Behavioral analytics for game industry
Every game producer wishes to cover the biggest amount of users to play it constantly.
Unfortunately, there is a huge competition in this very mature market.
And only "superpower" would be helpful for analyzing everything at a speed of flash and changing everything simultaneously. This power could save your exponential growth.
Our product could become such the ability for you!
What task was resolved?
Users segmentation in the game on the base of their behavior. The main target was to present more personalized game experience and more targeted purchases or payable services within the App.
Challenges:
Companies used already many other analytical instruments. Still, they have a lack of crucial information for getting useful. Also, the existing one instruments doesn`t provide understandable analytics as a picture of the game from the point of view of players.
This raw data of such analytical platforms push owners of a game to hire his own analytical department to make interpretation of data.
That`s why that was so important to bring the difference of our platform.
How all of that was done:
We gathered a huge quantity of metrics about users actions (like installations, purchases, clicks, level ups, achievements, user paths etc.). Our system gathered all that unstructured data by specific API.
Based on that brain of our platform could make segmentation of data according to users behavior.
For instance, we make clusters of users according to their manner in the game: active attitude/ inactive, quiet/ stormy, addicted to purchases/non-buyer etc.
Thanks to this segmentation a game company now know about the types of triggers that could push the player to stay longer in the game. So "Retention" and "LTV" could rise drastically.
Results:
Our platform provides a final analytics as a decision or recommendation, but not in a way of a raw data only (as a market proposes now).
What task was resolved?
Reviews of a game are very important for the game.
Still, that being a challenge to track all of them through the Internet.
Also, that is being in multi times harder to track reviews for your game and competitors games at the same time.
Challenges:
Sometimes even the name of the brand/company could become the source of a review. So brand awareness over the Net is also the thing that must be traced.
How all of that was done:
We make a parsing for specific websites and specific phrases. The administrator typed all the needed information once. Then our system goes regularly through of each web-site according to these rules.
Each review indicated with an emotional tone.
Results:
Good news for game business - you can now to feel the pulse of your game and immediately react on users complaints or even detect bugs in order to correct them quickly and increase user loyalty to your game. Thus, you can reduce churn rate.
