How to Optimize Customer Conversions With AutoML

How to Optimize Customer Conversions With AutoML

How to Optimize Customer Conversions With AutoML. Here, we’ll explore how to optimize customer conversions from a banking dataset using the predictive analytics tool Apteo.

81 percent of sales leads aren’t converted¹. Without targeting the right leads and optimizing conversions, getting more leads is like pumping water into a leaky bucket.

In another article, I explored how to use machine learning to optimize enterprise sales conversions. Here, we’ll explore how to optimize customer conversions from a banking dataset using the predictive analytics tool Apteo.

We’re given customer attributes like age, job type, duration with the company, account balance, and so on, which we can use to predict subscribe, or whether the customer subscribes to a term deposit.

This is an example of a binary classification machine learning problem, since subscribe can either be “yes” or “no.”

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