I analysed around 2,000 cases involving regular players at one casino brand over 12 months, looking at who stopped depositing the following month.
The average churn rate was 47%. Here's what I found:
- Payment declined: 30% churn
- Withdrawal delayed by a technical error: 34%
- Withdrew more than they deposited: 58%
- Cut deposits by half: 64%
- Asked to submit the same documents twice: 69%
Surprisingly, technical failures had the lowest churn rates. A player whose payment fails is still trying to deposit. They're frustrated, but they're still engaged.
What really hurts retention is repeated bureaucracy and the gradual decline in spending.
But the strongest signal wasn't a failed payment, a withdrawal or a KYC issue. It was silence.
- A daily player disappears for a couple of days: 4% churn
- A player who visits twice a month goes silent for a week: 79% churn
I even tested a more complex predictive model using all available data. It performed worse than one simple metric: days since the player's last visit.
We spend so much time fixing things that break because they're visible. Meanwhile, we're losing players who quietly stop showing up.
Three things I'd prioritise
- Track unusual inactivity relative to each player's normal behaviour, not just absolute days offline.
- Have a real person handle repeated KYC requests instead of sending another automated message.
- Stop treating every technical failure as a retention emergency.
Sometimes the biggest churn signal isn't a complaint. It's the absence of one.