Predict and reduce customer churn

Predictive models that identify customers at risk of cancellation and recommend personalized retention actions.

Overview

The Churn accelerator uses machine learning models trained with transactional, behavioral and interaction data to predict which customers are most likely to cancel.

Services

Churn Prediction

Models that calculate the cancellation probability of each customer within the next 30, 60, and 90 days.

Early warning system

Early alert system that identifies disengagement signals before the customer decides to cancel.

Risk segmentation

Classification of customers into risk tiers (low, medium, high, critical) for action prioritization.

Personalized retention

Recommendation of the best retention action by profile: discount, upgrade, proactive support, or personal contact.

Root cause analysis

Identification of the main churn drivers: price, service, product, competition, and satisfaction.

Churn analytics dashboard

Dashboards with churn rates, at-risk value, retention action effectiveness, and cohort analysis.

Where we operate

Where we operate with Churn Prediction

SaaS & software

Subscription churn prediction, product usage analysis, and engagement-based retention actions.

Telecommunications

Post-paid plan churn prevention with personalized offers and portability analysis.

Banking & Insurance

Identification of customers at risk of account closure or policy non-renewal.

E-commerce & marketplace

Inactive customer reactivation and abandonment prevention with personalized offers and optimal timing.

Education

Student dropout prediction and preventive actions based on engagement and academic performance.

Healthcare & plans

Health plan beneficiary retention with satisfaction and service utilization analysis.

How we work

Churn Definition

Aligning the churn definition for the business: cancellation, inactivity, consumption reduction, or downgrade.

Feature Engineering

Building predictive variables: usage recency, interaction frequency, NPS, tickets, and engagement scores.

Modeling & Calibration

Model training with temporal validation, threshold optimization, and lift analysis by decile.

Activation & Integration

Integrating churn scores into CRM and marketing automation with retention action triggers.

Feedback & Evolution

Monitoring retention effectiveness, feedback loop, and retraining with executed action data.