Monetization Measurement Platform

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2 Background - Ads Based Monetization Ad revenue is becoming an increasingly important piece in the monetization puzzle. At the same time, the lack of granular reports of ad revenue and ad interaction per user leads to an information gap. This report aims to study some of the important patterns in ad revenue and to identify actionable user segments as well as provide benchmarks for app companies. About The Data This study is based on information collected through the SOOMLA TRACEBACK platform. We analyzed more than 2 billion (2B) impressions across 25 different apps and more than 200 countries. The app sample consists a higher ratio of games compared to the ratio of games in the app stores. However, we noticed the same patterns regardless of app category. Executive Summary The study shows that the 80/20 rule works for ad revenue - more than 80% of the ad revenue is concentrated in a relatively small segment of users - typically less than 20%. Furthermore, in some apps the users who generates many impressions are not the ones generating the ad revenue. Specifically in rewarded video we have seen 19x difference in ecpm levels between different segments. The study further explore these 2 segments: Head segment - the top 20% of the users generating 80% of revenue - often referred to as ad whales Long tail segment - all the other users The study also shows that these segments are relatively consistent even over long periods of time. Users who were classified into the head segment in month 1 of their lifetime, contribute 67% of the revenue in the next month with ARPU that can reach 6x the average. Furthermore, we found the ecpm levels are also higher in month 2 for users who had high ecpm levels in month 1.

3 Revenue Concentration in Ad-Based Monetization The test was done by extracting all the revenue data by user. This was made possible by SOOMLA TRACEBACK technology that tracks advertising revenue on a user level basis. The chart shows the accumulation of users and revenue on a percentile basis. We compared results for various apps and report the minimal, average and maximal values in the chart below. Across all the apps that we checked. Revenue Concentration in User Deciles Accumulation Decile Contribution REVENUE 80% 60% 40% 20% 0% 1st 2nd 3rd 4th 5th 6th 7th 8th 9th 10th USER DECILES Conclusion Thought Provoking The top 20% of the users (head segment or ad whales) contributed at least 80% of the revenue. The bottom 80% (long tail segment) contributed at most 20% of the revenue. Ad revenue concentration is not reported by ad networks. Attribution models rely on averages and ignore the concentration.

4 High ecpm vs. Impression Concentration Having the revenue concentrated in a small number of users can be explained in 2 ways: These users are watching a lot of impressions The ecpm of the impressions shown to these users are much higher compared to others The chart below provides data to answer this. It maps the revenue concentration against the impression concentration. You can see the average across all apps as well as the edge cases. Revenue and Impression Concentration Max App Avg App Min App REVENUE 80% 60% 40% 20% 0% 0% 20% 40% 60% 80% IMPRESSIONS Conclusion In the average app, 20% of the users contribute 40% of the impressions and 80% of the revenue. In some apps, however, 20% of the impressions contribute over 90% of the revenue. The variation between apps is mostly related to the monetization mix of the app. Thought Provoking Mediation platforms use the average ecpm to prioritize network and ignore the ad revenue concentration.

5 ecpm in Head and Long Tail Segments To further answer the question from the previous page, we can compare the ecpm levels of the 2 segments. We are providing the comparison between the ecpm of the head segment and the long-tail segment. The chart provides 3 comparisons - the app with the minimal variance, the average variance and the app with the maximal variance between the segments. All the ecpm rates are for US impressions. ecpm in Head vs. Long Tail - US Only $40 $30 $20 Long Tail ecpm $33.16 Head ecpm $24.05 $10 $0 $2.84 $3.54 $1.31 $1.24 Min Variance Avg Max Variance Results On average, the studied apps had close to 10x difference between the ecpm of the two segments. Apps that had minimal variance had greater reliance on banners as shown in the next page. Takeaway Point The ecpm of the head segment can be as high as 19x of the long tail ecpm

6 Revenue Concentration by Ad Format The previous test showed that in some apps the head segment can produce much higher ecpms than the long-tail segment but in some apps the impact is smaller. In this test we compared the results by ad-format. Revenue Concentration by Ad Format Rewarded Video Interstitial Banner REVENUE 80% 60% 40% 20% 0% 0% 20% 40% 60% 80% IMPRESSIONS Conclusion In Banners and interstitials, the top users (the head segment) that accumulate 20% of the impressions contribute only 36.6% and 48.7% of the revenue respectively where as in rewarded video it's 82.3%. Takeaway Point Concentration exists across all formats but on banners it is driven by impression count variance while in rewarded video the variance is in the ecpm.

