Intro to Digital Analytics - history, strategy, tactics, myths and much more! | Richard Anning | Skillshare

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Intro to Digital Analytics - history, strategy, tactics, myths and much more!

teacher avatar Richard Anning, Digital & Psychology investigator

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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

8 Lessons (26m)
    • 1. Intro to Digital Analytics

    • 2. Digital Analytics Definition

    • 3. How Digital Analytics can help

    • 4. How did Digital Analytics begin?

    • 5. How did Digital Evolve?

    • 6. Beware the crystal ball

    • 7. Digital Analytics Myths

    • 8. Conclusion & Project

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About This Class

Are you one of those people who added Google Analytics to your site months ago, but haven't been back to check your results since then? Or maybe you're one of those compulsive checkers who peeks at your Google Analytics data every hour or so, without ever doing anything based on the results? The same can be said of your follower count on Social Media or how many likes your latest post is getting. If you are not sure why people don’t seem to be coming to your site or why your advertising can’t bring in profitable traffic then this is the course for you.

However, there is more to Digital Analytics than just Google analytics and in this course, I will give you the background of digital analytics. We will look at popular misconceptions, how teams should be structured, processes whilst always keeping the customers at the centre of our analysis and a focus on helping you create the best Digital Analytics framework. 

You should try this course if you are a:

  • A Founder who doesn't know where to get started
  • A Website owner who are struggling to understand their traffic and sales
  • A Marketer trying to build a community or find out more about their customers
  • Anyone who wants to understand a bit more about the theory and strategy behind analytics

This course is not for:

  • People looking for a specific how to’s on implementing the tools or how to create a dashboard
  • People who are looking for a quick fix or guaranteed income
  • Anyone who wants to implement Google Analytics and then forget about it
  • People who have a strong understanding of the basics and want to dive into more advanced topics

