If you have seen throughout the document, you might have noticed that I often said to leverage data, track, measure & optimize.
But, what should you be tracking?
Here’s the list of the metrics you should be tracking:
F.O.S.T.E.R™ (common across all)
These are the metrics you must be tracking across every single letter of the framework:
Drop-off Rate – Where do users abandon key flows? (Onboarding, features, pricing, etc.) Churn Rate – % of users leaving (monthly/yearly) Retention Rate – How many users stick around over time? Conversion Rate – % of users completing a key action (signup, upgrade, activation) NPS (Net Promoter Score) – How likely are users to recommend your product? Customer Lifetime Value (CLTV) – How much revenue does each customer generate? F: First moment clarity
Time to First Action – How long until users take the first meaningful step? Onboarding Completion Rate – % of users finishing the onboarding flow Activation Rate – % of users reaching the first “aha” moment (e.g., sending a message in Slack) Self-Reported Clarity Score – Survey: "Did you understand what to do next?" First Session Duration – Are they spending enough time to actually learn the product? Rage Clicks – How often do users furiously click on something that doesn’t work?
O: Optimizing for engagement
DAU/WAU/MAU (Active Users) – Daily, weekly, and monthly active users Stickiness Ratio (DAU/MAU) – Are monthly users coming back daily? Feature Adoption Rate – % of users regularly using key features Session Length & Frequency – How long and how often are they engaging? Time to Re-engagement – How long does it take before an inactive user comes back? Engagement by User Segment – Are power users driving all the activity, or is it balanced? S: Smart nudges
Nudge Open Rate – % of nudges (emails, push, in-app) that get opened Click-Through Rate (CTR) on Nudges – Are users acting on the nudge? Conversion Rate per Nudge Type – Which type of nudge (email, in-app, SMS) works best? Time to Action After Nudge – How quickly do users act after receiving a prompt? Unsubscribe/Opt-out Rate – Are nudges helping or just annoying people? T: Tactical pricing
Trial-to-Paid Conversion Rate – % of free trial users who convert to paid Churn by Pricing Tier – Which pricing plans have the highest churn? Expansion Revenue – How much revenue comes from upsells & cross-sells? Downgrade Rate – % of users switching to cheaper plans Discount Dependency – How many users only convert when they get a discount? Price Sensitivity Score – Survey: “Would you still pay if the price increased by X%?” E: Early Issue Detection
Support Ticket Volume & Themes – What are the most common complaints? Bug Reports & Frequency – How many bugs are users reporting? Latency & Performance Metrics – Is your app slowing down & frustrating users? Heatmaps & Session Recordings – Watch how users interact with your product First Contact Resolution Rate – % of support issues solved on first attempt
R: Refining for growth
Cohort Retention Analysis – How does retention look over different signup periods? A/B Testing Success Rate – % of experiments that lead to improvements Feature Sunset Rate – % of features removed due to low usage Revenue per User Growth – Is each user becoming more valuable over time? Referrals & Word of Mouth Growth – Are users bringing in more users? Time-to-Value (TTV) – How long before users experience real value from your product? Customer Support Load Over Time – Is the product getting easier to use, or do support requests keep increasing?
You can use a variety of tools to track each of them.
