AI Churn Prediction & Retention
Subscription and SaaS businesses
In subscription businesses, churn is a silent revenue killer. This predictive module turns churn management from a reactive scramble into a proactive strategy: machine learning spots at-risk users early, and generative AI writes personalised save-offers so customer success teams can step in before the cancellation happens.
80%+
accuracy predicting each customer’s probability of churning
3
models trained and compared: Logistic Regression, Random Forest and XGBoost
1
live Streamlit app where teams filter high-risk customers and export action lists
The situation
For SaaS and subscription providers, losing users after just a few months badly undercuts profitability. Keeping a customer is always cheaper than winning a new one, yet most businesses only react once the customer is already out the door.
Key challenges
- Customer success teams can’t see which specific users are most likely to leave.
- Data sits in silos, hiding the real drivers behind cancellations.
- Marketing spends on generic retention campaigns instead of targeted interventions.
How it works
Spot the patterns
After cleaning thousands of raw customer records, Logistic Regression, Random Forest and XGBoost models were trained and tested to find the most accurate way to separate loyal users from flight risks.
Score the risk
The winning model gives every active customer a churn probability score, pushed automatically into Google Sheets as a fast, lightweight operational backend.
Generate the save
The highest-risk profiles go to Gemini 2.5 Pro, which acts as a strategic advisor and proposes a personalised retention move, such as a targeted discount or a plan adjustment.
Put it in the team’s hands
Everything is wrapped in a Streamlit app on Streamlit Community Cloud, where marketing and customer success filter high-risk cohorts and export action-ready CSVs in seconds.
The outcome
The system protects monthly recurring revenue and raises customer lifetime value.
- Proactive intervention: customer success focuses its incentives on the highest-risk segments.
- Personalised action: generic campaigns are replaced by AI-tailored offers based on real churn factors.
- Operational agility: complex model output becomes a daily, usable business tool.