek. There's first what's gonna happen next, but it literally is the next of the same. Okay, So much like the breakout that we saw there. We have different types of goals, so we have a destination goal. What does that mean? If I'm on a contact us page and I fill out a form and I hit submit my websites gonna take me to basically a confirmation page that hate? Yeah, we got your form. Thanks very much. Or it's gonna run a JavaScript say forms submitted. There is a destination that's going toe happen. Okay, In that type of goal, I would simply select destination and select. Continue. But what if I was setting up the product goal? So that new product that I want to see what kind of interest there was. So maybe new product goal. Um X y z new product Next product, X y z. I might then put a duration goal at this stage. Okay, I might do a pages per screen or screens per session Goal. Remember the depth? Maybe Maybe one of my goals is to increase engagement because I've discovered that people that go more than four or five pages convert at a much higher rate. So I could set up some pages or screen screens per session goal. And then finally, in the event, as we described earlier, we played a video. Okay, in this case, let's go into the destination. We're gonna do that, contact us, coal us and we're gonna hit. Continue. Well, then, that stage, basically all we have to do is tell analytics What's the confirmation page? OK, is it a thank you page? So let's say, for example, your name is www dot my domain dot com slash thank you. Okay, that would be my destination goal. Except one thing here. One very, very important thing when you're full of filling out the U. R l for destination goals, you leave out the domain of the site, OK, and Google gives you a little hint here that says that, you know, you take it from the root domain. Now, if this happened to be, you know, contact us slash Thank you. Okay, because it's a sub domain of the Contact US page like this, which is very common again. All I take out is the root domain. I leave the rest of the path in as the destination. Okay, so I would delete that, and that's what that destination would look like. I can then assign a value to the school if a lead. If I have discovered that a lead each lead that comes in hasn't value based on percentage, that will close into deals and my average sales value, then I can punch that number in here. The beauty to doing that to actually giving goals certain values is if you're bringing in data such as your AdWords data where there's actual cox of data being seen, then you're going to see the prophet numbers for that specific marketing. You can also import your cost state if you like, But AdWords will actually pull that in just a long as you haven't linked properly. It's going to pull it in automatically, so that's an advantage to putting a value on the goal. And then we have a funnel option. Now funnel is optional, but if you know that you, you, your user processes through certain steps. By creating a funnel sequence, you'll be able to see if you have a resistance point in your sequence. So what does that mean? Well, maybe every user who fills out a contact US form must first watch um, the demo video. Maybe they can't even get to the Contact us page till they watch that demo video. And that's on screen demo video. Okay, are on page demo video. And if it's mandatory, I can put it as Aziz required. Yes. So it must happen if I put it was required. Actually, let me add a second step here first. So then they go from there to, um, are ideal customer where we tell him, you know, they give him a hint about who are ideal customer is to make sure that they understand maybe the investment that's going to be required here and they go toe ideal customer page. Okay. And then I had another step. That's the contact us contact us for right, and I don't have to fill out the thank you because that's the ending point. If I select required that they have to go into this step, then that's where they must begin from. If they don't begin there, they won't be included in this funnel sequence. Okay, I'm going to turn that off and then going to verify the school. It's going to say, Hey, we have 0% because these these girls mean nothing. Google checked our our site data and didn't see anything that matches that. So it's not a chance. Um, if you were to run this goal right now, you'd have 0% conversion. It doesn't mean that necessarily. You've done anything wrong, But if in the last seven days there should have been someone who hit this page that you've likely done something wrong and this is the point where you can fix that. 33. 2 8 Goals Overview: Okay, so now that we have some of those goals created, it's time to take a look at some of the goal reports. So we're gonna drop down to the conversion section, just gonna minimize the audience and go into the goal section. We're gonna go in tow, overview and very similar to the other reports, which, of course, is nice keeping it very, very, um consistent and intuitive for our learning purposes and usage purposes. But there are a few nuances that we need to be aware of. First of all, up at the top, you'll notice that we're looking at all goals. So depending on how many goals you have set up, that may encompass completely different objectives, one might be an engagement goal of time on site. Another might be a lead goal, which would obviously have a much higher value to it, then time on site. So you have the option of selecting the drop down and picking specific goals that you want toe look at. OK, so we have five goals here. We have a purchase completed, engaged users. Obviously, that was much higher. Um, registrations entered. Check out and smart goals and we'll talk very quickly about its Merkel's In a minute. We're actually in a session future session here. Um, so if we go into say, for example, purchase completed, it's going to change these numbers dramatically, right? Very much so, for the purpose of our demonstration will just leave it as all goals. But just so you're aware, that's how you would filter down. Essentially now we're on the overview report, so it's very much like a summary. We