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

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Refine your automated marketing campaigns with better timing

When building any automated marketing campaign that sends messages over time, you need to know how long the campaign should be and how long to delay the messages. The Customer Purchase Latency metrics calculated by Repeat Customer Insights can help you figure out that timing.

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Topics: Customer segmenting Rfm

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