Tag: kb repeat customer insights segmenting

Customer analysis details to better understand how a customer behaves

The Customer details page in Repeat Customer Insights shows what data the app has on a specific customer and how the analyses come out. Customer data First there is the customer data from Shopify including the customer’s name, email, what marketing consent they’ve given, and the ID from Shopify for the customer. The customer’s acquisition …

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Customer Segmenting to know which customers are the best customers

The Customer Segmenting in Repeat Customer Insights ties together various segmenting models into one place: RFM: Recency Frequency Monetary Customer Grading: A-F letter grades Automatic Segments Customer analysis Each customer is listed with their various analyses: Customer Grade When they last ordered How many orders they have (excluding cancelled orders) How much they’ve spent so …

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Digging into customer details to find your best customers

It’s been a busy month for Repeat Customer Insights development with a bunch of new features and analyses getting released. Eagle-eyed customers will notice the New Feature banners but I want to share them in detail. First up is the new customer details page. Every customer in your store will have one of these. You’ll …

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Why RFM has no set points that determine a customer’s ranking

Recently a Repeat Customer Insights was asking about what triggers the RFM scores to change, like from Recency 5 to 4. There are no set points or triggers that move customers from one RFM score to another. Rather, RFM ranks each customer against your customer base as a whole and based on where the individual …

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New customer filters for RFM scores released

Repeat Customer Insights now has the ability to filter customers by their RFM scores. Previously the app would use the RFM scores behind-the-scenes but they weren’t shown except in the data export. Great for spreadsheet users, but not great for stores who wanted to browse and explore their customers. I’ve added the option to filter …

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Most valuable 80/20 customer segments for your Shopify store

As a follow-up to my article about which segments to focus on, you can take a more precise approach. Each cell in Repeat Customer Insights’ Customer Grids is about 4% of your customer base. (The grid isn’t strictly 4% though due to how the algorithm works but it’s good for a rule of thumb). That …

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See how your customer segments have changed with the Customer Grid History

There’s been a suite of analyses I’ve wanted to add to Repeat Customer Insights since first reading them. I quietly launched the first back at the beginning of September but I’ve been watching its performance before officially announcing it. Eagle-eyed customers might have spotted it already. I’m calling it the Customer Grid History and it’s …

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How your customers automatically decay with RFM

RFM scores are built from three components: Recency, Frequency, and Monetary. Though they are scored the same, they act differently. Recency is an odd one and can look the most chaotic for some. That’s because Recency will start to decay from the moment a purchase is made and get lower and lower until the customer …

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