Reading Funnel Reports

Once a funnel is created, the funnel report gives you a step-by-step view of how visitors move through your defined journey — and where they stop. Reading this report correctly is what turns raw drop-off numbers into actionable decisions.

The funnel visualisation

The funnel report displays each step as a horizontal bar. The width or fill of each bar is proportional to the number of visitors who reached that step. As you move down through the steps, the bars narrow as visitors drop off.

For each step, you see:

  • Visitor count — the number of unique visitors who reached this step within the selected date range
  • Conversion rate from the previous step — the percentage of visitors from the previous step who continued to this one
  • Drop-off count and percentage — the number and percentage of visitors who did not continue to the next step

The top of the funnel (step 1) always shows 100% — it is the baseline against which all subsequent steps are measured. Every step below it shows its conversion rate relative to step 1 (cumulative conversion) and relative to the previous step (step-to-step conversion).

Understanding drop-off

The drop-off percentage between two consecutive steps is the core metric of a funnel. It tells you what fraction of the visitors who were progressing through the journey stopped at that transition.

How to read it: If 1,000 visitors reached step 1 and 400 reached step 2, the step 1→2 conversion rate is 40% and the drop-off is 60%. That 60% either left the site, navigated elsewhere, or did not complete the step-2 action in the same session.

What constitutes a "problem" drop-off: There is no universal benchmark because the right conversion rate depends entirely on the journey. A 10% checkout completion rate on a first visit from cold traffic may be excellent. A 40% drop-off between a cart page and the first checkout step is almost certainly worth investigating. Use your own data over time to establish baselines, then look for statistically meaningful changes.

Clicking into a step

Clicking on a step in the funnel report surfaces additional detail:

  • The percentage of all site visitors who reached this step (putting it in context of total traffic)
  • The percentage of step-1 starters who reached this step (cumulative funnel conversion)
  • The drop-off rate from the previous step

This layered view helps you understand whether a step's low conversion rate is caused by a small audience reaching it in the first place (a discovery problem) or by a large audience failing to convert once they arrive (a friction problem). These require completely different fixes.

Interpreting common patterns

Large drop at step 2 — the landing page is not convincing If the majority of visitors who reach step 1 do not proceed to step 2, the problem is usually the entry page itself. The page is either attracting visitors with the wrong intent, or it is failing to create enough motivation to continue. This is the most common funnel finding and often the most impactful to fix.

Common causes: unclear value proposition on the landing page, missing trust signals, weak or absent CTA, page load speed issues causing abandonment before the page fully renders.

Gradual decay across all steps — friction is distributed If each step loses a consistent 30–40% of visitors, there is no single catastrophic drop but the cumulative effect on final conversion is severe. This pattern often indicates broad friction: confusing navigation, too many required form fields, unclear next steps, or lack of urgency.

High drop on a late step — the closing moment is broken If visitors make it through most of the funnel but fail at the final step (e.g., the payment step or the confirmation action), the problem is typically very specific: a broken form, a payment processor error, a required field that is confusing, or unexpected costs revealed too late. Late-step failures often have the highest ROI to fix because the visitor was already committed.

Spike in drop-off correlated with a date — something changed If you can see the funnel over time, a sudden change in drop-off at a specific step that correlates with a deployment date indicates a regression. The JavaScript errors report is the next place to check.

Using funnels with heatmaps

Funnels tell you that visitors are dropping off at a step. Heatmaps tell you what they were doing on that page instead of proceeding. These two tools are most powerful when used together.

For example: your funnel shows a 65% drop-off on the checkout page. You enable a click heatmap on /checkout. The heatmap reveals that a large proportion of clicks are on a "Back to cart" link that sits prominently above the checkout form. The fix is a layout change — moving that link to be less prominent — not a copy change or an offer change.

Without the heatmap, you might spend time A/B testing headlines or adjusting pricing, missing the actual cause entirely.

FAQ

Does a visitor have to complete all steps in the same session? Yes. Statalog counts funnel progression within a single session. A visitor who views step 1 on Monday and step 2 on Wednesday is not counted as a funnel conversion. This is by design — session-level funnels reflect the immediate conversion flow and are less susceptible to coincidental path attribution. For journeys that span multiple sessions, step timings (see Step timings) will show very long average times, which is itself a useful signal.

What if my funnel steps can be visited in any order? Statalog funnels are ordered — visitors must reach steps in the defined sequence within a session. Steps visited out of order are not counted. If your journey genuinely allows non-linear paths, consider defining multiple funnels that capture each primary path separately.

Why do funnel visitor counts differ from the Pages report for the same URL? The Pages report counts all pageviews for a URL regardless of what came before or after. Funnel visitor counts are a subset — only visitors who reached that step as part of the defined sequence, within a session, are included. Funnel counts will always be lower than or equal to the total pageview count for a given URL.