Shopify articles - Page 24

Automatic segments help smaller Shopify stores retain customers

To help RFM work better on small and mid-sized stores, I added Automatic Segments into Repeat Customer Insights a few years ago. They consolidate each pair of RFM scores into a specific segment (like R5F3). Similar segments are then grouped to create the final Automatic Segments (R5F3 becomes the Potential...

Starting repeat purchase analysis in Shopify

I came across a question from a Shopify store the other day: What's the best way to start doing LTV and repeat purchase analysis? How early would you start paying attention to it? I've got 2000 customers so far and curious about seeing repeat purchases and in particular what impacts...

Correctly configured cohorts should accommodate refunds smoothly

Following up on yesterday's article, Shopify's refund skewing can get complex when it comes to customer cohorts. I don't know how their cohorts work but in Repeat Customer Insights the cohorts use the order's adjusted values as described in the previous article (i.e. refunds adjust the original order's amount). That...

How refunds can skew Shopify reports

Recently a Repeat Customer Insights customer was asking about how order refunds work in the app because Shopify's behavior is odd. Shopify subtracts refunds for repeat customers that come in during that month from the repeat customer revenue in that month. We had to issue a bunch of refunds in...

How Customer Purchase Latency takes the guesswork out of scheduling marketing

Customer Purchase Latency is a metric that measures the number of day in-between orders. If a customer comes in to buy a sandwich every day, their latency is 1 (day). If they come in every Tuesday, it's 7. Alone, Customer Purchase Latency isn't very actionable because individual customer behavior varies...

Use quality tools to give you the answers you need

With Spring just around the corner, I've been monitoring the garden temperatures in the air and soil. The experiment with the grow lights worked really well. Too-well in fact... The fava grew quite well (less than 3% failed to germinate). The peas though, they took off like little-green rockets and...

Analyze how your customer base changes over time to find hidden trends

An extremely valuable analysis technique that's often overlooked is to evaluate how your customer base changes over time. Not just demographic data (e.g. they are getting older) but how your different customer segments make-up your customer base as a whole. Are you getting more loyal customers? Are so-so customers defecting...

How different AOV meanings teach you new things about your customers

Average Order Value (AOV) is a metric mentioned a lot when it comes to ecommerce metrics. It's easy enough to calculate your AOV, you're just adding a bunch of order totals together and then dividing to find the average. The fun part of comes from giving the AOV meaning. What...

Coping with unintended consequences

This weekend our neighbors cut down some large trees and bushes by our fence. That'll have a bunch of good consequences but one surprising negative one is the sun. Now the sun reflects off their house and blinds me in my office for a couple of hours each day. It's...

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