have total goal completions. If there were gold values assigned, this is where that value would total up. In this case, there were no values assigned. And that makes sense because we're actually running an e commerce component, which is tracking the values pulling those values in from the E commerce. A. There's not really a point at this stage of having a Google value here. We have an overall conversion rate that's going to differ so dramatically, though again, if we go up to the goals here until X a purchase completed, which would be one of the highest values, it's gonna be a much Mawr expected conversion rate. So again, just reemphasizing that we're dealing with totals here and you have that ability to filter in abandonment rate. This one's really quite important. Four purchases noticed that keeps disappearing when we look at the engagement goal because there is no abandonment rate at that stage. Actually, let me just pull that up here for a second engaged users. Okay, um, we have a conversion and there is actually an abandonment rate, but it's it's it's coming in at 0%. Okay, so it depends on how the goal set up, whether it's going to be able to track that with conversions, especially with the e commerce module running, it's really easy to see an abandonment rate back to all goals. But essentially what that means is somebody went through the process to purchase and left before Fan are finalising the purchase, and then it breaks out the actual goals right? 12345 There's your your different numbers, and again these charts are interactive, so if I push it, it's going to change the main chart to represent that total. Right there, I scrolled down. We have to sub categories Gold completion location, which is the U. R L. If it's a euro based goal. If it's not, if it's an engagement. It will be the final page that they were on. Okay, And then we have a source medium. Now, we haven't talked about source medium yet, but we will be shortly in the acquisition module. But essentially, what this means is, where did this traffic come from? That converted, and this is a pretty powerful report. Then we are going to go into it in detail. If I were to hit view full report here, it's actually going to throw me into the acquisition module at this stage, so I'm not going to do that. But that's a quick way to actually get into more detail about the source medium. Okay, Um, at that stage, we can go into the goal you RL's, and it's going to be basically a duplication of what you were seeing on that summary page. So if I go back to the summary, we have the completion location of youthful report. In this case, if I go full report, it's going to throw me right into that goal. You're else Page. So it's just the extension of that summary on the overview page 34. 2 9 Goal Reports: so continuing on, we're gonna look at the next report. The reverse goal path. Now, this report starts to give us a little bit of intel as to how the user progressed. We have the completion. You, Earl. Where the final. The final point was, um, where the gold was completed. Is this particular? You are well on the website. Then we step back One step. Where did they come from? So in this case review order, if we look down to, um, they're all pretty standard as far as the previous step. But that's essentially what it is going to happen if you have a check out sequence. As in an e commerce site like this, this is probably going to be fairly consistent. Same with the step prior to that and the step prior to that. If I narrow this down, maybe engaged users might give me some randomness. Here. There we go. So we have basket. Was the completed h ah, Goal you, Earl. Prior to that, it was the store. They were actually in the store component and prior to that, they had registered on the site. They completed a registration. And then prior to that they were. They were in the sign in screen, so they went to sign in, but they didn't have an account, so they registered. Then they went to the store than they checked their. They probably added something at the store and went to their basket. Okay, this was an engaged user. What? Qualified? Based on the parameters of that. OK, that's the reverse goal path that you're seeing there. The funnel visualization. If you recall that, we've got to take it off engaged users here because there are no funnels created. Ah, for the, um, for the engaged users. Those air gonna b'more sequence schools right where their steps involved. So if we're going to purchase completed, this would be the funnel that we would have created in the goal. So they came from the cart. Then they went to building shipping payment Review purchased. Complete the beauty to this report. This reports actually quite interesting, especially for e commerce sites where there is a sequence of steps and we can often identify in that sequence resistance areas. If you have too many steps or maybe too few steps or where are you losing the sales? Where's that abandonment happening from the site after somebody said, Yeah, I would like to buy this, but yet they don't complete the sale. This is where you can actually see this in a very visual way. So what happens here? What? We got 11,837 people that came into the cart in 6813 left. Okay, only 42% went on to the billing and shipping stage. So where did the 6000 go? Well, 14 992 left left the site another 1000 when it went to the sign in page. Okay, which makes sense that one's OK. Another 9 44 went to the basket, 5 66 went to the store and 3 63 went to this additional page here. So let's say, for example, your objective is to save as much as you can. Of this 58%. That's not proceeding through the building and shipping. You could say, for example, make a change to this page and see over a period of time how it effects this abandonment, this leaving for of the cart at this stage, and that's the real power towards this funnel visualization to be able to see that we move on to the billing and shipping. Well, guess what? Another 820 leave from there. What's wrong with his billing and shipping, right? We can continue to consistently improve on that page to get these numbers down, but 83% continues on 17%. Go somewhere else. We get to the payment stage. 