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Match-3

Here you can see the example of the game analysis. Additionally we will see the reports on what you should pay attention when analyzing a game of the Match-3 genre.

Match-3 game has the following features:

The game consists of many levels, which are gradually unlocked. Unlocked levels can be completed several times. For example, if the player has access to 20 levels, after the 19th level they can go to the 5th or 10th level, and then return to the 20th level. In devtodev interface such levels are called locations.
Players have different resources, the balance of which can be changed when completing the level.
There are different bonuses / items in the game, which make it easier for the player to pass the game. These bonuses can be received for good results or bought using the in-game currency.
The in-game currency can be bought using the real money.

Event structure example

In addition to analyzing data in the main reports, you can integrate custom events to track and analyze specific user actions. You can use custom events to get an insight into how users use the application, which quests they accept, how often they interact with each other, which offers they open, and so on. You can also analyze custom event data in the Custom event report.

You can build a funnel and analyze conversion rates at each stage. For example, you send an event every time a user enters an in-game shop, clicks on an item, buys an item. Based on these events, you can build a funnel and check the conversion rate at each stage in the Conversion funnel report. Below you can find examples of events that may be useful to you.

Case example

Integration tips can be found in the integration section.

In the Game structure report we can see the current distribution by levels, income from each level and the share of paying users.

To begin with, let's see the distribution of users by levels in order to assess how many users have visited the level and at what levels the players are stuck. This will help us assess the complexity of the levels.

On the Player levels tab add these metrics to the report: Passed the level, Remaining on the level and % of remaining users.

At each of the first three levels we lose from 8.6% to 14.4% of users, most likely this is due to the fact that users were not interested in the game, not with the complexity of the level.

Now let's compare the distribution by level of two cohorts of the users who registered in the project at a different time. Let’s take users who registered a week ago and two weeks ago. We will track the dynamics of their flow by levels and predict where users who registered a week ago will be in a week.

It can be seen that users who registered two weeks ago are already distributed at all levels. Users who came in the previous week are focused on level 5. It is also clear that none of the players has reached level 10.

Now let's see monetization metrics by levels, in order to understand how much money each level bring to us. After analyzing the report, we understand the distribution of users by levels, the income that each level brings and the share of paying users:

The main income goes from level 9, this means that we should interest users who are at the entry levels. It is also clear that there is a peak in payments at level 6, most likely this is due to the fact that users see and buy a special offer.

Now we’ll build a report not in the terms of levels, but in the game locations (Locations tab). During a certain attempt to complete a level, the users may change various numerical indicators: resources, game currency, etc. The report will show the distribution of players by locations and user flow in these sections. We can track the change in any numerical parameter of the location in terms of successful or unsuccessful attempt (these can be steps, health units, boosters, etc.).