Case study: how the authors of ToysBurg improved the performance of the game

Toysburg: The Monumental Adventure is a builder from the Romanian Angry Mob Game team. The game was released exactly a year ago – in December 2014. And it started, according to App Annie, extremely unsuccessfully.

At the first stage of work on the project, the authors of ToysBurg, in conjunction with DeltaDNA specialists, found the shortcomings of the project.

The game was studied using an analytical platform. It turned out that the project had too long a tutorial: some users left the game during the learning process. In order to fix this, the Angry Mob Games team has introduced several different types of tutorial. The difficulty level varied depending on the player’s skills. If the user was guided quickly, then the tutorial ended just as quickly. If the player interrupted the session during the training, then the tutorial started from where he left off.

Then it turned out that despite the good performance of the first day, by the seventh day most users were leaving the game. To understand what’s going on, the Angry Mob Games team retested all the gameplay elements. As a result:

• gaming sessions decreased;
• the players were given a clearer definition of long-term and short-term goals.

In other words, the game was made more dynamic, and the players received motivation that forced them to return to the game again.

During the testing process, it was also possible to understand that the difficulty curve of the game is increasing too quickly. Immediately after training, players were given difficult missions, which, apparently, was one of the main reasons for the low indicators of the 7th day.

To fix this, Angry Mob Games introduced the ability to postpone too difficult tasks for later. As a result of these and the changes described above, retention rates for 7 days increased by 100%.

The final stage of the Angry Mob Games team has set up monetization. Before the work on bug fixes began, the gameplay was interrupted by hard paywalls. Using A/B testing, we managed to find the optimal ratio between IAP and motivated advertising. As a result, the players no longer faced hard paywalls. In addition, it was possible to find out exactly where it is best to reward players with hard currency, and where it is possible to do without it.

The team carried out work on the project in June – it was during this period that the project indicators improved.

A source: https://deltadna.com