HOW TO PREDICT AD REVENUE ROAS
(SO EASILY, YOUR GRANDMA CAN DO IT)
WEDNESDAY, NOVEMBER 23rd │16:00 CET
In this exclusive webinar, we’ll demonstrate and explain the entire process behind creating ROAS prediction models for Ad-Monetized Games.
We’ll cover what data is needed, how to turn this data into insights that are useful for predictions, how to practically create calculations and charts in Google Sheets, and how to use the model to understand the game’s monetization potential.
Our focus will be on the practical learnings and outcomes to help you replicate the process for your own game.
QUESTIONS WE'LL BE ANSWERING:
- What data do I need to predict the ROAS for ad-monetized games? And how do I access this data?
- How can I perform an initial analysis to understand the data and its predictive potential?
- How can I create a ROAS predictive model based on retention and ARPDAU?
- How can I build a predictive model myself using Google Sheets or Excel?
- To be a better professional, what outputs can I leverage from a ROAS predictive model?
- Which learnings from AppAgent’s day-to-day usage of the model can help me level up my marketing efforts and improve my ROAS?
Head of Marketing at AppAgent
A founding member of AppAgent, with a focus on data and business strategy. Oversees excellent delivery on tier-1 publishers such as Babbel, Kiwi.com and Glu Mobile.
Mobile Marketing Lead at
Growth consultant for apps and games with 15 years of professional experience and 9 years in the field of mobile marketing. Has worked on Dreamloft, Bosch, Brainly, PhotoRoom and other top mobile businesses.
The team at AppAgent immediately understood how they could work with us to alleviate pressure points and drive growth. AppAgent’s campaign management and bespoke LTV model are now central to our User Acquisition process.
Craig Forret / Co-Founder at dreamloft
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