Forecasts and scenarios
Player retention that acts on the prediction
Most retention runs on manual lists and one offer for everyone. Sellrise scores every player, flags who is leaving before they are gone, and tells your team who to contact today, with which offer and through which channel.
The demo opens right away: name, email and a password, no call. Inside: today's player queue on demo data.
The problem
A retention manager rebuilds the same lists by hand, the analyst re-exports the same report, and by the time a valuable player is flagged they have already stopped depositing. One offer per cohort means a high-value player and a random one get the exact same message.
What you get
- A list for today: who needs attention and what to offer each of them
- Churn risk per player, so you reach the leaver before they are gone
- Time and channel for each contact, your team decides and sends
- The bonus picked for the player, not one bonus for everyone
Questions operators ask
Do we replace our current retention tool?
No. Sellrise works alongside your platform and CRM, your scenarios stay where they are. Nothing to migrate.
How is the effect measured?
On your own players: a control group, your team as it works today, and your team with Sellrise. The metric is average turnover per player over one month.
What data do you need?
Four tables by Player ID: players, deposits, bets, sessions. Contacts are optional, only if messages and calls go through Sellrise.
Other use cases
- Traffic quality
Know which traffic source pays back, before the hold clears
See this use case - Call analytics
Every call scored, not four in a hundred
See this use case - Forecasts
Analytics that works where a player is worth a few dollars
See this use case - Bonus matching
The right offer for each player, at the right time
See this use case - Forecasts
Spot VIPs early, skip the ones who won't pay back
See this use case
Let us prove it on your numbers
Send your numbers and get a quote for your market plus a plan to prove it on your own players.