This guide explains how to use the At-risk top customer score from Batch AI Predict to identify your most valuable customers before they churn and act while there is still time.
Batch AI Predict's At-risk top customer score identifies, among your historically high-value customers, those whose engagement signals are decreasing. The objective is to act before a potential decrease in their spends. The output is a float between 0 and 1: 1 is for the highest risk and 0 for the lowest.
The score is recalculated on a regular basis. New customers cross the risk threshold at each recalculation, so retention actions can be triggered on a continuous basis rather than in periodic batches.
This score is designed specifically for top-value customers. It is computed across your entire database, but is most meaningful when applied to customers who have historically been among your highest spenders or most engaged profiles. It is not a generic churn score for your full base.
Most loss of momentum is invisible until it is too late. By the time a top customer has stopped purchasing or engaging, re-engagement becomes significantly harder and more expensive.
With the At-risk top customer score, you can:
Detect early degradation signals among your most valuable customers, weeks before they go fully inactive.
Trigger proactive retention actions (personalized offers, VIP communications, or relationship outreach) while the customer is still reachable.
Avoid wasting retention budget on customers who are not at risk, or on customers who are too far gone to recover.
The recommended setup. Because the score updates regularly, new at-risk customers enter the segment continuously. A trigger-based automation ensures they receive a retention message as soon as they cross the threshold, without manual intervention.
How to set it up:
Go to Orchestration > Automations in your Batch dashboard.
Create a new automation with an Attribute Change trigger:
Trigger condition: Predictive score [At-risk top customer] crosses above 0.5 (or your configured threshold)
Define your retention message: a personalized email, a push notification, or a coordinated sequence.
Add a capping rule to ensure customers are not re-entered into this automation too frequently (for example, no more than once every 30 days).
Activate the automation. From that point on, every customer who becomes at risk automatically receives the retention message.
Recommended test: Use a Control Group on your automation; exclude a random portion of at-risk customers from the retention flow and compare their behavior over 30-90 days against the customers who received the message. This gives you a clean measure of the retention uplift generated by the automation.
If you are not yet ready to implement a trigger-based automation, you can run regular manual campaigns targeting at-risk top customers.
How to set it up:
Create your campaign in Batch.
In the targeting step, apply a condition: Predictive score [At-risk top customer] ≥ 0.5 (or your configured threshold).
Optionally combine with a filter to restrict to historically high-value customers (for example, customers in the top 20% by historical revenue).
If you plan to run this campaign regularly, save the audience as a named segment (for example, [AI] Top clients at risk) so you can reuse and monitor it easily over time.
In campaign mode, customers who become at risk between two sends will not be reached until the next scheduled campaign. The trigger mode is more effective for this reason.
Industry
Example use case
Retail
VIP customers whose purchase frequency is declining: send a proactive "reserved for our best customers" push or email before they stop buying altogether
Media & Entertainment
Premium subscribers whose weekly engagement is dropping: send a curated content digest or exclusive early-access communication to re-engage them
Travel
Gold-tier travelers who have not booked in over a year: reach out with priority access to a private sale or a personalized destination suggestion
Retail (subscription)
Loyalty program members showing early signs of disengagement: trigger a renewal incentive or a loyalty milestone message before they lapse
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