Predicting customer behavior is quite challenging. But knowledge of a customer at an individual level offers enormous benefits, and can help companies provide better customer experience and retention, targeted marketing, increase sales, and proactive care. However, many existing customer models are very macro in nature and fail to deliver at an individual level.
Machine Learning allows us to build micro-level models by taking into account all digital touch points of a customer with the company. These models will help predict what a customer is going to do next, what their near-future behavior will be and what response to anticipate from an action.
On this webinar, you’ll hear the current state of machine learning in Customer 360 – and then learn how you can stay one step ahead in building highly customer-centric models for your business.
You'll discover how Automated Machine Learning provides:
The ability to develop and refresh Customer 360 predictive models at any time
The ability to deploy models with a click of a button
The ability to operationalize Customer 360 models by following a process that is user-centric
Justin Dickerson GM of Global Finance, DataRobot
Raju Penmatcha Customer-Facing Data Scientist, DataRobot