We’ve recently added some new tools that work really well together to help you better understand customer behavior. These tools are available in your account now if you’ve connected your store using our automatic Shopify data import tool.
New Filtering Options
We’ve added two new ways for you to isolate different segments of customers for analysis in Everhort.
When you click to add a filter, you’ll now see a dialog like the one below, with tabs to select filters at the customer level or the order level.
On the customer tab, you can now select to filter by customer tag. Tags will be populated automatically from your store if you are using Everhort’s Shopify import connection.
If you click over to the “Order” tab, you can filter customers based on certain criteria about their orders. On this tab, we’ve added the ability to filter by product property:
Like customer tags, product properties will be imported automatically from your Shopify store.
You can use several different types of matchers when filtering by product property, including Equals, Does Not Equal, Is Set, and Is Not Set. You can learn more about how these matchers work can in our support center.
New Baseline Average LTV
After applying a filter, Everhort will add a new green line to the LTV by Cohort chart showing how the “baseline,” or unfiltered average LTV compares to the performance of your filtered customer group.
For example, let’s say we’ve filtered by customers who are tagged “Subscriber:”
The new “12 mo. average (baseline)” curve helps us see that all monthly cohorts in the “Subscribers” segment of customers, especially recent cohorts, have superior LTV curves. After 11 months, customers in this segment have an average LTV of $2,000, compared to an average LTV of only $1,226 among the customer base as a whole.
We believe the new filters and baseline average tool work well together to help you understand how different segments of customers perform relative to each other. We will be adding more types of filters and matchers in the future to allow you take this even further.