Hey there, this is when I typically built a segment or two, export them to spreadsheets, and do some comparison analysis.

There are many ways to do this, but one quick way would be to choose two date ranges; ie: 60 days before your refresh and 60 days after, a year later (hopefully comparing the same weeks or months). Then make a segment of people who purchased at least 2 times for each range and compare.

Spend and traffic can differ between years, so take it with a grain of salt. Ideally you’d be using your ecomm platform for this data analysis and you could try pulling down all your sales history and customer information and running it through an LLM to analyze, or if on Shopify, ask the AI assistant to do the work :)

Hey TJ.

Tried making a segment and the numbers didn’t make sense but will try it out again and see if i can get the results I am looking for. Thanks for your response :)

Regards

Heer

Hi ​@Heer,

Did you manage to figure this out?

I like TJ’s suggestion above. Another simple way to achieve this would be to create a segment of everybody who’s placed an order at least once over a certain time frame, and then another segment of everybody who’s done so at least twice. The number of profiles in the second segment divided by the number in the first segment will be your repeat purchase rate for that time frame. Let me know if you have any questions.

-Byrne

Just to add here, depending on if this type of reporting is granular enough  for you, but you can go to the Placed Order Metrics and look at a really high level cohort report.  There are many other commercial reporting tools that can generate more specific filters or views (e.g. by weekly cohorts, etc).  But if you just need a high level view, I find this chart just enough to get some high level insights.

You can find the cohort analysis here: Analytics → Metrics → (Placed Order - or whichever metric) → Cohorts.

You’ll get a Cohort Analysis chart that might look like this:

This will show you, in this case “Placed Order” events by each monthly cohort.  So if you look at this a few months after the brand refresh, you can see those folks that purchased in the months right after the brand refresh, and see how many of them came back to repurchase either as a percentage (or count).  You can then compare the folks that purchased in previous months before the brand refresh, and how many came back in month 2, 3, etc.  

You can learn more about this here:

• Understanding cohort analysis in the metrics tab

Hope this helps!