There are innumerable optimizations you can try in your Shopify store. But boiled down they all fall into two groups: adding something positive removing something negative Optimize your images to make them smaller and load faster? Removing negative (the time for the page to load). Upsell a product on your cart page? Adding positive (larger …
Tag: kb repeat customer insights
Find which products to promote or ignore by using your Repeat Purchase Rate as a hurdle rate
One way to evaluate which products to promote is to look for the ones that create more repeat buyers. To do this, you’ll want to calculate the Repeat Purchase Rate for each product, preferably based on the first order. Repeat Customer Insights does this for you automatically in the First Product Analysis. Next you want …
Discovering which products bring back the most repeat customers
Your products have a few purposes but two important ones are: contribute to your Shopify store’s profit satisfy the customer so they come back and buy again later Satisfying the customer vs making the customer happy is a whole multiple-article discussion that we’ll leave for now. Getting a customer to come back and make a …
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 …
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 …
New period comparison insights added to Repeat Customer Insights
Repeat Customer Insights has received updates to its data analysis and insights engine. Now the Store Analysis and Customer Purchase Latency reports will automatically compare the various metrics to how they performed in the past. You can select any year or quarter available in your account and the app will analyze the performance compared to …
Using cumulative cohort reports to find groups of the best repeat buyers
A Repeat Customer Insights customers was asking about how the cumulative orders in the Cohorts Report work: Why doesn’t the sum of month 1 to n on the cohort customers % match the nth month for the cumulative cohort %? The percentages are based on how many unique customers have bought out of the whole …
Using alternative customer segmenting models when your Shopify store is still growing
The RFM model works really well for large stores. With 125 unique segments, there’s a lot of fine-tuning potential. For smaller stores (and stores that don’t want to fiddle), it might be too much as it is. Say you get 500 orders per month (6,000 per year). That means you’ll have about 4 customers added …
How Average Latency is underused by Shopify stores
Recently I added the Average Latency metric to Repeat Customer Insights. Latency is the time between events for a customer, specially purchases. For example, if Sally placed two orders 10 days apart then their Latency would be 10 days. The app has always reported on the Average Latency in the order sequences, e.g. 10 days on …
Learning when to switch tactics as the results falloff
This morning I planted a few hundred seeds into the garden. Normally I try to grow the seeds into baby plants and then transplant those. They’re stronger and more likely to survive. But with the weather lots of the baby plants aren’t surviving long enough to get transplanted. A good third of the garden has …