Hyper-Casual games
Last updated
Last updated
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 hyper-casual genre.
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.
Description | Custom event | Parameters |
Watching videos: you can find out the levels where users are willing to watch ads in exchange for bonuses, as well as find other ways of encouraging them to watch video ads | Event name show_ad Parameters reward, number, level, type, e.g., extra_moves, 100, 10, banner | reward (string) – getting extra moves, extra spins, extra boosters, etc. number (int) – number of awards received level (int) – highest available level type(int) – ad type: rewarded, banner, interstitial |
Store opening is an event that allows you to find out at what point and at what level users enter the store. You can also use this event in funnels to see the stages where users have difficulty shopping. | Event name store_open Parameters source, level, e.g., main_menu, 17 | level (int) – highest available level source – in-game store points of entrance: the main menu, the playing field, etc. |
Tap on an item: this event can allow you to see the items players are interested in and the level where hey do it. You can also use this event in funnels to see the stages where users have difficulty shopping. | Event name goods_tap Parameters product_name, level, category, e.g., bomb, 22, boosters | product_name (string) – the name of the item that the user tapped on level (int) – highest available level category (int) – item category: boosters, coins, custom items |
Authorization: this event highlights the levels where players log in, and the methods of authorization. | Event name authorization Parameters level, method, e.g., main_menu, 10, fb | level (int) – highest available level method (string) – way of logging in: social networks, email, game center |
There are often many levels in hyper-casual games that gradually unlock. An attempt to pass the level can be both successful and unsuccessful. Moreover, it can affect on the player’s numerical indicators: currency, number of boosters, etc. Therefore, firstly we analyze the distribution of users by levels. So we will understand how many users visited the level, how many of them got stuck and at which level.
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 15,6% to 45.41% of users, most likely this is due to the fact that the user was not interested in the game and not with the complexity of the level.
Now we’ll build a report not in the terms of levels, but 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.).
Remember to apply segmentation to the reports. It is possible that users who come from different sources go through levels differently. Most likely, user payments are also differ. Segmentation can give new insights for your game.
It will also be useful to monitor the users’ flow. Go to the Churn Rate report in the Engagement section. We can take actions to reduce the users’ flow to a minimum after analyzing at what day the majority of players fall off.
Games of this genre often have short game sessions, that means we should pay attention to the frequency of sessions. The frequency of sessions can tell us about the user’s interest and the habit of using the game. We’ll go to the Sessions report. We’ll evaluate the frequency of sessions using the Number of sessions metric.
If necessary, we can also evaluate the length of sessions by selecting the Session duration metric.
