◾Churn prediction

The Churn Prediction model is a dynamic tool explicitly created for casino 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 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 within 30 days. Based on the custom needs of the clients, Smartico can train models for different no-deposit periods or different definitions (e.g., no deposits and no gameplay)

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 probabilty 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 for 30 days

You can find the current distribution of the players by rank in the "Churn risk ranks" report.

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

For example, a probability of 94.3% for Critical rank indicates that out of 100 players, 94 players will churn.

Distribution of players by ranks

The "30-day net-deposit projections" show the monetary value of the net-deposit for the next 30 days 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.

Using churn ranks in the CRM campaigns.

The churn rank of the player is updated by a special event."Core: churn prediction updated.".

This event is sent when a player migrates between the ranks, for example, from Low to High.

Using this event, the Operator can build a real-time campaign when the user enters the rank requiring retention action.

Campaign that triggered by entering into Critical or High ranks

It also can be used inside the campaign to stop marketing insensitivity when the user rank is going to low-risk ranks.

Stopping campaign when user is evaluated as Low or Medium risk.

Churn risk can also create a segment of users that can later be used in the Campaign, Automation rules, Missions, Mini-games, and Tournaments.

For example, you can target specific mini-games only to the users with a high probability of churn or expose them to specific missions from the Gamification area.

Analyzing the model performance

There are three reports available for the churn model.

Churn risk ranks

Showing the current distribution of players by risk rank and the historical size of each risk group of players.

Users vs. Ranks

Reporting shows the history of user migration between the ranks.

Actual churn report

This report shows the actual churn rate of players, players who did FTD and reactivated players.