Find out more at The School Bell


Meet Your Teacher

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Richard Anning

Digital & Psychology investigator


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1. Intro to Digital Analytics: I guys, my name is Richard on Welcome to my introduction to Digital Analytics scores. In this course, we're going to have a look at what Digital Analytics is. We're going to move beyond just looking at the tools and dashboards in the guide that a lot of people offer to actually figuring out how it should be done. We will look at the history of digital and the history of the Internet to see how we got to where we are today. Then we'll take a look at the business models on how they've advanced over the years and what opportunities have been created. Once we have a good basis and a background into how we got to where we are today, we'll look at how well well run Digital analytics program can help any business. And then we'll start to have a look at how you congrats started with a career in digital analytics as well, if that's something that you're interested in, finally, we'll take a look at some of the myths and misconceptions around what Analytics is then will take a look at some of the hurdles you might face when trying toe set up an analytic program or build up your digital analytics skills until we're gonna break down where you need to look at. Finally, at the end of the course, as of every skill share course you'll be able to upload a project. Andi, In this project, you'd take a look at what you think are some of the key innovations that they're gonna happen over the next a few months and years, and then how people should be adapting to these shifts and changes. Well, let's get started with the first lesson, and I hope you enjoy the course. 2. Digital Analytics Definition: So now we're going to talk about what is Digital analytics. We're going to discuss the various definitions, the sort of areas that it can cover on the ways in which it can help business. Then we're going to go on to a little bit of the history of digital analytics before covering some of the popular misconceptions around it. There's obviously a lot more to digital analytics than just Google analytics and checking how many likes you get on Facebook and Instagram, and I'll give you the background of digital analytics in this course and really allow you to get deepened, understand some of the strategy, thinking and concepts behind it. You will discuss hell. Teams can be structured in what processes you can set up. That will mean that you'll always keep customers at the center of your analytics, and you always keep results and driving Optimization is and improvements forward. Now we're going to have a look at some of the definitions of digital analytics. Some of these definitions are pretty lengthy. There's a lot going on in the digital world of new technology and new software becoming available all the time in a lot of different areas and across a lot of different devices. This makes creating a succinct definition of digital athletics a little bit of a difficult task. So now I just have a quick think about what you understand and what you know about digital analytics today. How you would define it before we have a look at some of the real definition. So one of the big definitions is from a man named Avonex Kaushik. He's a digital marketing evangelist for Google, and he describes Digital analytics is the following. It's the analysis of qualitative and quantitative data from your business on the competition to drive continual improvement of the online experience that your customers and potential customers have, which translates to your desired outcome both online and offline. No, this is a pretty accurate definition off digital analytics, but obviously it's a little bit lengthy, and you should have come out the other end of it, not really understanding that much more about what it actually is or how to get started with it. That being said almanacs, Kaushik does write a great blogged that you'll find links to in the course notes, which is good. Occam's razor, which are highly recommend you send an hour to checking out, as he really does a deep dive into some of the conception. He gives him great overviews and framework, so they used quite a lot in the digital analytics world. Another definition, one that I think is probably a little bit more easy to understand, would be that it's about understanding and optimizing how your business is performing a live. This is a little bit short, a little bit broader, but generally you get the sense of what we're trying to achieve, what we talk back, digital analytics and what businesses and people are trying to achieve. And they instigated Digital Analytics program or higher an analyst. The most common way people get into digital analytics is fruit website analytics in tools like Google Analytics or from Facebook and Instagram likes, which is becoming a lot more popular in the days of influences where if you have a big enough following or you get enough people to your block, you can start charging money for it, they say. The more business focused approach, which is focusing on how many sales people are making on their e commerce sites or how many people are downloading that these are some of the first ways people get into it is the understanding what's happening. And then once they start to have a data driven strategy, and once they start to see some positive effects on their business efforts, then they start to look at how they can optimize and how they can improve their businesses through the understanding through the sort of insights and data that they're getting. 