7 ecpm of Head vs. Long Tail by Ad Format (All Geos) We can also look at the ecpm difference between the two segments and compare that difference across ad-formats. We Indexed the results so they fit in the same scale. The ecpm of the head segment in each ad-format is the and the Long tail ecpm is given as a ratio of the head ecpm. ecpm in Head vs. Long Tail by Ad Format Long Tail ecpm Head ecpm 75% 50% 25% 0% 43.5% 27.0% 5.5% Banners Interstitial Rewarded Video Conclusion In banners, the ad-whales in the head segment have over 2x the ecpm but most of the difference is created by the volume of impressions they are generating. In Rewarded Video on the other hand, the ecpm of the head segment is 19x higher compared to the long tail segment. Thought Provoking How much more effective would a monetization strategy that takes these segments into account be.

8 Ad Revenue Concentration Summary Ad revenue concentration exists in all the apps we tested and the top 20% of users generate at least 80% of the revenue and up to 99% of the revenue. The average was 89% of the revenue. The ad revenue concentration happens regardless of geographical region If we define the top 20% of the users as head and the bottom users as long tail we can compare ecpms of these two segments - the variance can be as big as 19x in the ecpm levels In banner based monetization the main difference between the users in the head segment to the users in the long tail segments is the amount of impressions. Banner whales simply watch a lot of ads. In Rewarded Video based monetization the main difference between the segments is the ecpm levels. Rewarded Video whales monetize every impression 18 times better. Interstitial whales watch more impressions and enjoy higher ecpms. About SOOMLA TRACEBACK The data presented and gathered in this study is made possible by the unique ability of SOOMLA to trace-back ad revenue to a single impression. The platform features different reports allowing our customers to analyze the monetization of different segments and to track ad interaction patterns.

9 Consistency In Ad Revenue Segments For these segments to be actionable a key requirements is that the user behavior will be relatively consistent over time. Here are some examples: Users who viewed many impressions in a given period, will at the same in a subsequent period Users who generated high ecpm in a given period, will also have high ecpm in the following period The 2nd part of the study is answering the consistency question. The Next Month Contribution Split The first test we designed is to look at the two basic segments. The head - the top 20% of the users by ad-revenue and the long tail - the rest of the users. We selected the users into cohorts according to their first month of activity by comparing their d30 ARPU. We then looked at the revenue from these cohorts in the 2nd month of their lifetime - between days 31 and 60. In the chart below you can see what ratio of the revenue was contributed by each cohort in Month 2. Next Month Contribution of Head Segment Ratio From Total Revenue 75% 50% 25% 0% 42% 33% 22% 78.5% 67.3% 58.3% Min Avg. Max Long Tail Segment Head Segment One can notice that the head cohort kept generating most of the revenue and is consistently over performing compared to the long tail cohort. One can say "once an ad-whale, always an ad-whale".

10 Next Month ARPU Levels of the Ad-Whales We can also look at the ARPU of these top users in the next month and compare that to the overall ARPU of that app. In the chart below we compared the ARPU of the ad whales in the month after they were segmented to the average monthly ARPU of that app. Next Month ARPU of Head Segment $1 Overall ARPU Month 2 Head Segment $0.75 $0.78 $0.5 $0.25 $0 $0.41 $0.43 $0.19 $0.03 $0.17 Min Variance Avg Max Variance Conclusion We can see that the ARPU of the head users is higher than average across all apps we tested and that the next month ARPU of the ad whales could be 6x higher than average. Thought Provoking Ad-whales behave like payers and companies should focus on retaining and acquiring such high value users.

11 What About ecpm We can repeat the same exercise for ecpm. Instead of selecting the top 20% of the users by adrevenue we can look at the top 20% of the users by ecpm and than evaluate them in the following month. The results of this analysis across all apps are given in the chart below. Next Month ecpm $40 $30 Longtail ecpm Average ecpm Head ecpm $30.03 $20 $10 $8.22 $11.49 $0 Conclusion Thought Provoking The obvious conclusion is that users who have a high ecpm rate in month 1 also show higher ecpm in month 2. The head ecpm rate is nearly 3x that of the average ecpm. Segments which consistently pay high or low ecpms can benefit from differentiated waterfalls and provider selection.

12 Key Findings Ad revenue concentration happens in every app and the top 20% of the users contribute 89% of the revenue in month 1 and also 67% of the revenue in the cohort in the following month. The ecpm of the users in the head segment can be as high as 19x when compared to the ecpm the long tail segment. In apps that leverage banners, the main difference between the head segment and the long tail segment is in the amount of impressions while in apps that leverage rewarded video the main difference is the ecpm levels. The ARPU of the head segment remains high in month 2 and can be as high as 6x the overall ARPU Data Driven Monetization Brings Results Here are some of the feedback we received from customers: "I was able to grow my app faster through profitable user acquisition instead of relaying on organic traffic" "My ad revenue doubled (2x) as a result of optimizing ad placement" "I created lookalikes of my ad whales and acquired users with 97% Day-30 ROI" "My ecpm increased by 40% as I created segments and applied differentiated ad strategies" "I caught competitors that advertised in my app despite being blacklisted"