[ AI churn prediction ]
See Which Customers Are Drifting Away While There Is Still Time
We build churn models on your product usage, billing and support data, score every account, explain why it is at risk and put the right retention step in front of your team.
- Risk scores for every account
- Weekly
- Risk scores for every account
- Reasons shown behind each score
- Top 5
- Reasons shown behind each score
- Alerts where your team already works
- In your CRM
- Alerts where your team already works
Churn risk this week
Example, week 4
- Northwind LabsGrowth plan79
- Logins down 46%
- 2 open tickets
- Champion left
- Kestrel FoodsStarter plan58
- BrightpathScale plan35
- Atlas ClinicsScale plan19
Sample accounts. Scores are 0 to 100 risk.
Why Churn Surprises Most Teams
By the time a cancellation request arrives, the decision was made weeks earlier.
- 01
Signals sit in different tools
Usage lives in analytics, billing in Stripe and complaints in the help desk, so nobody sees the full picture.
- 02
Health scores are guesses
Hand-weighted scores look tidy but rarely predict who actually leaves.
- 03
Success teams spread thin
Without a ranked list, managers spend time on accounts that were never at risk.
- 04
No feedback loop
Teams cannot tell which retention plays worked, so the same mistakes repeat.
How We Build Your Churn Model
We prove the model on your past churners first, then connect it to the people who act on it.
- 1
Define churn
We agree what counts as churn for your business: cancellation, downgrade, lapse or falling usage.
Churn definition and labels
- 2
Feature build
Usage, billing, support and account data become weekly features per customer.
Feature pipeline
- 3
Backtest
The model predicts past churn without seeing the outcome, so you see how early and how accurately it would have warned you.
Lift and lead time report
- 4
Activate
Scores, reasons and suggested plays are pushed to your CRM or success tool, with tracking on what happens next.
Live scores and playbooks
What the System Does
Scores your team can trust and act on, not a dashboard nobody opens.
- 01
Behavioral signals
Logins, feature adoption, seat changes and usage trends, tracked week by week.
- 02
Explained risk
Each score lists the drivers behind it, such as falling usage or unresolved tickets.
- 03
Suggested plays
Recommended actions per risk type: a check-in, training, a discount or an executive call.
- 04
Cohort views
Churn risk by plan, region, acquisition channel or onboarding path.
- 05
Revenue at risk
Risk weighted by contract value so the biggest exposures come first.
- 06
Outcome tracking
Saved and lost accounts feed back into the model and the playbooks.
What We Measure With You
Targets are set during the backtest; results depend on your data and how your team acts on the alerts.
- 01
- Lead time
- Weeks of warning before a churn event
- 02
- Precision at top
- Share of flagged accounts that would have churned
- 03
- Save rate
- Flagged accounts retained after a play
- 04
- Net revenue retention
- Movement in retention for the scored segment
Where It Fits
Churn Modeling Stack
Built on your warehouse and pushed into the tools your team uses.
- XGBoost
- LightGBM
- scikit-learn
- SHAP
Find Out How Early You Could Have Known
We backtest on customers you already lost, so you see the warning time and accuracy before anything goes live.
Book a Churn Call
Churn Prediction Cost
Indicative starting prices. Cloud compute is billed to your account.
Get a Fixed QuoteFeasibility backtest
Churn definition, features and a backtest
2 to 3 weeks
from$2,500
Production scoring
Weekly scores, reasons and CRM alerts
6 to 10 weeks
from$12,000
Retention program
Scores plus playbooks, experiments and outcome tracking
3 to 5 months
from$35,000
What Customer Teams Say
5.0Clutch
5.0GoodFirms- 5.0Google
- 4.9Upwork
I had the pleasure of working with Sajal Tech on a travel website, and it was an incredible experience from start to finish. They demonstrated professionalism, clear understanding of requirements, and excellent communication throughout.
Knowledgeable, efficient, and ahead of schedule. Will hire again.
They completed our project even when the scope changed slightly. They were cooperative when we wanted to add or modify features.
Churn Prediction Questions
A few hundred past churn events is a good start. With fewer, we start with a simpler model and segment rules, then improve as data builds up.
Yes. For annual plans we predict renewal risk several months ahead using usage and engagement trends.
In Salesforce, HubSpot, Gainsight or Slack, or in a simple dashboard. We match the tools your success team already uses.
Yes. Each score includes the top drivers, so the account owner knows what to talk about.
We can run holdout tests where some flagged accounts get the standard treatment, so you measure the real effect of each play.
Data stays in your warehouse or cloud account. We work under NDA, follow ISO 27001 practices and can mask personal fields.
Let's build your next product together
Book a free strategy call and leave with a clear plan and estimate. No commitment.
- 01Pick a time that suits you
- 0230 minutes on scope, stack, timeline and budget
- 03Fixed-price proposal, NDA on request