How to measure and optimize ad revenue once you cannot afford specialised tools. How to use BigQuery, Firebase to make better decisions. Presentation delivered by Przemek Modrzewski from Google and Adam Tyszer from Huuuge Games

1. Ad LTV measurement - Proof of Concept
Przemysław Modrzewski, Analytics & Measurement Principal Lead
Adam Tyszer, Head of Performance Marketing Business Intelligence
March 2019
1
5th GameCamp

2. Purpose of the project
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• Enable companies to calculate LTV for ad based
games
• Use only free tools
• Rely on Google’s products, which deliver best in class
value and performance
○ Google Firebase
○ Google Big Query
○ Google Data Studio

3. Agenda
Adam Tyszer | Przemysław Modrzewski 3
• Introduction to calculation of LTV for ad based games
• Challenges in calculating advertising LTV
• Presentation of a proof of concept
• Q&A session

4. LTV (Lifetime Value)
4
Metric, which takes into account all future cash
flows from an individual user
Adam Tyszer | Przemysław Modrzewski

5. LTV (Lifetime Value)
5
Metric, which takes into account all future cash
flows from an individual user
More than metric
1. LTV is not only historical data analysis, but rather valuation of the future revenue
2. LTV in marketing is predictive
3. The are many ways to calculate LTV
Adam Tyszer | Przemysław Modrzewski

6. LTV (Lifetime Value)
6Adam Tyszer | Przemysław Modrzewski

7. The main goal of marketing today
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● Acquire users not based on present value but future value
● Being able to act during lifecycle of users
● Change focus from buying installs to buying valuable
users
Adam Tyszer | Przemysław Modrzewski

8. ● Non cohorted data does not make it possible to calculate LTV
● Appfigures does not provide cohorted revenue data so we need a workaround....
Challenges of calculating LTV for ad based games
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Non cohorted Cohorted
Adam Tyszer | Przemysław Modrzewski

9. Challenges of calculating LTV for ad based games
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● Players do not (generally) make payments and agree to have their play
interrupted by ads
● Revenue is based on the number of ad impressions and ECPM (Effective Cost per
Mille)
● However the data from AdMob (number of impressions and ECPM) is not
cohorted
○ We have a sum of revenue for a day, source, geo, etc.
○ But do not know if this revenue is form users acquired today, yesterday or a
week ago
○ This makes it impossible to properly assess performance of a particular
cohort
Adam Tyszer | Przemysław Modrzewski

10. Challenges of calculating LTV for ad based games
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● We calculate ECPM based on revenue and impressions from
AdMob
● The calculated ECPM is then used for calculation of cohorted
revenue
● In order to do that we need number of ad impressions per users
○ Acquired on a particular day
○ Per each day as they progress
Adam Tyszer | Przemysław Modrzewski

11. Proof of concept - visualization
11Adam Tyszer | Przemysław Modrzewski

12. Proof of concept - metrics
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Impressions
Acquisition
Costs
Revenue per
impression (RPM)
native connector

13. 1. Step - Firebase data
13Adam Tyszer | Przemysław Modrzewski

14. 2 Step Transfer media data
14Adam Tyszer | Przemysław Modrzewski

15. 3 Step - AdMob data
15Adam Tyszer | Przemysław Modrzewski

16. 16
Join tables in Big Query

17. Some details of SQL methodology
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Impressions by unique IDDate Install Source
Cost
CPM
Install Date Install Source
Geo
Geo
Geo
Impression Date
Adam Tyszer | Przemysław Modrzewski

18. Outcome dashboard (first step to LTV methodology)
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Important metrics:
1. ROI for important date ranges
2. AARPU in estimated break
even pont
3. Effective CPI (cost per Install)
Adam Tyszer | Przemysław Modrzewski

19. Outcome dashboard (first step to LTV methodology)
19Adam Tyszer | Przemysław Modrzewski

20. Visualization by GEO
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21. What if we “under the surface” ?
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Profits
LTV
Costs
Acquisition
Retention
Upselling
Adam Tyszer | Przemysław Modrzewski

22. LTV (Lifetime Value)
22
Metric, which takes into account all future cash
flows from a cohorts of customers
More than metric
1. LTV is not only historical data analysis, but rather valuation of the future
2. LTV in marketing is predictive
3. The are many ways to calculate LTV
Adam Tyszer | Przemysław Modrzewski

23. Important facts to consider
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1. Paid traffic very often monetizes in different sources
(attribution)
2. Paid traffic influences visibility
3. We can act during lifecycle of users (events analysis)
4. We should test business models and acquisition sources and
media (obviously ;-) )
Adam Tyszer | Przemysław Modrzewski

24. Special thanks!
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Grzegorz Balcerzak
www.lightpixel.io

25. Thank you
25