Funnel and conversion analytics is the discipline of mapping sequential user actions toward a defined goal, measuring how many users complete each step, and diagnosing where and why they drop off. It sits at the core of product analytics, marketing measurement, and revenue operations — giving teams a precise vocabulary for what "conversion" means and a structured method for improving it. Unlike high-level metrics that tell you something changed, a well-built funnel tells you where it changed, for which segment, and by how much. The key mental model to carry into every funnel analysis: aggregate numbers lie — always segment before acting, and always anchor your window logic to real user behavior rather than calendar convenience.
What This Cheat Sheet Covers
This topic spans 13 focused tables and 100 indexed concepts, 92 flashcards. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
A jump-to index of every table row in this cheat sheet.
An interactive map of every table and concept in this topic.
Table 1: Funnel Core Concepts and Definitions
The vocabulary of funnel analytics is deceptively precise. Terms like "conversion rate," "drop-off," and "step" have exact meanings that determine what your data actually measures — getting them wrong produces misleading reports.
| Concept | Example | Description | |
|---|---|---|---|
Steps: Visit → Sign Up → Activate → Purchase | • An ordered sequence of user actions (events) leading to a defined goal • the "funnel" shape emerges as users fall off at each step | ||
event_name = 'Add to Cart' for step 3 | • A specific, trackable user action that represents a meaningful decision point • steps should reflect active user choices, not passive page loads | ||
Step 2: 142 of 593 = 24% | • Percentage of users completing the previous step who also complete the current step • the inverse of drop-off rate | ||
6 purchases from 593 visitors = 1% | • Percentage of users who entered the funnel at step 1 and completed the final step • the headline KPI, but least actionable on its own | ||
1 − (142 / 593) = 76% drop-off | • Percentage of users who reached a step but did not complete it • more useful than conversion rate for identifying problems | ||
Step 2 loses 451 users vs. step 4 losing 121 | • Raw count of users lost at each step • prioritize fixes by absolute loss, not percentage — higher volume losses have greater business impact | ||
Completed purchase, submitted lead form, account created | • A primary business goal action • the ultimate outcome the funnel is built to drive | ||
Added to cart, visited pricing page, watched demo video | • An action indirectly related to KPIs that occurs more frequently and indicates progress • two sub-types: process milestones and secondary actions | ||
Email verified → account created (macro) | • Micro conversion that represents linear movement toward a macro conversion • tracks where users stall on the direct path | ||
Signed up for newsletter (may predict future purchase) | • Micro conversion that does not directly lead to a macro but may predict future conversion • contextual to site goals | ||
Median 2 days from signup to first purchase | • How quickly users move through the funnel • two funnels with the same conversion rate can have very different velocities, impacting cash flow and trial conversion | ||
Median 14 min between "started sign-up" and "completed sign-up" | • Median duration between consecutive steps • long gaps signal friction at that specific transition even when drop-off looks acceptable |