Retention Intelligence

Know Who Will Leave Before They Do

Score churn risk and deploy save actions where they protect the most revenue.

Review My Churn Metrics Discuss a Retention Strategy
R
Retention / Risk Monitor
Live
Total Risk Volume
$1.2M High Priority
Avg Risk Score
0.74 Active Base
Campaign Performance
+12.5% Save Rate
High Risk Customers
AC
Acme Corp
Score: 0.92 (Critical)
GS
Global Systems
Score: 0.78 (Warning)
OI
Omega Inc
Score: 0.65 (Watch)
Top Predictors
Login Frequency
Support Sentiment
Recommended Action
Executive Outreach

The Problem

Most organisations know who churned, not who is about to churn:

Churn is reported monthly or quarterly, with little early warning.

Cancellations, dormancy, and inactivity sit in different systems and reports.

“Save” offers are generic, not designed by segment, risk level, or lifetime value.

Retention, sales, and marketing teams work from different churn numbers and definitions.

Result: preventable revenue loss, rising acquisition pressure, and limited visibility on which customers can still be saved.

Business Outcomes

Protect recurring revenue and CLTV by intervening before customers fully lapse.

Improve unit economics by retaining profitable segments instead of replacing them at high CAC.

Stabilise forecasts by reducing volatility in active base and renewal rates.

Align teams around clear churn definitions, risk thresholds, and ownership.

Core Offerings

Customer Churn Management Services

01

Churn Framework & Definition Design

Create a clear, shared definition of churn and risk.

  • Churn definitions by business model (subscription, repeat purchase, contract-based).
  • Time-to-churn thresholds by product, segment, and lifecycle stage.
  • Base churn taxonomy: voluntary vs involuntary, price-driven vs service-driven.
  • Ownership map: which teams own which parts of the retention funnel.
Definition Architecture
Total Customer Base
Voluntary Churn
"I want to cancel"
Price Sensitivity Competitor Switch
Involuntary Churn
"Payment Failed"
Card Expired Dunning Failed
02

Data & Signal Foundation

Assemble the behavioural, transactional, and service data needed to detect risk early.

  • Unified customer and account ID across CRM, billing, ecommerce, and support.
  • Churn feature set (RFM, Usage, Engagement, Support signals).
  • Cohort tables and retention curves at product/segment level.
Unified Signal Architecture
Salesforce
Stripe
Zendesk
Mixpanel
Identity Resolution
Stitching Sessions & IDs
Feature Store
03

Churn Risk Modeling

Quantify churn risk and prioritise customers and segments for action.

  • Churn propensity models (ML techniques).
  • Survival / time-to-event models to estimate timing.
  • Driver analysis to identify top predictors.
JD
John Doe Inc.
Enterprise Plan
92/100
Critical Risk
Risk Factors (SHAP Values)
Support Ticket Vol (High) +15% Risk
Login Frequency (Drop) +12% Risk
License Utilisation +5% Risk
Model: XGBoost_v4
94% Accuracy
04

Retention Playbooks & Activation

Translate risk scores into operational actions.

  • Segment- and risk-specific playbooks.
  • Integration into CRM and Marketing Automation.
  • Triggered campaigns based on risk level.
retention_logic.js
1 const assessCustomer = (customer) => {
2 if (customer.riskScore > 0.85) {
3 // Trigger Executive Intervention
4 crm.createTask({
5 priority: 'URGENT',
6 owner: 'VP_Success',
7 playbook: 'SAVE_OFFER_A'
8 });
9 } else {
10 marketing.addToFlow('NURTURE');
11 }
12 }
05

Measurement & Governance

Ensure churn management delivers measurable lift and remains under control.

  • Dashboards for churn, retention, and reactivation.
  • A/B and uplift testing frameworks.
  • Reporting on incremental revenue saved.
Retention Lift Experiment
Cohort: Q3 High Risk
Stat Sig (p < 0.01)
72%
Control
+8.5%
Test Group
Revenue Saved
$42,500
ROI
4.5x

Typical Use Cases

Subscription and SaaS

Renewal risk scoring, save teams prioritisation, and downgrade early-warning signals.

Ecommerce and retail

Inactivity detection, win-back campaigns, and segment-specific offers.

Financial services and telecom

Attrition risk by product and plan, targeted retention and cross-sell actions.

Why Rudder Analytics

Data and model-led approach

Churn work grounded in RFM, survival analysis, and propensity modeling, not generic KPIs.

Full-stack capability

From data engineering and feature design to models, dashboards, and activation.

Business focus

Every churn initiative measured in revenue retained, margin impact, and CAC reduction.

Tool-agnostic deployment

Churn scores and playbooks integrated into existing CRM, MAP, CDP, and support platforms.

Turn churn management into a predictable, measurable revenue protection system.

Review My Churn Metrics Discuss a Retention Strategy