One size does not fit all!

As a mobile game studio,
you know that your financial success
depends on player retention (CPI<LTV),

( whatever monetization model you use:
ads, InAppPurchases or Subscriptions).

But player retention
depends heavily on difficulty tuning,
which is complicated and tedious:
analytic tools are complex to setup and use,
and they let tune blindfolded!

Too difficult ? A frustrated player will churn
Too easy ? A bored player will churn

And once you reach a good balance,
retention hits a ceiling:
mobile players are very diverse,
one size does not fit all!

You lose players that could stay in your game
if the difficulty was sometimes easier or harder for them.

Introducing

Plug&Play Real-Time Personalization Platform
to increase Retention in mobile games

Data-Driven Difficulty Analysis
Simplify and Optimize your Difficulty Balancing

For each stage in your game,
askblu.ai helps you find the optimum difficulty
for your overall audience of players

 

 

Real-Time Player Personalization
Break the Retention Ceiling - Increase your Revenue

For each player starting a stage,
askblu.ai tells your game in real time
if you need to set the difficulty easier or harder
to keep the player in his/her flow zone.

 

All of this available with one simple SDK,
no guessing in data selection,
ready to be used by games designers,
in a full SaaS ML-Ops platform !

Easy to setup SDK,
with NO IDFA.

"Plug&play" solution,
no web portal setup.

Real players,
and your players only.

One goal: increase
retention and revenue

A/B metrics with
and without askblu.ai

Machine Learning
with no investment!

Get Usage Credits today to test askblu.ai for free!

We are looking for innovative mobile game studios interested in providing a personalized experience to their players.
SIGN UP (top menu)  for a FREE early access to askblu.ai and you will have the opportunity to help us shape this new innovative solution.

Proud to be among the 6 finalists for the Best Innovation Award for the Pocket Gamer Mobile Games Awards 2020 in January 2020, London.