Driving Smarter Decisions With Data: How Chimp.Works Harnessed The Power of Machine Learning
Founded in 2014, Chimp.Works has built their reputation on the back of a series of highly successful mobile games. They produce simple and satisfying short session games like Baseball Boy, Rush and Rider. As a company, they’re continually adapting to the changing mobile gaming landscape and improving every aspect of what they do.
The Data Gaps
To achieve his goal, Hani knew that automation was critical. Creating automated reports that acquisition and marketing managers could access on a daily basis was where they needed to be. That meant establishing dashboards that allowed the team at Chimp.Works to plan, predict and make data led decisions.
Chimp.Works relied on a combination of BigQuery and Amplitude to manage their data and analytics. Together, these tools helped them understand their player level data. However, they lacked the ability to drill down and go deeper. Critically they were missing the ability to accurately attribute which of their marketing channels was driving conversions.
And, of course, working across two analytics tools made it difficult to establish a genuine single source of truth.
As well as wanting accurate attribution data, Hani also wanted to drive even more value from the data. His aim was to take the richer data from AppsFlyer and use it as the foundation for two machine learning projects; the first focussed on optimising UA creative, the second a forecasting tool.
Smarter Creative Decisions
There’s a simple truth about all forms of advertising. Some adverts work. Some don’t. Much of that success is down to the creative execution. The marketing team at Chimp.Works wanted to understand which combination of creative elements produced the most successful adverts. Understanding the relationship between colours, characters, text and the flow of the advert would help produce more effective creatives.
Predicting The Future
Machine learning has also been applied to help Chimp.Works marketing managers make more accurate forecasts about campaigns. They have the ability to forecast the performance of campaigns over 3, 7, 14, 30, 60 and 90 days. Now, at any point in the lifecycle of a campaign, marketing managers can answer a really simple question – ‘Is this game performing as we’d predicted?’. And, of course, if the answer is no, corrections can be made in real-time.
Collaboration has been key to Hani’s success. His close work with the marketing team at Chimp.Works means he can understand what they really need. And, his engagement with a wide range of AppsFlyer stakeholders has also been critical.
Hani and his data team at Chimp.Works are constantly exploring new ways to support their marketing colleagues. That means harnessing AppsFlyers native capabilities as well as its ability to provide the trusted data for their machine learning projects. What that ultimately means is more success for Chimp.Works and a better experience for their team and their players.