Maximize LTV
in mobile games
Incymo improves the LTV (lifetime value) of players
by personalising in-game offers. Our customers are mobile
games that have a wide variety of offers at varying prices.
About us
Hi!

We are incymo, an ML-based company that studies the behavior of mobile game users by identifying their current needs in order to personalize offers to buy game currency or any in-app purchases. This is how we help game owners and publishers grow their LTV and earn more.

Our mission is to empower players to enjoy their games more and help game owners earn more money to create cool new games.

We strive for easy integration with games so as not to waste a lot of the developers’ time. By taking a deep dive into the project, we are able to ask many questions in order to offer only  the best solutions.
HOW WE WORK
Stage 1
We find out the client's needs, study the players' behavioral patterns and generate audience insights for subsequent application with personalised offers and increased LTV. Please see some insights exmples below.
Stage 2
After conducting analytics in step 1, we move on to integration and testing. Through the API we pass recommendations with the description of the offer to the client for each user as part of the A/B tests, training our AI and perfecting the result to the specified values.
!
We only work with anonymized data that holds no value outside the perimeter of the particular game. We do not need to know who your users are; we are only interested in their behavior.
Starting to work
Game Data Access
Users’ behavior and game events
Data analysis
Studying player patterns
Generating insights
When, to whom and in what form to pass the offer
Client decision
Decision to integrate incymo.ai
Setting up API
Setting up event submission
Creating offers
Identifying possible offers
Personalised model
Choosing an offer for the player
A/B tests
Running model-based tests
Comparing control and test groups
Finding out that the group with offers from Incymo has higher LTV
Insights examples
example 1
Showing an expensive offer to players at an early stage of the game (up to level X) increases the probability of churn by Y% (Y large)
example 2
Let us consider a segment of users who play slower than other players but spend a total of more than three hours in the game. In this case, the expectation of revenue from showing an expensive offer is X% higher than that from showing a cheaper one
example 3
If users complete the first X levels of the game in Y hours or less, their LTV will be Z% higher than the average, provided the expensive offers were shown (despite the current logic of offer showing)
Why choose us
The client pays for the result only.
If LTV increased 3% or more we charge a one-time fixed price for each new user who went through incymo.ai recommendations.
In a rare scenario we do not meet our 3% LTV increase goal you do not have to pay us!
Contacts
We will happily share our expertise and answer your questions.