Better customer segmenting by looking at more than one analysis

When you're marketing to your best customers, how do you decide who is the best?

Is it based on how much they spend?

Or how many times they've ordered?

Or how long ago they last ordered?

Each of those is a component of the RFM algorithm but it doesn't give you a straight answer. That's because much will depend on how a customer's scores relate to each other.

For example, you'd want to send a VIP promotion to customers who have ordered frequently (F=4 and F=5) but probably not to ones who just ordered last week (R=5). Otherwise you might have some complaints and have to price-match past orders which can cause a lot of extra customer service work.

Relating two scores together will give you a better understanding of the customers.

Three scores is even better but it can get overwhelming (that's 125 different segments).

This relationship between scores is what Repeat Customer Insights' Customer Grid does for you. By comparing the scores in pairs, it creates easier to understand segments. That's how it's able to describe and provide recommendations for each segment of customers.

Eric Davis

Retain the best customers and leave the worst for your competitors to steal

If you're having problems with customers not coming back or defecting to competitors, Repeat Customer Insights might help uncover why that's happening.
Using its analyses you can figure out how to better target the good customers and let the bad ones go elsewhere.

Learn more

Topics: Customer segmenting Rfm

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