Let's dig into the new start date feature in Repeat Customer Insights a bit more.
(Even if you don't have the app, you might want to follow along as there's some advice you can steal from about tracking different dates)
Like most interesting things, your store has evolved and changed over time.
Perhaps you had major changes to your product offerings. Say going from drop-shipping and white-labeling to creating and manufacturing your own product.
Or you'd pivoted into another market (or sub-market).
Or you've changed how you sold (e.g. from wholesale to DTC).
Whatever the reason, the metrics before will be vastly different than the metrics after.
For example, if you sold wholesale and then switch to DTC it is likely your Average Order Value is going to drop like a rock. Instead of a handful of retailer ordering 100s of units you might have 1,000s of consumers ordering a couple of units each.
Using the regular date filters in Repeat Customer Insights you'd learn that your AOV has dropped but that's common sense. You'd probably think the drop was due to the placement change but everything is fine now.
What if there's a second drop that happened since you went DTC? Say a coupon is getting over-redeemed or your free shipping offer is too-low? The old all-time period would have caused you to ignore your AOV (in a boy-cried wolf situation).
With the new start date you now have the option to show the analyses from that date on. In this example, you'd want to separate the wholesale from selling DTC and see that while selling by DTC-only your AOV has dropped in the last few months.
The start date also plugs into the Insights Systems so your metrics will automatically be compared to your full history, this year, and even the quarter-over-quarter. This comparison can help you catch trends early enough to correct them.
Eric Davis
Measure your customer loyalty
Measure the different levels of customer loyalty with Repeat Customer Insights. It uses various models to segment and grade your customers based on their behavior.