Introducing Convertedin’s AI Prediction Engine for E-commerce Stores

Customer segmentation is an essential part of e-commerce growth and Convertedin. But our newest product release takes segmentation to a whole new level with AI prediction!

Now e-commerce store owners can use Convertedin to not only segment customers but also predict customer behavior and segments based on those customers’ actions inside your store.

The new AI Customer Prediction Engine views customers based on the RFM model, which segments customers based on recency, frequency, and monetary value criteria.

This is what the RFM model looks like:

1)     Recency, which measures the number of days since the customer last made a purchase.

2)     Frequency, which measures how often a customer visits or makes a purchase from your store.

3)     Monetary, which measures the total value of money spent by the customer during a specific time frame.

Convertedin’s new engine relies on RFM using machine learning.

In other words, it looks at customers who visited your store recently, are regular buyers, and who offer a high monetary value to your business and predicts other segments that are similar to them.

What does this mean for you as a store owner?

As a store owner, you can now use Convertedin to predict new customer segments such as who is ‘more likely to buy from you’ or ‘people who may churn next week or next month,’ and many more. 

You can then target them with automated cross-channel ads via Facebook, Instagram, and Snapchat.

For example, if you can see that some of your customers are segmented as “people who may churn next week,” you can create a specific ad for that segment across multiple social media channels.

When these likely-to-churn customers do not churn and begin visiting your store more and making purchases, Convertedin’s AI will automatically change their segment so that they can begin to see a new set of ads that helps them convert.

Customer Segments available in our new product release

At the moment, the new AI Prediction Engine can predict the follow customer segments and behaviors:

–          Top customers: These are customers who regularly buy from you, result in high revenues, and make the most purchases.

–          Active customers: These are customers who have made recent purchases and contribute regular revenue to your store.

–          Emerging customers: These are customers with high potential for up-selling and cross-selling opportunities, based on their recent purchases. They are a good source of revenue and are considered frequent buyers.

–          Unsteady customers: These are customers who have good potential to buy using upselling and cross-selling depending on the offer made. They have bought recently from your store but aren’t frequent buyers nor do they offer a high monetary value to your store. That’s why their frequency and monetary criteria are considered “unsteady.” 

–          Customers at risk: These are customers who aren’t currently buying from you but previously had a high frequency and monetary value to your store.

–          Potential lost customers: They are customers who aren’t buying from you now and have low frequency and monetary value.

–          Inactive customers: They are customers who aren’t buying from you now and have low buying frequency but when they used to buy from you, they brought in high revenues.

–          Lost customers: These are customers with low recency, frequency, and monetary value for your store.

–          Zero purchase customers: These are customers who have never made a purchase inside your store.

Explore Convertedin’s new AI prediction engine by logging into your dashboard.

To learn more about RFM and what the RFM model is, read our blog post RFM for E-Commerce: Basics You Need to Know.