Retaining customers is core to the success of any business. Therefore, the ability to predict your rate of customer retention, or the percentage of customers that will stop using your product or service during a certain time frame, is key to informing the next actions you choose to take with customers.

Enterprise organizations are now more enabled than ever to leverage machine learning techniques on top of their large, highly-valuable data sets to provide insights. And predicting customer churn is a prime use case of such machine learning techniques. To see how to do this and what to consider when tailoring this use case to the way your business works, watch this recorded webcast by Thorogood Data and AI Consultants Sanjay Sajeevan and Robbie Shaw.

What to expect:

• Background on the different approaches to model customer retention depending on the nature of the business and the depth of insight desired
• A demo using Amazon SageMaker about how machine learning can be applied to predict customer retention
• How to use the results to influence business decisions from an aggregate level and to individual customers
• Further considerations around machine learning model improvement and next best step recommendations for customers

Is it for you?

• Are you looking to improve your customer analysis to retain more business?
• Are you interested in the application of machine learning and artificial intelligence to key business questions?
• Are you interested in using Amazon SageMaker for machine learning?