83% continues on 700 leaves, um, or go somewhere else. We get 3500 that review 95% from the review page go to purchase complete. They've gone through a lot of trouble at this stage, right to to make your purchase your on the review page and you're still losing 5% now. It's not a huge number, not a big number by far. But if it is a big number for your particular e commerce site, this would fire off alarms. How do I fix this? OK, so that's the funnel visualization. We then have the goal flow, and the goal flow is very similar to what we saw before in the audience flow. Back in the audience section, the user flow, we have the source of traffic coming in. We're just skipping all the intermediate pages, okay? And we can change the beginning component, but we're seeing what happens in the CART stages against Step one, Step two, Step three. The very visual diagram. Finally, smart goals is something new that's been introduced, and it kind of tag teams with AdWords. So if you're running AdWords programs, basically, AdWords starts to create goals for you. Um, at this stage, I don't highly recommend turning on smart goals. It tends to have a mind of its own, but essentially, it's based on what Google AdWords deciphers as a good potential user. And if it sees enough actions that lead to conversions, whatever your conversion is, if it's being commerce site, it's a sale. If it's a lead based site, it's a lead. Whatever those conversions are, it starts to basically decipher what happens with those users that convert versus those that don't and set up goals based on those averages. Problem is, of course, in your in your conversion reports and AdWords. They tend to get bloated at that stage that, um, your conversion start to go through the roof, and that's why I'm not a huge fan of it. But you would need to turn that on at the AdWords stage. And you can certainly do that if that's of interesting. If I go into it, you're going to see, you know, was smart. Goal completed. No. Yes. Ah, these are the amount of sessions. So these goals were automatically created the smart goals by AdWords. And then it's evaluating what exactly happened with that particular traffic. 35. 3 0 Ecommerce: Okay, So now, before we jump into the e commerce, a section of conversions one thing I'd like to say about the goal section, and it's kind of funny, but it's true. You're actually going to spend very little time in the goals reports. And the reason why is after you've set up your goals, you're primarily going to see them and review them based on the different resistance points , whether it's behavior, whether its acquisition, whether it's who's coming to your site in audience, this is where you're going to see these gold numbers and they're going to bring on a lot more meeting. I like Teoh refer to this. You know, if we go back to the overview pages, um, well, go all goals, nice numbers. But I really can't take actions on this. I can't do anything about it unless I'd apply it to areas that I actually have control of, such as my marketing, such as my design such as my content, that kind of thing. So you're actually not going to spend a lot of time in this section of the reports, but it's good to know how to generate from or start at this position. If you're curious about certain goals when you initially get started, when we get into the deeper reports here of acquisition and behaviour going to see these numbers show up right in the data charts as we were seeing earlier in the audience. Okay, let's hop over to E commerce now. So, toe, have this data populated. You must have any commerce site and it must be configured and set up properly. We talked about that way back in the early sessions of the basic training and you definitely want to have a programmer do that connection, right? I mentioned that, and you're gonna very quickly see why, as we start to look at this reporting, first of all, these numbers are accurate numbers. They're actually pulling from your e commerce site. When it's connected properly, you're seeing the actual revenue numbers. You're seeing the actual number of transactions. The average order is simply a mathematical equation. But that's the actual average order. When you're down into the marketing side, you're seeing Berg broken down by campaigns, Kemp coupons used affiliate marketing. If you're doing any kind of affiliate kind of marketing, you're seeing the actual details of products product specific stuff. Okay, so this is obviously pretty detailed. This is pulling this all in from your e commerce engine. When I get into categories, product categories, these are the actual category set up on your website in your e commerce side. And if you have product brands Ah, you would have data here in this case, not set. So I just very quickly went over the overview page. But this is the actual data that's that's pulling in from the site. OK, dumb. We're gonna dive in a little deeper here into the shopping analysis side of things, and you're going to start to see some reports that are again using what's pulled in from your e commerce site to your general analytics tracking. So, for example, on the shopping behavior, this is a incredibly powerful report as faras impact. But again, it's not necessarily going to give you actionable steps, So it's nice to know, and it can certainly fire off some alarms that you're going to do some deeper analysis based on it, but is not going to tell you what the problem necessarily is. So at the top here we see, you know, all sessions this is analytics. No shopping activity. So they didn't go to any pages that our product oriented sessions with product views 20% no cart edition. 