The neat thing about having a unified customer scoring system like Customer Grades in my app, is that you can just sort customers quickly get an idea of your best customers.
Compare that to sorting by a single metric, like as Customer Lifetime Value.
With a single metric you'll see who is best for that metric but everything that metrics doesn't measure is missed. If you had one huge account in the past but they didn't come back, they probably aren't your best customers anymore. But looking at a single metric will make you think they are.
For example, if your products were used by the vendors of Super Bowl 2020, that account would have spent a ton in 2020. But then nothing else since.
A unified metrics that pulls in multiple others metrics will account for that. Your Super Bowl customer would score highly on amount spent but would score low on how many orders and recent orders. While that customer who buys $49 cases every month like clockwork could score higher.
In the long-term you want more $49/month regular customer than flash-in-the-pan accounts.
Eric Davis
Segment your customers to find the diamonds in the rough
Not all customers are equal but it is difficult to dig through all of your data to find the best customers.
Repeat Customer Insights will automatically analyze your Shopify customers to find the best ones. With over 150 segments applied automatically, it gives your store the analytics power of the big stores but without requiring a data scientist on staff.