A few months back I adapted Repeat Customer Insights so it can analyze itself. Meaning for my custom "store", instead of using Shopify for the data it uses it's own data for analysis.
It's not a perfect match as ecommerce has different customer behavior than SaaS but the majority of the analyses and insights worked right away and showed their value. Some were even better than I expected (e.g. the First Product Analysis showing which account levels were attractive to new customers).
It works because many of the models apply to all forms of commerce. One-time retail sales. Ecommerce. Subscription boxes. SaaS. Even blends of different forms.
The advice, norms, and tactics will be different but many of those vary between businesses in the same industry already.
Strong models and well-thought-out customer analyses are universal.
That's why you should find ones that have been tested heavily like RFM and rely on them instead of the latest fad and gimmick.
Plus this adaptation has given me lots of ideas for future features.
Market to your customer's timing
Figure out how long customers wait in-between purchases and you have a key component for your marketing timing. This is the basis of the Average Latency metric and Order Sequence Report in Repeat Customer Insights.