3. How Digital Analytics can help: If we now understand, what did you do? Analytics is and have a high level overview of what it can do and what it's about. It's now time to science. Have a look at how Digital analytics can help businesses. There's a myriad of different ways. Did your analytics and help, But I'm gonna focus on a few of the high level, more common ones that will cover off, over and over again in the course. So the 1st 1 is around managing smart goals and helping staff grow and learn. One of the things is if you imagine that the company or, well, where there is no data and no one's looking at the data, nobody would know if things were working off. They were making the right calls. So without some sort of Analytics and insights program, it's very difficult to set smart goals that are measurable and achievable on. That could be Time friend because nobody would know if they'd hit them on up. It's a little bit the same as an athlete trying to train and improve about getting any feedback on their performance. This is how analytics and help the staff grow and learn by providing a little bit of feedback on if they're marked in campaigns working or which products doing better than other products. So the next one is learning about customers, obviously, is very important part of running any businesses, getting customers and understanding our customers because the more you know about them, the easier it is to help and serve them. Then, of course, once you really start to dig into it, you can start to put these together and look at how star for performing, look about how customers are performing and then look at the website itself for the act itself to understand performance and uncover rule problem areas that maybe starve on creating the right campaigns or they don't understand customers enough. Or maybe it's just that there needs to be said, new ideas coming out because data will show you what's not working. What is working on That way you can help prioritize projects and come out of ideas off the back of 4. How did Digital Analytics begin?: So now we're going to have a look at How do Analytics began Onda. We can even go all the way back to 18 30 free. When a man with the somewhat brilliant name of Charles Babbage originated the concept of a programmable computer, he basically was one of the first people to understand that computers could be used for more than just a single task. One time that they could be reprogrammed. Andi, that this processing power could be used to do a lot of different tasks. He basically invented the punchcard system of programming computers that were actually popular until the 19 sixties, when they were still around. And still we used to lock to program computers and get data in and out of computers. Bill Gates actually learned this at IBM when he was a very young man, so they were around until very recently. But then in the 19 nineties, well, actually, in 1990 man named Tim Berners Lee developed the very first digital browser for the World Wide Web, which is where we get the www dot from. Of course, so the World Wide Web was initially just a way of sharing information really standard like word document or data information between different computers. He certainly didn't invent it, thinking everything that would happened in the following 30 years would have actually happened. So at the beginning in the 19 nineties were a pretty expensive and complicated time to manage a large or feature laid in website, especially since e commerce wasn't really a thing at the time. It is very difficult for websites toe make money off them. So most websites were online catalogues where basically it was just a little bit online shop front and then somebody would call or go and visit a store or they were just experiments in which people were just testing out this new technology. That's ah at the time as well, where there was a new coding language that went with all of this too. Basically allow people to create these websites. And that was HTML, which stands for hypertext markup language on a new protocol allow computers to trouble, which is hate TTP on these still, with the main forces behind the web today, analytics at this time such a zit waas was very limited. Basically, when you load ah website, you make a request from a server, and that request gets locked on these. They're called log files that people can go and have a look out and see which pages are being called and how often they're being called. And that was essentially all that the analytics Watts was looking at. How many pages were being requested on UH, it was also the year in which people tended to use hit counters, which just told how many visitors had come to a website. But there was very little being done to understand the customer or the person behind these hit. 5. How did Digital Evolve?: Okay, so now we're going to talk about digital platforms, digital business models and how these evolved over time, as I mentioned, digital analytics kept up very much with websites and got a lot more user focus over time and a lot more commercially focussed over time. And as you'll see, that's exactly what happened with digital businesses. They started off around the 19 nineties, when the first websites crept into existence, although up to today, where it seems like every businesses digital in some way. So first off there with just websites, they weren't very interactive. They weren't very colorful. They were often just text with maybe one or two photos on them, and they were very much like online catalogues. On the business model that worked with them was billed as the big business of that day was offering to build a website for companies. This was an incredibly arduous endeavor. The coding languages weren't very good. It was very difficult to host a website, keep it secure and keep it stable. So even building website was a difficult job back there. Unlike today, this business is still around, but it has a lot more competition from things that WordPress or wick allow you to build your own websites very easily without knowing any code. Then websites got a little bit more interactive. This is when you gotta look more sound. Video on things started rolling in and out. You could start to play games with websites as they could understand where your mouths was clicking or where a person was pointing, and this gave rise to advertising. So when they were first invented, banner adverts were an incredibly efficient way of getting traffic to your brand because they were very cheap. The new audiences were still very willing to click on them, so they weren't like they were today, where they're very much ignored on. Viewed with suspicion, people were really willing to interactive adverts, so that became huge business and it basically spawned some of the companies like Google Facebook that we've seen today. Social media is when businesses move from just being brands going. One way to people is that there be two way direction where people would start interactive people online about 2005 his, when faced with really launched made social media the big new kid on the block, shortly to be replaced by APs so that were around before 10 4015. But they really came into their own with Cloud story on much more powerful phones. The initial acts were something like your camera, app or calculator, app or contacts out that really didn't add much value. It was more when Facebook and WHATS app YouTube started coming out on phones that acts really became the reason to buy a phone in itself was early phone weren't sold on the power of the APP. They're sold on the battery life on the design on the screen size. But then, in