How do you find a balance between providing a positive user experience and increasing your app’s revenue?

That was the problem the Nord studio had before they came to MyTracker. Read on to find out how we helped them deal with it.

The customer

Nord developed the mobile game Hustle Castle – a medieval castle simulator with RPG elements.

  • Hustle Castle attracted 16 million players within a year after its launch and was ranked by App Annie as one of the Russian games to earn over USD 25 m.
  • It’s currently among the top 16 role-playing games in the App Store.
  • Shortly after launching, Hustle Castle became one of the globally promoted projects on Google Play.

The goal

To convert non-paying players into customers to boost revenue from in-game purchases.

There’s a direct relationship between the amount of money a player spends on their first purchase and the likelihood of them making a second one. For those who make a USD 1–4 purchase, the probability of a second one stands at 46%, increasing further as the ticket grows: USD 5–10 – 50%; USD 11–25 – 60%; USD 26–50 – 62%; USD 50+ – 70%.

Our experiment focused on improving user experience with the first purchase via custom offers, which would help convert more non-paying players into customers.

How things worked prior to Personalize

If a player hadn’t bought anything for 30 days after registration, they would receive a special offer once every two weeks, which they could accept or ignore. If they ignored it, they would receive an even better offer after 60 more days (a total of 90 days without a purchase).

A more detailed explanation of the way these offers were made is given below.

Integration of Personalize

After completing the integration with the help of our personal manager, Hustle Castle’s mobile development team enabled tracking of the four standard events used for model training in MyTracker Personalize. Then they fetched player recommendations through our Realtime API and generated special offers with their own algorithms.

If you’d like to learn more about MyTracker Personalize and how to connect it, please see our blog post.

Using the recommendation engine and split testing 

Automated A/B testing is an integral part of MyTracker Personalize. Split tests comprise several stages, and ours was no different.

Learn how to get accurate results with A/B testing from another blog post.

The hypothesis

To measure the effectiveness of the test results, we used the following hypothesis:

“Using the MyTracker Personalize recommendation engine can boost ARPU in a non-paying segment by 10–30% with personalized offers.”

We chose ARPU – average revenue per user – as our key metric, as it fit the hypothesis best.


We split all non-paying users into two groups:

  • The control group continued to receive offers based on the same logic as before:
    • If the user didn’t make a purchase within 30 days after registration, they would receive a special offer once every two weeks.
    • If the user didn’t make a purchase within 90 days after registration, they would receive an even better offer; e.g. with more in-game currency or a bigger discount.
  • The recommendation group, on the other hand, was receiving 1 out of 100 offers agreed with the studio once every two weeks. MyTracker Personalize automatically segmented users based on their gender, age, geography, device model, and other criteria and then selected the most fitting offer for each user within a subsegment. Our ML recommendation model was learning throughout the test, each time showing groups of users offers that were based on their behavior. 

For example:

  • The segment of 18–25 y.o. Android users from Russia was shown offer No. 4; after two weeks, based on the data accumulated, they were shown offer No. 37 – and so on until they made a purchase.
  • The segment of 25–35 y.o. iOS users from the USA was shown offer No. 17; after two weeks, based on the data accumulated, they were shown offer No. 6 – and so on until they made a purchase.

The results

The test lasted three months and gathered enough users to achieve statistical significance and confirm our hypothesis – Hustle Castle’s ARPU in the recommendation group grew by 23%.

Increase your mobile game’s revenue by 10–30% with personalized recommendations from MyTracker Personalize.

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