Actionable SaaS Metrics

Want to know which metrics to track for your SaaS business and how to gain actual actionable knowledge? I'm working on an ebook and some JavaScript magic that you can directly use on our product.
http://metricsftw.com/

Transcript

1. Actionable SaaS metrics Thomas Fuchs Freckle Time Tracking
2. The goal is to sustainably make more money (duh).
3. Spend Less More customers Charge more easy (do it!) hard likely not worth it
4. What metrics to track?
5. Money per day
6. Conversion rate The percentage of newly created accounts that become paying customers
7. whoa, raw data sucks
8. now, that’s better* *more later
9. paid at least twice in 100 day time span signed up on January 26 Conversion rate
10. Churn rate The percentage of paying accounts that are cancelled* within a time period (usually monthly). *includes abandoned (credit card not updated)
11. Lifetime Customer Value All the monies the average paying customer will end up giving to you.
12. Lifetime Customer Value daily billed $ amount per paying customer × average length of paid subscription
13. Lifetime Customer Value Money = average daily $ amount billed in the last 30 days
14. Lifetime Customer Value Accounts = current number of active paying accounts
15. Lifetime Customer Value Churn = 30-day churn rate (in %) for the last 30 days
16. Money ÷ Accounts × 30 days × 100 ÷ Churn rate Lifetime Customer Value
17. (Money ÷ Accounts × 30) × (100 ÷ Churn) Example: Money = $1,000, Accounts = 500, Churn = 5% (1000 ÷ 500 × 30) × (100 ÷ 5) = 1000 ÷ 15000 × 20 = $1,200
18. The goal is to sustainably make more money…
19. (Money ÷ Accounts × 30) × (100 ÷ Churn) 1. charge more 3. lower churn 2. increase conversions
20. (Money ÷ Accounts × 30) × (100 ÷ Churn) easy hard hard
21. Trends > Absolute numbers It doesn’t matter if your churn rate is 2% or 15%, it only matters that it goes down over time (does it?)
22. Raw data (billed amount per day, last 3Y)
23. 30-day moving average (billed amount per day, last 3Y)
24. Days where billing didn’t work or where we had to catch up with lots of payments
25. These spikes are not meaningful and distract from the overall trend.
26. Locally weighted scatterplot smoothing (LOESS) (billed amount per day, last 3Y)
27. “LOESS is a non-parametric regression method that combines multiple regression models in a k-nearest- neighbor-based meta-model.” (Gesundheit!) TL;DR: LOESS gives you meaningful trends https://github.com/jasondavies/science.js/
28. Real world example: raising our prices
29. We increased prices between 60% and 250% Lifetime customer value up conversion rate down
30. To increase conversion rate, we introduced a lifecycle email sequence (after some tweaks it worked beautifully!)
31. Segmentation Find places to improve by plan, by number of users, by number of support emails, by amount of data, by referrer, etc.
32. thomas@slash7.com @thomasfuchs