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How to make data more human with Google Data Studio

How to make data more human with Google Data Studio

Code for Life now has over 130,000 registered users as far afield as Australia and Brazil, meaning we produce a lot of data in need of analysis for communication purposes, reports and user research.

An official Code for Life report requires many data sets, including the exact number of registered users or the countries these users are from. We also analyse in-game data like the real time spent on each of our levels in the Rapid Router game. Our data sets are gathered from various sources ranging from our Cloud SQL database to Google Analytics, Facebook, Twitter and beyond, which can make it hard to get a holistic overview of the project and its progress. We also have to consider that some people reading our reports don’t necessarily understand data jargon, like sessions, bounce rates or returning visitors. We therefore end up having different reports from different sources which are not easy to customise to our needs.

We needed to find a tool to help us sift through our data and draw meaningful conclusions.

The solution? Google Data Studio!

There are several visualisation tools, like Excel and Tableau, that allow users to access data and create reports, but unlike Google’s new visualisation and analysis tool, many are not easily customisable, nor available for all operating systems, and they don’t all allow connections to multiple data sources. 

This free, cloud-powered tool (currently in beta in the UK) already provides integration with multiple data sources. You can create reports that are easy to share and automatically refresh, so they will always be up to date every time you view them!

It is also dynamic in view mode; you can use your mouse to hover over charts to check values you are interested in, filter the dates you want to view and click for further details. In edit mode, on the other hand, you can create and customise beautiful reports quickly and easily.

 

 

Tah-daah! This is an example report!

Let’s look at some useful features, by going step by step through a real example: understanding how visitors find our website and checking if our product backlog reflects our findings. 

We start with a blank canvas containing just a few design elements.

 

 

You can select the calendar icon from the overhead header and choose a time range, so that your report will always be up to date. Here for instance we’ve chosen the last seven days.

 

 

We also decide to add a number of visitors scorecard, but the dark grey text color doesn’t quite fit on our blue header – this is easy to solve.

 

 

We can change the style of the scorecard:

 

 

While we’re at it, let’s also add a comparison with the previous period.

 

 

Now the “Visitors” scorecard looks better against the blue background.

 

 

Great – now let’s see how people find our website by adding a chart of referrals.

 

 

We can now pull our referral data and make it easily digestible using a pie chart.

 

 

Google Data Studio allows a lot of customisation. In our case, we’ve added a note to explain to our stakeholders what Organic and Direct mean, using the text box in the tool bar. 

This chart represents the traffic for all of our visitors, and we can see it’s mostly organic and direct. But we are also interested to know whether we get the same results for returning visitors.

 

 

Looks like for returning visitors search engines are used even more!

Let’s now find out what keywords they are they using to find it? Let’s add a table that will allow us to see more than 10 results by using the table icon in the toolbar. 

 

 

Let’s remove the ‘not provided’ and ‘not set’ results that clutter our nice table by using a filter and widen the time range to one month in order to get more significant results. 

 

 

Now it make sense that returning visitors that already know about our project type Code For Life-related keywords to find us again. Next, we’d like to understand which keywords new visitors use.

 

 

If we switch to view mode, we can actually browse through all the results.

 

 

So the first “generic” keyword used to find our website is the 32nd. It means that most users type something related to the Code For Life project or our first game Rapid Router to find the website. The number of keywords here is not really significant because Google Search now encrypts all search queries. But this actually confirms what user interviews had already suggested; that Code For Life is mostly marketed through word of mouth.

Now let’s go back to Edit mode, and add a table that tells us the list of referral websites visitors use to find us – the online equivalent of word of mouth.

We copy the previous table, and add a filter to remove direct and search engine traffic types:

 

 

That’s awesome! These results suggest that if we want more traffic, one way would be to make sure we get included in more websites like the ones above, but also that we make sure people find us by typing the right keywords in search engines, like “Coding resources for schools” for example. 

What does our backlog say about prioritising outreach and community related user stories?

Google Data Studio allows us to add different data sources, which is awesome. To be fair, we haven’t found a way to safely get data from our database, as currently Cloud SQL can only be added as a data source without SSL protection, which we don’t allow for good reasons. But it’s important to remember Data Studio is still in beta and already very promising.

Our backlog is in a Google Spreadsheet, that we can safely add as a data source to Data Studio. The goal is to create a very basic product graph, showing us user stories prioritised by Cost To Delay and Strategy.

 

 

Of course, some of the metrics don’t fit yet, but we can change it as we can create new metrics, aggregate some others, etc.

 

 

Here, we easily transform our t-shirt sizes Costs of Delay into numbers. We do the same with Strategy:

 

 

Now, let’s say the aggregates for these new metrics are average (and not cumulated):

 

 

If we add a filter to only see the stories concerning outreach and community, we get the following results:

 

 

And the final graph looks like this:

 

 

Of course, this is just an example of how you can use Google Data Studio to quickly and efficiently create human-readable and shareable data boards.

Happy data analysis!

Celine Boudier, Code for Life Team Leader

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