This Case Shows Specific Expertise. Find the Companies with the Skills Your Project Demands!

You're viewing one of tens of thousands of real cases compiled on Many.dev. Each case demonstrates specific, tangible expertise.

But how do you find the company that possesses the exact skills and experience needed for your project? Forget generic filters!

Our unique AI system allows you to describe your project in your own words and instantly get a list of companies that have already successfully applied that precise expertise in similar projects.

Create a free account to unlock powerful AI-powered search and connect with companies whose expertise directly matches your project's requirements.

AI-Powered Customer Churn Prediction and Retention System

coderio.com

Food & Beverage

Subscription Services

Telecommunications

Financial Services

Customer Churn Risk and Retention Challenges

CocaCola Andina required a predictive tool to anticipate customer churn and manage abandonment risks. The lack of an early warning system hindered proactive retention strategies, leading to potential revenue losses and inefficiencies in customer lifetime value optimization.

About the Client

One of the largest CocaCola bottlers in Latin America, operating in Chile, Argentina, Brazil, and Paraguay. Focused on innovation, sustainability, and operational efficiency in beverage production, distribution, and sales.

Development of Predictive Churn Management System

Implement an AI-driven early warning system to identify customer churn risks up to 90 days in advance
Reduce customer churn rates through proactive retention strategies
Optimize retention costs and maximize customer lifetime value
Enable data-driven decision-making via real-time analytics and dashboards

Core System Functionalities and Features

Real-time dashboard for churn risk visualization
Risk factor analysis and pattern detection algorithms
Early warning alerts for potential customer losses
Integration with existing CRM and data warehouse systems
Customizable retention strategy recommendations

Preferred Technologies

Python

Power BI

AWS

Machine Learning Algorithms

Required System Integrations

CRM platforms
Enterprise data warehouses
Third-party analytics tools

Non-Functional Requirements

Scalability to handle large volumes of customer data
Real-time processing performance for timely alerts
Data security and compliance with privacy regulations
High system availability and fault tolerance

Expected Business Impact

Enables proactive customer retention strategies through 90-day advance churn prediction, reduces revenue losses from customer attrition, optimizes marketing spend efficiency, and enhances customer lifetime value through targeted interventions.