Compare each customer with their usual pattern
Bring the relevant signals into view.
CHURN PREDICTION
Know who’s pulling away. Before they disappear.
Make widening visit gaps and changing habits visible, so you know who to check in with.
Explore the proposed workflow with Sample data.
Customer signalUseful next action
Compare each customer with their usual pattern
Choose a thoughtful win-back message
Product concept · sample journeyTHE PROBLEM
A missing regular rarely announces it.
When visit records and conversations sit apart, it takes manual work to choose a relevant next step. Start with the customer’s context.
Understand the signals behind their risk
Review the timing and permission behind the action.
Choose a thoughtful win-back message
Keep the resulting visit and costs visible.
Try a little of churn prediction.
Compare each customer with their usual pattern. Explore this preview, then open the complete workflow.
Open full demoAisha’s visit gap is widening
Review the customer’s own baseline. A signal suggests a check-in; it does not prove they will leave.
A CLEARER WORKFLOW
From manual checks to a connected journey.
| Job | Without a connected workflow | With the Reten concept |
|---|---|---|
| Understand the context | Review separate customer records | Compare each customer with their usual pattern |
| Choose a next step | Rebuild the timing and audience manually | Understand the signals behind their risk |
| Review the outcome | Reconcile replies and visit records | Choose a thoughtful win-back message |
WHERE IT FITS
Part of the whole customer story.
Proposed stages · sample journey
At-risk
Notice the break in routine
A sample 21-day visit gap, longer than this customer’s usual pattern.
See it runSample WhatsApp message
Hey Aisha, it’s been a little while ☕ Your favourite iced latte misses you. Drop by for a treat this week?
Reply STOP to opt out.What to measure
Eligible customers returning
WORKS WITH YOUR SIGNALS
Start with the records you have.
No live connectors are confirmed yet. Explore the proposed data sources and confirm availability before setup.
MEASURE WHAT MATTERS
From a message to a recorded return.
Define the eligible audience, return window and qualifying bill. Track replies, visits and offer costs separately. Attributed revenue is a useful signal; a comparison group helps assess additional impact.
How to measure recoveryBetter together.
WhatsApp AI
Explore how customers and owners could get answers in WhatsApp, with a scripted preview.
Live Insights
Explore recency, frequency, spend and repeat-visit patterns in one clear view.
Loyalty
Preview a loyalty card that connects earned rewards with the customer’s next visit.
A closer look at churn prediction.
What can I try in Churn Prediction today?
The interactive preview lets you compare each customer with their usual pattern using Sample data. It runs in your browser and does not connect to your business or send messages.
What information does Churn Prediction need?
Customer identifiers, permitted contact details and the relevant visit, bill or feedback history. Available sources must be confirmed during setup.
Can I control the next action?
The proposed workflow includes owner review, frequency limits and opt-out handling. Explore these controls in the demo; live availability needs confirmation.
How will I know it helped?
Compare eligible customers, messages, qualifying return visits and associated bills within a defined time window. Attributed revenue alone does not establish incremental impact.
YOUR NEXT CHAPTER
Your regulars are worth
coming back for.
See what a thoughtful next message can do.