Today I decided to start working through the course material of Google’s Digital Analytics Fundamentals Course, which teaches people how the Google Analytics tools work, and how to use them effectively on a website, especially business websites. Although the official course happened last year, the course materials are freely available online. Although this is a little different to my usual blogs on here, I felt that it was important to do this course and discuss it here, to help me put what I have already learned about digital practices into a practical framework that will undoubtedly be useful in my professional life.
The course consists of a number of instructional videos, some text, and a series of online quizzes. There are six modules, so far I have worked through three. I made extensive notes that I will try to clear up and summarise here to help get them into my memory!
Changing Customer and user behaviour has changed how people approach measuring data. This is due to a number of major trends caused by online usage.
– Information is available to everyone (who uses the internet). For example, when choosing which business to use, site to go to, or product to buy, users have all kinds of reviews and recommendations to help them decide.
– Mobile devices mean people are connected 24/7.
– Cloud Computing, which means there is almost unlimited computer power available, and almost unlimited data available.
This means that customers and users need to be engaged differently. Rather than following a linear path (e.g. customer discovers your store, checks out your product, is engaged by you, buys a product, is retained as a future customer) the customers have much more control and can do these things in almost any order. Therefore, you need access to plenty of fast data to find out how they are engaging with your site.
Unit Two – Getting Started
This section covered why data and analytics are necessary for a good business strategy, and how they should be implemented.
There is plenty of quantitative data that is very easily available, for example, it is possible can track when users come to a website, what they do there, even where they have come from the get there. However, it is also important to back this up with qualitative data – the video lesson uses customer surveys as an example. this provides a more well rounded view.
Data should drive continual improvement. However, the data needs to be treated in the right way to make it useful.
– Measure the data – find out about your customers.
– Report the findings to the right people in your organisations who need to make decisions based on it.
– Analyse the data: trends, segmentation and benchmarking by making comparisons either internal data based on your site’s past data, or by the data of other websites and organisations within the same sector.
– Have an expectation for your site, then figure out if you do or don’t meet it and why.
Aggregated data will show overall user trends, but subsets of that data will show why those user patterns change.
Google Analytics will show common segmentation of traffic data. The video lesson suggested a number of useful segmentation possibilities, such as data, device, and geography. I’m actually already quite familiar with this, as WordPress, Soundcloud and YouTube all show this kind of data, although not in so much depth.
Conversion and Conversion Attributes
‘Conversions’ are an important measurement, divided into micro and macro conversions. ‘Macro conversions’ are key actions on a website or app. For example, if you are an online retailer, a macro conversion would be a user buying a product. Meanwhile, a micro conversion is an action taken that might be a step towards a macro conversion, such as downloading a coupon.
Attribution data works by assigning credits for a conversion.
A Last Click Attribution means that all of the value produced by conversions goes to the click that generated the revenue. But it might be more beneficial to look at all of the marketing that led up to the click. A user may interact with the website many times before the macro conversion, which shows which role each micro-conversion channel plays in the macro-conversion. An alternate is First Click Attribution would shows which channel first brings users to the site. Or you could assign a percentage of the revenue to each assisting channel.
Overall this shows which channels are used and how, as well as how they work together. Then you can allocate marketing budget and resources to the right places.
When creating a plan for using Google Analytics, it should always be changing. There are a number of elements.
– Start with a business objective, which states what you want to achieve.
– Have strategy and tactics. For example – if a strategy is to sell a product, a tactic is to have an online store, advertising etc.
– Choosing KPI – Key Performace Indicators, the numbers based on the statefy and tactics that can be tracked on a daily basis. Using this, a measurement report can be created that shows how the site etc. is performing
The video lesson noted that you should consider whether the site you have to capable of tracking the KPIs you want to have data on. Again, this is something I’m familiar with, for example, through YouTube I am able to track demographics of my viewers, including age and gender, which might be useful in building an audience. I cannot do this through WordPress, if I wanted to use a similar strategy on this blog.
Unit Three – How Google Analytics works
Some Types of Data
‘Dimensions’ describe characteristics of your users and their actions.
‘Metrics’ are the quantitative data of those dimensions.
The video lesson went into detail about a number of types of dimensions and metrics. Most of this I understood quite well since, as I mentioned before, I’ve already dealt with analytics through YouTube and SoundCloud. However the tools available are clearly much more in depth than the ones available on those sites, with more segmentation options.
The next three modules deal with how Google Analytics measures data in much more detail. I’m looking forward to doing them and writing about what I’ve learned. I feel that while much of the information in the first three modules was quite obvious to me, the focus on analytics for business put it into a new and interesting context.