Yesterday I was going through the sales process for Repeat Customer Insights and assigning one metric to watch for each stage of the process.
I'm doing this so I have a focus for optimizations. At a glance I can see where problems arise and the overall health.
(I'm also using the Green/Yellow/Red light system which makes it even easier)
As I was thinking about the process, one part caught my attention: the Retention/Upsell step.
The app is a subscription app so churn-based metrics are the best metric for retention.
But if the app was sold differently, other metrics would be more relevant.
Repeat purchases or the Repeat Repurchase Rate would be the best retention metric if someone could buy the same product again or buy any other product. It's a measure of the customer's overall behavior, e.g. did they like the product enough to buy again?
Most Shopify stores will want to measure and track their Repeat Purchase Rate. The rate is better than the raw amounts in most cases because it'll adjust to business growth/contraction.
Repeat Customer Insights tracks your Repeat Purchase Rate automatically for you. It's so important it was one of the first metrics ever added to the analyses.
Tracking upsells would be best if someone could only ever buy one unit of a product. A customer would have to buy another product or upgrade their account (like in the case of JSON-LD for SEO) if they wanted to buy again. Repeat Purchase Rate will still work for them except for upsells done before checkout (e.g. a good upsell app will track pre/post-upsell performance separately).
Stores selling on a subscription basis would use churn metrics for retention (e.g. customer churn, revenue churn, retention percentage).
Different metrics for different business models.
Track down which customer cohorts perform the best
Different groups of people behave differently. Repeat Customer Insights creates cohort groups for you automatically to see how your customers change over time and spot new behavior trends.