No business likes to lose customers.
And today’s business world is more competitive than ever. Your customers have more options — and your competitors can reach them easier than ever before.
So customers are constantly juggling a decision around where to spend their money.
Consequently, developing a strategy to retain customers is now an essential part of any business.
But every customer leaves for different reasons, and an individualized retention campaign can be costly if you apply it to every one of your customers.
However, if you could predict in advance which customers are at risk of leaving, you could reduce those costs by solely directing efforts at folks that are at a high risk of jumping ship.
Fortunately, we can use artificial intelligence — or more specifically, a machine learning platform — to predict when a single customer is likely to leave based on their actions (or inaction). This is often called ‘churn.’
Although churn rate originally started out as a telecom concept, today, it’s a concern for businesses of all shapes and sizes — including startups.
And thanks to a number of cloud-based prediction APIs, accurately predicting churn is no longer exclusive to big businesses with deep pockets.
A.I.-Powered Churn Prediction
Churn prediction is one of the most popular uses for machine learning in business. It’s basically just a way of using historical data to detect customers who are likely to cancel their service in the near future.
In effect, we want to be able to predict an answer to the following question: “Is this particular customer going to leave us within the next X months? ”
And of course, there are only two possible answers to that question — yes or no. Easy.
For this guide we’re going to use BigML to make those predictions.
BigML provides a convenient graphical interface for setup, visualization of the data, and the final predictions. Everything is point-and-click — no coding necessary.
So let’s get to it…
Looking for an on ramp?
This is a how-to guide intended for developers and tech-savvy business leaders looking for a proven entry point into A.I.-powered business systems.
And the steps are really easy — it’ll only take a few minutes to run through this.
What You’ll Need
Right off the bat, let’s get the initial requirements knocked out.
Create an BigML account.
If you don’t already have a BigML account, go ahead and set one up.
Step 1: Create the Dataset
To start, go to your BigML Dashboard.
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