recent years, we've seen that on a phone's processing power is the main reason to buy a phone. Nowadays, that, along with cloud storage, became a huge business model. So if you think of our apple, they didn't create act of their own, except for things like iTunes, which allowed you to move a lot of your physical products that you might have had a Walkman or something like that. Wonder iTunes, where you could have your music anywhere. You could access your photos anywhere, and Dropbox is another great example of this and YouTube, where you can suddenly start to access content anywhere on then. This allowed people to really join the mobile revolution recently, where we're starting to see the Internet of things, which is where the WiFi is going to enable more and more products to become digitally connected, like watches and headphones and cars. Now, almost anything is digital. Digital allowed people to move around and stay connected in their cars with their watches while they're going to runs. Amazon is moving into stores, so it now everything's mobile. Everything that can be is starting to be connected to the Internet, So the Internet things is the real new business model. 6. Beware the crystal ball: before we talk about the myths that surround digital analytics is probably good to talk about, something that affects almost all of us in every era of our life, which is that it is almost impossible to predict the future. And this has been seen a lot in the digital world where essentially people who made a lot of predictions in a lot of them have turned out to be very untrue. So now we're going to have a look at some of the things that people have predicted in the past that have turned out not to be so true. For example, the 1st 1 is that the telephone has too many shortcomings to be seriously considered as a means of communication. On this was by Western Union in 18 76. Shortly after that, well, 100 years after that, the president of the then very large company called Digital Equipment Corp thought that there would be no reason in what one computer in their home, although packed. It's worth noting that around that time computers weighed seven tons and they certainly weren't the user friendly machines that we have now, and they had a lot less functionality despite their incredible size, this is just a nice image from Total Week or film with Arnold Schwarzenegger that shows how people also mistake technology and half will grow in the future. Where much like with back to the future, they thought we'd have hoverboards and hovering cars, people thought that they put video technology in payphone. Nobody really sure, the rise of the mobile phone People typically tend to think basically something that we have now but slightly better, often hovering or with videos attached to it. And this isn't just some harmless fact about human nature that we're bad at predicting the future. It can very negatively harm companies. So this graph shows the sales of digital cameras in the blue versus analog cameras in the red. And if you think about Sony versus Kodak, Kodak went out business because it didn't bet on digital cameras. It better analog cameras on This turned out to be a bit of huge stake on this graph. Here. Choose the valuation of two different companies on, and obviously one bet on digital of one didn't on the Blue Line shows the value of blockbuster on the Orange Line shows the value of Netflix. So even though digital is a very hard thing to predict, it's very important to adapt to changes and to keep an eye on what are the right thing to bet on on one of the wrong things to better. So, for example, VHS is a new technology one over the beta max, and there's been lots of things that people are better in the past, including in the dot com boom that really didn't come off and didn't work. For example, with the Microsoft Zoom or Google's attempt to build a social network just haven't worked, so it's very important to remain adaptable and flexible. 7. Digital Analytics Myths: Okay, so now we're going to talk about some of the myths and misconceptions that people have around digital analytics in the world of analytics in general, these are pretty pervasive in society. They've changed over time. Andi is important that you're aware of them so that you can try and avoid them in your career and in your company. Because these are some things that really hold people back in their attempting to create a successful company. So the first myth is that people think that they don't need any analytics. They think that their company has enough information or that they're running along just fine without a strong analytics program. In some cases, this can be true. But in many cases, this just is a force assumption. Almost any business can benefit from an increase in understanding of their customers of their business and their competitors. If you meet a company who says we don't need Teoh gnome or about any of thes things, we know enough already, and we don't think we're going Teoh needed in the future. That's a company you should be wary off on for yourself. You may not have a roll right now, that requires analytics. But if you're looking to get into it, try and find any numbers that you can and see how they can help you to further understand your business on your role. Better so you don't want to become an ostrich with your head buried in the sand. So the second myth is that it's just nerds numbers that anyone doing analytics has, ah, higher degree in mathematics and looks it statistics in databases all day to look at confusing numbers and come up with algorithms and models to decide that uber or Amazon should price their next product. Somehow, myth number free is linked to this is the people often assume that analytics very difficult to get into and that there's a very high bar to entry. This is maybe true off more traditional database analytics, but in digital analytics, almost anyone can start because you've probably been doing it in your own life. When you look at your social media posts, seeing how many views and like to get and then start to come up with some hypothesis around which post do better, what gets more interaction, what time of day or what day of the week is a better time to post. That's doing digital analytics already, and that's you beginning to understand what's happening on what works and what doesn't work , and the type of people that like your posts, that is essentially digital analytics in itself. And that's something you can get started, but really easily. If you have a website you should put Google Analytics on and you'll be surprised how easy it is to get started with a lot of the