How to turn Analytics data into actionable information 2: segmentation by time and device

Digital marketing is becoming ever more complex; according to the Think with Google multi-screen research

“Today 90% of our media consumption occurs in front of a screen. As consumers balance their time between smartphones, tablets, PCs and televisions, they are learning to use these devices together to achieve their goals. This multi-screen behavior is quickly becoming the norm, and understanding it has become an imperative for businesses.”

We have all the data on earth...

Everyone with at least intermediate knowledge about Analytics and AdWords knows that Google provides almost all the data necessary to be successful in this multi-screen world thanks to Enhanced campaigns. This provides the opportunity to target and bid by device and time segmentation. We also have Analytics report segmentation options for checking the effects and results of our strategy. What’s the issue, then?

The problem is the abundance of options; it is really hard to find the right actionable information among this mass of data. Below I will present a few easy-to-understand Analytics and reporting tips helping you finding order in disorder, or the needle in the haystack if you wish.

How to start?

Let's kick off with a simple insight to determine the best performing days of the week and how to set our AdWords bidding strategy to incorporate this piece of information in order to optimize our campaign? To do so let us look at the graph below where the horizontal axis shows the days since last visit data and the vertical axis shows the conversion rate data.


We can immediate deduct obvious and actionable information that can be used in our AdWords strategy:

Segmentation by device and dayparts

Ok now we know which days of the week work best but we have more sophisticated bidding options in AdWords and have much deeper data in Analytics, so let’s try to come up with insights about performance throughout the day:



We defined 4 dayparts to understand the conversion performance: morning, working hours, evening and night. If you look at only the first chart, you will see that evening hours have the most impressive conversion rate, working hours are second and the remaining 2 dayparts do not seem too interesting... On the other hand if one looks at the second chart showing the total share of conversions by number a quite different conclusion emerges. This is a good example how never to judge by one metric only. A single metric without context is always misleading and usually not actionable! It is clear in this example that even though almost 40% of all conversions occur during working hours the other 3 dayparts are resulting in the same amount of conversions and conversion rate.

Dig deeper!

Although these charts are very informative and help us understand the context, they don’t really translate into concrete optimization steps. At this point we are a bit confused and not too sure what to do with our bidding strategy.

To solve the puzzle we have to go even deeper and segment the performance by hour and by device. First we look at desktop visitors from the AdWords campaign and easily identify the top conversion peaks, uplifting trends and worst performing periods, which serve as a perfect input for our enhanced campaign optimization!






Then we do the same for mobile and tablet visitors and a completely different pattern of conversion distribution emerges:



Based upon this info we can schedule our mobile and table AdWords bids optimally.



Conclusion and tips: increase budget and bids during conversion peaks and decrease for low performing periods - especially if your budget is limited and able to get only a small percentage of available impressions.

In the following posts we will continue with more segmentation and analysis tips. Stay tuned!

Loganis was used for data extraction and charting in the examples above. Loganis is a free system that enables one to extract data from Google Analytics and Facebook and share the resulting charts with colleagues and clients. Loganis also allows one to download the data to Excel real-time; an example is shown in a previous post in this blog.

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