▪️Churn & LTV prediction

The Churn Prediction model is a dynamic tool explicitly created for casino & sport operators to identify and categorize players based on their risk of discontinuing play.

This tool is particularly focused on predicting the likelihood of players not depositing and not betting (absence of the both events) within the next 30 days. The model assigns each player a churn probability score daily. This scoring system is integral to categorizing players into risk groups, thereby providing the possibility to enhance player retention.

Churn definition

In the context of this model, a player is considered to have churned if he has not deposited AND not played (any bet) within the fixed 30 day period.

Churn scoring and player ranking.

During the evaluation, the mode assigns a risk score for each player with values between 0 and 1. Where 0 is the lowest probability of churn and 1 is the highest.

All players are assigned to one of 6 churn ranks for a more straightforward interpretation.

Rank name	Explanation
Not set	Player didn't have any deposit yet
Low	Low probability of chrun, no action required. Risk value 0-0.4
Medium	Medium probability of churn, no action required. Risk value 0.4-0.6
High	There is a high probability of churn; action is recommended. Risk value 0.6-0.85
Critical	Risk 0.85-1, action is highly recommended.
Churned	Player is churned by definition. Didn't deposit AND bet for 30 days

Churn risk ranks" report - daily, for the last 30 days.

You can find the distribution in dynamics of the players by rank in the "Churn risk ranks" report - daily, for the last 30 days.

Go to Reports -> Extended Reports -> Users’ Segments by Churn Risk)

Churn Metrics Snapshot

Another report for the current day snapshot with metrics is "Churn Metrics Snapshot"

Go to Reports -> Extended Reports -> Churn Metrics Snapshot

This report shows the number of players for each rank and the "Probability to churn" for this rank, calculated based on historical predictions.

Example: A probability of 99% for Critical rank indicates that out of 100 players predicted historically for this rank, 99 players have churned.

The "30-day net-deposit projections" show the monetary value of the net-deposit for the next 30 days (average, based on user's history) if these players continue to be active.

To see the "Probability of churn" metric, the model should be active for at least 30-day period so the model can compare its evaluation with actual churn data and calculate this metric.