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glossary · analytics term

What is funnel analysis?

The technique for finding the exact step where a flow leaks the most people, so you know what to fix next.

Funnel analysis is the practice of measuring how many people reach each ordered step of a multi-step flow, such as visit, signup, activate, and pay, and calculating the percentage who continue versus the percentage who drop off between steps, so you can locate the single step where you lose the most users. Each step's conversion rate is the count who reached that step divided by the count who reached the step before it; its drop-off rate is one minus that, the share who left. The overall conversion rate is the count who finished the last step divided by the count who entered the first. The point of the analysis is to find the biggest leak: the step with the steepest drop-off is where a fix returns the most users, because every step after it is capped by how few make it through. A good funnel report also shows time-to-convert (how long a step takes) and lets you break the funnel down by a property (source, plan, device) so you can see the drop-off is worse for, say, mobile signups. It answers one question, of everyone who started, where exactly did we lose them, which is the question that tells you what to fix next.
the mechanics

Steps, conversion, and drop-off

A funnel is an ordered list of steps a user is supposed to pass through, top to bottom. For a product it is often something like visit → signup → activate → pay. Funnel analysis puts a number on the narrowing between each pair of steps:

  • ·Steps are the events in order. Each user either reaches a step or does not, and reaching step 3 means they also reached steps 1 and 2.
  • ·Step conversion is the count who reached a step divided by the count who reached the step before it. It is always between 0% and 100%.
  • ·Drop-off is one minus the step conversion, the share who left at that step. The step with the biggest drop-off is the leak.
  • ·Overall conversion is the count who finished the last step divided by the count who entered the first. Every step after the leak is capped by it.

A useful funnel report adds two things on top: time-to-convert (how long a step takes, so a slow step shows up even when few people abandon it) and a breakdown by a property like source, plan, or device (so you can see that the drop-off is much worse for mobile than desktop).

a worked example

A concrete example

Say 1,000 people land on your pricing page this week. Here is the funnel to a paid plan:

stepreachedstep conversiondrop-off
1 · visit pricing1,000n/an/a
2 · start signup40040%60%
3 · activate12030%70%
4 · pay8470%30%

Overall conversion is 84 / 1,000 = 8.4%. But the headline number is not the point. The biggest drop-off is step 2 to step 3, activate, where you lose 70% of the people who started signing up. That is the leak. Doubling activation from 30% to 60% would roughly double paid customers, because every step below it is fed by that step. Spending the same effort on the pay step (already 70% conversion) would move far fewer users. Funnel analysis is what tells you to work on activation, not checkout.

how smolanalytics does it

Just ask where people drop off

In smolanalytics you track the steps as events (one snippet on the web, one POST /v1/events call from a server), then you do not build a funnel chart by hand. You ask, in plain English, from a dashboard bar or from your own Cursor or Claude over MCP:

where do people drop off in the signup funnel?
what's the visit → activate → pay conversion, and which step leaks most?
is the activation drop-off worse on mobile than desktop?

The answer is computed from your events by the same deterministic report the dashboard renders, never generated by a language model, so the leak is named exactly, with its real drop-off number, not a plausible guess. A CI agreement test fails the build if the editor's answer ever differs from the dashboard, so the number you are told to act on is the number that is true.

You do not even have to ask. The verdict, on the dashboard and in a morning brief, does this unprompted: it looks across your funnels, finds the step where you are losing the most people, and names that leak as the thing to fix. That is the whole idea, the tool tells you which step of the funnel to work on instead of leaving you to read a chart and guess.

Common questions

What is funnel analysis in simple terms?
It is counting how many people make it through each step of a flow and where they quit. Picture a real funnel: many people enter the top (a visit), fewer reach the middle (signup), fewer still reach the bottom (a paid plan). Funnel analysis puts a number on each narrowing so you can see the one step that loses the most people, which is the step worth fixing first.
How do you calculate conversion rate and drop-off rate?
Conversion rate for a step is the number of users who reached it divided by the number who reached the previous step. Drop-off rate is one minus that, the share who left at that step. Overall conversion is the number who completed the final step divided by the number who entered the first step. For example, 100 signups to 40 activations is a 40% step conversion and a 60% drop-off.
What is a good funnel conversion rate?
There is no universal number, it depends entirely on the flow, the audience, and how many steps there are. A five-step onboarding funnel and a two-step checkout are not comparable. The useful comparison is against your own past: track the same funnel over time and watch whether a specific step's drop-off improves after you change it. That is why a funnel is most valuable as a before-and-after, not as a single headline percentage.
What is the difference between funnel analysis and retention analysis?
A funnel measures a one-time ordered flow (did a user get from step 1 to step N this session or signup). Retention measures whether users keep coming back over days and weeks after they convert. Funnels tell you where people fail to finish; retention tells you whether the ones who finished stick around. You usually want both, and they read the same events.
How does smolanalytics do funnel analysis?
You track the steps as events, then ask in plain English, from a dashboard bar or your own coding agent over MCP, "where do people drop off?" The answer is computed from your events, never generated by a language model, so the biggest-leak step is named exactly, with its real drop-off number. The daily verdict does this unprompted: it surfaces the step you are losing the most people at and tells you to fix it.
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