Cool Tool: Decomposition Tree for Ad Monetization (PART 2)

Published by Digital Limbo on

In collaboration with Rubén Barrena Crespo

We talked about the theory behind the decomposition tree, let’s now move on and see how it can be used to analyze your ad monetization data and get conclusions out of it.

Here the link to download the excel file.

To update the document, you just need to paste your own data in the Sheet “Data” tabulated in the order: Date, Metric, Platform and Value. If the name of the metric has a different name in your Analytic tool, it should be changed also in the Column A of the Sheet “Tool”.

Once the data is loaded, the periods to be analyzed should be updated in the Sheet “Tool”, setting the start and end date for Current and Control periods. Current period would be the period to be analyzed and the Control Period is the one compared with the Current. It could be Week over Week, Month over Month or even different periods of time, like current month over last six months. Since the tool is based on Daily Average, the period duration would not be affected.

Finally, once  the platform to be analyzed is chosen in the cell H5, all data will be updated according to that platform.

Now it is time to understand the data and take conclusions.

For example, in this scenario, the increase of +15% of Revenues on iOS is mainly due to the increase of Impressions more than the increase of eCPM (+11,4% Vs +3,2%). This increase is explained because of the increase of people watching VideoAds (Engagement +16,4%) that have been able to counter the drop of Active Users.

On Android, we can see how Revenues decreased (-6,3%) despite the increase in eCPM by +1,0%, which couldn’t compensate the drop in Impressions (-7,1%) which, in its turn, is mainly explained by the decrease of VideAds Watchers (-5,4%) caused by an important drop in Active Users (-3,8%). As an additional factor, there is also a decrease in Engagement (-1,7%) and Frequency (-1,8%). The drop in Frequency mainly explains the increase of eCPM (0,8% over +1%).


Additionally, decomposing the changes by the impact of each single metric, in the following graphs it is seen clearly how the main KPIs affected the variation in Revenues:

  • iOS: between the two periods, Revenues increased +$1.500, where Engagement is the main increase factor (+1.578), followed by far by an eCPM increase (+$359). Thanks to both KPIs, the negative effects of DAU (-$400) and Frequency (-$37) have been compensated.

  • Android: between the two periods, Revenues decreased (-$500), where Active Users is the main decrease factor (-$300), followed with similar impact by Frequency (-$139) and Engagement (-$132).

Now it’s time for you to download the excel file and play around with the decomposition tree to have some insights on your ad monetization!

Rubén has been working in the Strategy Department at Social Point for 3 years and now is working as a Freelance Consultant. With a combination of product, market and customer understanding, he is able to provide meaningful insights to companies and set up the next steps in strategic topics.

1 Comment

David Nguyen · August 13, 2020 at 19:27

Hi Ruben,

Such a great post! Thank you a lot for this.

May I ask how do we apply this for other ad formats (interstitial, and banner)?


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