Predicting Customer Churn with Accurate and Explainable AI Models

A business has a product or service that attracts customers and generates revenue streams. Everything is great for a while. Now the business sees customers are churning. Business analysts and domain experts in your company are pouring over KPIs and doing surveys to identify a few trends, yet cannot quite pinpoint the mix of causes for every customer churned. Most importantly, marketing does not have a rank ordered list of potential churners next month and the reasons why they would leave - to effectively craft relevant and personalized campaigns, offers etc., and bring them back in! If this sounds like your business, this is where building high accurate AI/ML models with explainability can help greatly. Churn is a common issue. It can happen to a business for a variety of reasons - Pricing, Competition, Quality of product, Service, etc. This webinar is about building AI/ML Churn models and explaining the reasons for churn at a customer level. In this webinar, you will learn: - How to define churn in your business - Hard churn vs Soft Churn - How to structure the problem with the historical data you have - How to create training, test and holdout sets for building models - How to build AI/ML models using Driverless AI in a few min - Generate rank ordered churners with reason codes. - Identify areas (Prescription) quantitatively in your business for improving customer retention Presenter: Karthik Guruswamy, Sr. Principal Solutions Architect at H2O.ai