GAMWIT's Player Frequency model tells you how many days a player will be active next week, so a promotional calendar becomes a schedule instead of a guess.
Player Predicted next visit
Example rows, not live data shape as in the GAMWIT platform
Why frequency matters
How often a player logs in is one of the clearest signs of retention. GAMWIT's Player Frequency model predicts when each player will return, so campaigns go out on the right day, not a fixed schedule.
See what your team getsTurn into discounts nobody needed.
Often the first sign a player is drifting away.
Need different timing.
A real screen from a licensed GAMWIT account, on sample data. Every player on the base is scored.
Every player, scored
Customer id, the return band the model predicts, 0 days, 1 to 4 days or 5 to 7 days, and the recent activity behind it. Exportable, or delivered into the CRM.
982 players scored. Sample data.
These are sample players. In a walkthrough, we run the Player Frequency model on yours.
Book a walkthroughWhat changes
Same calendar, same budget. Campaigns go out on the days each player is likely to be back.
Campaign timing
Without GAMWITA fixed promotional calendar, sent when the schedule says so.
With GAMWITCampaigns land when a player is about to return.
Who you target
Without GAMWITThe whole base, or whoever spent most last month.
With GAMWITThe players predicted to be active that week, so budget goes where players are.
Engagement dips
Without GAMWITNoticed in the monthly report, weeks after the drop.
With GAMWITFlagged the week the drop is predicted, to the team that can act.
Planning
Without GAMWITTraffic spikes are a surprise. Servers and staff are set for the worst case.
With GAMWITDemand is predicted a week ahead, so servers and staffing are planned against it.
How it works
Why frequency is hard to predict
Habits change
Some players return daily, some now and then, and what brings them back changes with interest, in-game experience and friends. Holidays and big releases change it again.
The data has gaps
Players move between devices, hold multiple accounts, and hit connectivity problems. New games have no history to learn from, and processing all of it in real time is its own problem.
There is a line to respect
Prediction should improve the experience, not push players to play more than they want, and privacy rules limit what can be collected.
Fixed rules cannot keep up with changing habits. The Player Frequency model learns from behavior and game interaction, and it does so without personally identifiable information.
GAMWIT watches activity continuously and tells your team when engagement looks like it is about to drop, while a push or an in-game reward still works.
A regular who is predicted to drop from 5 to 7 days to 1 to 4 is flagged before the habit is gone.
In practice
Examples from GAMWIT's use-case guide. They show how the model is used, not a customer's results.
The declining regular
The situation
A player who usually plays 5 to 7 days a week is predicted to play only 1 to 4 next week.
What GAMWIT does
GAMWIT flags the drop before it becomes churn risk. A reload bonus or loyalty multiplier goes out while the habit is still there to reinforce.
The at-risk week
The situation
GAMWIT predicts 0 active days in the coming week for a player who was active last week.
What GAMWIT does
A reactivation offer fires now, with a time limit, rather than after the inactivity has stretched to a month.
Preventing fade-out
The situation
A daily player has shifted to weekly play.
What GAMWIT does
GAMWIT reads the trend. A daily login challenge is triggered to re-establish the daily habit.
How to use the results
Quick winSegment players every week into the three activity bands, and run reactivation, nudge and upsell from those lists.
Try it yourself
Sign up and build your first model yourself, no setup call needed. Prefer a guided tour? Book a walkthrough instead.
Getting started
The Player Frequency model at a glance
What it asks of your team
Marketing, Finance, Risk and Compliance teams use it directly, without an analytics background.
Wherever and however your gaming data is stored, the GAMWIT team handles the connection. See how GAMWIT connects
Once connected, the model runs on its own and delivers fresh predictions on every run.
FinalistCompliance Innovator of the YearVixio · 2024
NominatedCompliance Technology ProviderEGR North America · 2024
NominatedData and AI PartnerEGR B2B · 2022 · 2023The Player Frequency model is already built. Connecting your data takes 2 to 4 weeks.