basic numbers and metrics that you might need. Basically, if you have a website you should put Google Analytics on, there's a load of great courses out there. And so it's very easy to get moving on your journey to becoming an adult. One thing to be aware off is that analytics won't give you a quick solution. Essentially, it's a little bit like joining a gym. And when you get a personal trainer, many people think they're going to see results very quickly, and they're unaware off how long it's going to take to see results in the discipline and effort that comes with achieving results. This is the same in digital analytics. It's very easy to make some slow progress and start to understand it. But if you do want to progress to the likes of Amazon and Facebook and get real understanding, it would take a long time and a lot of discipline and start seeing the results. So what can happen is essentially the analyst, and you might start to find this in your journey. Is that because the senior objectives think that going to be a quick solution, they very quickly start to ignore analysts who aren't giving them the answers they want or the answers that they want quickly enough. So myth number five is that analytics is a finite task. This essentially means that lots of people think that they can just install analytics on their website, or if they hire an analyst, the job is over. This is quite similar to people thinking that once they've hired a personal trainer, they'll get a six pack, and then once they've got the six pack that the six pack will stay. This is basically not possible. Once you do analytics, you start to realize what you get into the world that everything is constantly evolving on . This basically means that you can't achieve this nirvana like state, where you're in light and didn't you know everything there is to know. There's always more to learn. There's always another test to run. There's always Mawr information that you can find out, and in more ways you can innovate and evolve your product. So this means that isn't a predictable analytic cycle. This is basically the ideal that is stored in a lot of universities, lot of schools, a lot of businesses that you come up with a plan, implement the plan. Look at what happened. Try and think about what's going to happen next, and then come up some hypothesis about what you should do and then implement them and then go round and round in that circle. But what often happens is companies innovate. There's new things happening all the time. New technology is happening all the time. Consumer expectation to changing and new competitors come in the space, which means it's really easy to go round and round in a circle, continually optimizing a product because you have to innovate and change. And it's very difficult to analyze something that has never been done before. So things like uber every and being Google They were very difficult to run strong and elicit programs at the beginning because they had such new offerings. So what they did is they focused on what's most popular and grew from there. But they were never 100% certain in their beliefs because it wasn't a circular pattern. They were essentially building a new path rather than going round in circles. 8. Conclusion & Project: Hello, sir. Now arms of the final video of the course, and we're just going to go through everything that we covered in the course of a quick recap, and then we'll cover off the project and how you can get in touch with me. Europe so inclined in if you ever have any questions. So at the beginning of the very first, let you remember, we discussed how analytics can help companies. Hopefully, this makes a lot more sense to now. So the first thing is around. Managing smart goals without data is very different to have measurable goals and seeing if goals are achievable. It also hopes companies understand their customer's understanding how they're performing. It helps them generate new ideas. Teoh improve their performance and better serve their customers. It helps companies and staff understand what they're good at. What they're not good at errors there week at and helps them learn and grow by providing real time feedback like a coach woods. The numbers allow them to really understand how they're doing and what they could be doing better. This enables them to get more customers in neighborhoods in tow, uncover problems Andi enables them to prioritize projects to understand which projected can have the most impact in getting more customers, making more money and solving their problems. So just to cover off the key things to take away about Planalytics from this course is that it's not just a collection of data is not just about the creation of complicated models, big tables that have very little impact on the real world. You and almost everyone you know is doing it in some form or another, either through looking at which social media posts you do get the most traffic or getting the most like how your website is doing what people are engaging with Andi looking at what makes a company successful? What makes company unsuccessful waded, Google beat Yahoo. Why did uber succeed where so many others have failed? And if you want to start taking it to the next level, getting bit more professional, start by generating hypothesis, right? Your office is down about how humans are behaving online and then find some data to test it . Run a little, test yourself. So finally, your project is a great feature of skill. Shown enable you to actually put your newfound skills into practice and maybe get a little bit of feedback on it and see what other people have written. And then we can start to see just how good well are predicting the future. So think about the Pacific business or business area win. Or you could just think about all businesses generally and then right down free innovations that you think will impact them in the future. This could be a new technology, a new platform or a new product that could come out and shift the way people buy things. If the way people find information or shift the way people speak to each other, it could happen in the next three months, or it could happen in the next five years. Then start. Think about how people should be adapting today to be ready for these ships. Think about what the shift is going to be, what impact it's going have. Why you think it's gonna have such a big impact or such a small impact on, then how people should be adapting to these changes. So the final thing is, thank you. Thank you for listening. The everyone to get in touch with me. There's my email. I hope you enjoyed the cause and look forward to seeing all your projects