Funnel Analysis Guide
Identify and fix the biggest drop-off points in your conversion funnel.
Usage
- Define funnel steps from first touch to desired outcome
- Measure conversion rate between each consecutive step
- Identify the largest absolute drop-offs (not just percentage)
- Segment the funnel by user attributes to find specific problem areas
- Prioritize fixes by impact (drop-off volume × potential improvement)
Examples
- SaaS signup funnel: Landing page (10,000) → Signup form started (2,500, 25%) → Signup completed (1,500, 60%) → First action completed (600, 40%) → Day 7 retained (300, 50%) → Paid (90, 30%). Biggest absolute drop-off: landing → signup (7,500 lost). But signup → first action (900 lost at 40%) may be more impactful to fix — these users already showed intent
- E-commerce purchase funnel: Product view (50,000) → Add to cart (5,000, 10%) → Begin checkout (2,500, 50%) → Enter payment (2,000, 80%) → Purchase (1,600, 80%). Cart → checkout is the biggest relative drop (50%) — likely causes: unexpected shipping costs, required account creation, confusing cart UX
- Segmented funnel insight: Overall signup-to-activation: 40%. Mobile: 25%. Desktop: 55%. Mobile is dragging down the average. Investigation reveals: mobile onboarding wizard has a broken step 3 that doesn't scroll properly on small screens. Fix that one step and overall activation jumps to 48%
Guidelines
- Define funnel steps based on user actions, not page views — "clicked Add to Cart" is a better step than "viewed cart page"
- Use time-bounded funnels: "completed within 7 days of signup" not just "ever completed" — this gives actionable conversion rates
- Segment by: device, acquisition source, user plan, geography. Averages hide problems that segments reveal
- The step with the lowest conversion rate isn't always the best to fix — fix the step where you lose the most absolute users
- Beware of survivorship bias: users who reach step 5 are already highly engaged — their feedback doesn't represent those who dropped at step 2
- Run A/B tests on your highest-drop-off step first — a 10% improvement on a 25% conversion step has more impact than 10% improvement on a 90% step