Fixed Price · 2 Weeks · You Own Everything

Know which customers will churn. 30 days before they leave.

We build a churn prediction system using your existing analytics data. In 2 weeks, you'll have a risk score for every customer and a playbook for saving them.

$4,997 · Fixed Price · 2 Weeks
Start Predicting Churn — $4,997 See what's included ↓

Your CS team gets a 30-day head start on every at-risk account. Money-back if the model can't identify at-risk patterns.

Built for B2B SaaS companies at $3M–$30M ARR

Your CS team finds out customers are leaving when the Stripe webhook fires. The decision was made 30 days ago. The signals were there 60 days ago. Nobody was watching.

Right now, you find out a customer is leaving when they cancel.

By then it's too late. The decision was made weeks ago. The signals were there — declining logins, fewer features used, support tickets with frustrated tone, team members going inactive.

But nobody connected those signals into a system that says: "This account has a 73% chance of churning in the next 30 days. Here's why. Here's what to do."

That's what we build.

Most "retention solutions" are just dashboards with red and green dots. They tell you someone left after they left. The entire industry treats churn as a reporting problem when it's a prediction problem.

TWO-WEEK DELIVERY

A working churn prediction system in 2 weeks.

WEEK 1

Behavioral Signal Analysis + Model Building

We connect to your analytics platform and CRM. We analyze 50–85 behavioral signals from your existing data.

Engagement signals
  • Days since last login
  • Login frequency (7-day, 14-day, 30-day trends)
  • Feature breadth (how many features used)
  • Feature depth (intensity of use)
  • Session duration trends
Behavioral signals
  • Time to first value (how long to activate)
  • Key feature adoption (which high-value features used)
  • Support ticket frequency and sentiment
  • In-app search patterns (looking for help = friction)
Financial signals
  • Days until renewal
  • Contract value relative to usage
  • Payment history (delays, failures)
  • Discount level (heavily discounted = price-sensitive)

We build the model using your historical data: logistic regression for interpretability, gradient boosting for accuracy, combined into an ensemble.

Trained churn prediction model + feature importance analysis
WEEK 2

Risk Scoring + Intervention Playbook

We score every active customer across four risk levels.

Risk LevelScoreWhat It Means
Low0–25%Healthy, no action needed
Medium25–50%Watch list, light touch
High50–75%Proactive outreach needed
Critical75–100%Immediate intervention
INTERVENTION ACTIONS
  • Critical (75–100%): 48-hour outreach script, executive escalation criteria, save offer parameters
  • High-risk (50–75%): Feature discovery campaign, check-in call framework, success plan template
  • Medium-risk (25–50%): Dashboard alerts, automated email triggers, health score thresholds
Customer risk scorecard + Intervention Playbook + SQL queries for ongoing scoring

What "prediction" actually means in practice.

We don't promise magic. We promise math.

30–60
Days of Early Warning
Your CS team sees risk before customers decide to leave
35–45%
Of Churns Captured in Top 10% of Risk Scores
Focus on the top 10% to save 35–45% of all churns
50–85
Behavioral Signals Analyzed
From your existing analytics data — no new instrumentation
3
Top Churn Drivers Per Account
Not just "at risk" — but WHY
If you have 1,000 customers and 50 churn per quarter, the model will correctly flag 18–23 of them in the top 100 risk scores, 30–60 days before they cancel. Enough time for your CS team to intervene.

$4,997. You own everything.

$4,997 one-time
  • Trained churn prediction model
  • Customer risk scorecard (every customer scored)
  • Feature importance analysis (what drives churn for YOUR customers)
  • Intervention playbook (4 risk levels, specific actions)
  • SQL queries for ongoing risk scoring (your team runs these monthly)
  • 60-minute walkthrough call
  • 30-day email support

You own the model, the queries, and the playbook. No ongoing fees required.

If the model can't identify at-risk accounts better than random, we refund 100%. This hasn't happened.
Start Predicting Churn — $4,997
Want us to run the model monthly and update scores? Available at $1,497/month — but the one-time delivery stands on its own.

What we need from you.

Setup time: 5–10 minutes to grant read-only access. No engineering work required from your team.

Common questions.

How accurate is the model?
The model identifies at-risk accounts 30–60 days before cancellation. Top 10% of risk scores capture 35–45% of actual churns. No model is 100%, but knowing which 10% to focus on is dramatically better than guessing.
What if we don't have enough data?
You need at least 6 months of history and 500+ customers. Below that, the model won't be reliable. We'll tell you upfront if we don't think there's enough data — before you pay.
Can our team maintain this without you?
Yes. We deliver SQL queries your team runs monthly. Any analyst who knows basic SQL can refresh scores. Full documentation included.
What analytics platforms do you support?
Amplitude, Mixpanel, PostHog, Segment, Google Analytics, BigQuery, Snowflake, and most SQL databases. Ask if you use something different.
Is our data safe?
Read-only access only. We never export raw customer data. We work within your analytics platform. NDA available. Compliant process for healthcare companies — we work within your existing security framework.

Every month you wait, accounts churn that could have been saved.

$4,997 to know which customers are leaving before they decide to. 2 weeks to a working prediction system.

This sprint solves one problem. The Foundation (6-week diagnostic) connects it to everything else — pricing, activation, competitive positioning — so fixes compound.

Start Predicting Churn — $4,997 Have questions? Email [email protected]