50% of those didn't add to cart, whereas 50% or there thereabouts did add to cart. You see the flow through going through here right from the 50% that adding to cart about looks like about 60 55% went on to check out what we got, 47% that abandoned in the cart again, this is very impactful. It might set off some alarms that I might need to check into greater detail here, but I can't really decipher for from this data what to do. Just that there might be an issue. OK, so it's a great visual. However, it it needs to be put in perspective. This is a high level report. I'm gonna need to dig further. Um, if I want. If I want Teoh get some actionable steps down here, I can see the breakout via new visitor or returning visitor. And again, how that differs again. Very, very interesting writer Returning visitor is 27% are going to of the total are going to view products versus only 17% of sessions with product views. I'm not sure what I would do about that, other than trying to have visitors come back more frequently, right? So it's not giving me the details that I really need to make some decisions. Their sessions. And this is just a drop down on Lee splitting out this traffic by the type of visitors. Incidentally, speaking of splitting out, I could even add segments here, right? I could just wipe out everything and bring back in our Mountain view segment. And then that data would only show that information. If I click on abandonments, it's going to show me the new visitor of returning visitor abandonment rates again using these steps in the sequence, okay? 36. 3 1 Ecommerce: okay, Moving into check out behavior again. Very similar. Only we've gone to the now they've they're checking out there following that funnel stages , right? So billing and shipping payment review the drop off and it's a visual. It's a very visual report. Same chart data down here, sessions and abandonment, and I'm not. It's not that I don't see value in these reports. They definitely will trigger me to look deeper. They'll sound alarms, but you can't make decisions necessarily actionable decisions from these reports. The point is very high level. At this stage. We go into product performance, and here we're seeing the actual breakdown of products. Now this is an area of the e commerce module, and I'll just minimize the shopping analysis that product performance, sales performance, um, a little less on sales performance product list performance if you want to go into categories related products, that kind of idea. But mainly product performance and product list performance are going to be a lot more important as faras in analysis perspective. Okay, um, because this is the only place you're going to see this data other than your e commerce platform. Okay, so you may get better data from your e commerce platform As far as analysis, however, the variable in here, the variable that you're going tohave is the analytics data from this particular for the for the actual analysis as well. Okay, so under product performance, literally, it's each and every single product. Their sales value is long as there's a purchase, uh, unique Purchases versus repair. Repeat purchases, quantity, average price quantity, average quantity. Any refunds that maybe happened shopping be, um ah, behavior reports. So carted detail rate. Okay, bye to detail rate. The car to detail rate is the product ads. How many products were added, divided by the views, right? So how it's basically telling us, how likely have somebody views it? They're going to actually purchase the product. Um, same abided detail rate. It's based on those average views overall. Okay, so some interesting data here and product analysis I just find that a lot of e commerce platforms people will actually do this auditing right on those particular platforms overall . But the data is pretty intense or there's lots of there's lots of information getting pulled in here, and we can certainly see it in the additional report sections where we can make better decisions. But, um, yeah, it just really depends on your objectives when you're viewing these reports. Now, what I do want to say again is when you're viewing on your platform, you don't have the analytics data, and that is the big advantage of these two different reports. The product performance in the product lis performance is you actually have the analytics data. So, for example, I could bring in a secondary dimension here. And maybe I'll bring in source medium to see how that played a role on these sales. Okay, so now this is a little different is if I want to. Let's clean this up a little. Let's just look at actually going to take off that source medium for a second. I'm going to drive into a single product, so there's a single product. Then I'm gonna add that source medium. We haven't talked about source medium yet, but we will in the future lesson. Essentially, what it is telling us is where that traffic came from. Ah, its source and it's type of traffic so we can see that the best source for sales of this particular product is directed. They had the direct you, Earl, to come from. Ah, second best was male. Ah, eso an email. Ah. Then Google sites etcetera and you go down and see when you get into, um types or mediums of cost per click ads. Cost per 1000 ads has paid advertising, and you could evaluate the effect of those marketing strategies on an individual product by product basis. This is something you can't necessarily do on your E Conor's platform. So that's why I say you may, if you're if you're running an e commerce site, these are two reports you may spend some time one and actually start to analyze. 37. 3 2 Ecommerce Marketing: Okay, so the final reports that we're gonna look at in the e commerce section as the marketing reports under the marketing reports, we have internal promotion order coupon product coupon affiliate code within your e commerce set up, you're able to set up so different different connections that involve internal marketing. So coupon codes, That's an obvious one. Any coupons codes that you have on your e commerce platform? Well, analytics will actually segment that traffic those orders so that you can analyze thumb. Ah, and how those coupons actually did internal promotions might be banners on your site that you have promoting other products or services within your sight. So this is all marketing but its marketing within the platform within your e commerce module. So let's go into internal promotion here, and we can see, um, out of the gate on the main report that it breaks it down by internal promotion names. So we're creating these promotions in our in