I've been getting more fond of cohort reports lately.
They present a lot of data all at once which is overwhelming at first, but the more you work with them the easier they get.
What I've been enjoying is using the cohorts as a quick way to watch customer acquisition trends.
I'll look at last month and the month before and compare them to how this month is going. But not the whole cohort, only the initial month. This ensures I'm looking at only the new customer behavior in the month which is only acquisition.
Using June as an example, I'd compare:
- June's metrics vs
- May's metrics in Month 0 vs
- April's metrics in Month 0
The Month 0 part is key, otherwise you'll pull in later behavior (e.g. April's cohort who came back in May or June to buy again).
In Repeat Customer Insights where Month 0 is laid out vertically, this is easy to compare as you just read down the column.
This process keeps new customer behavior separate from repeat customer behavior so you can spot acquisition problems before them grow to big to handle.
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.