Growth Analysis method

Funnel Analysis

Shows at which defined journey step people fail to progress to the next step.

Funnel Analysis shows where people progress or drop out along a defined user journey. Comparing transition rates and user groups helps identify improvements to investigate.

Core question

At which step and for which cohort does the transition rate fall most?

Prepare plan Method guide

Start comparison

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Participants: 1-5
Time: 1-3 h

Phases may be revisited; their order supports the work but does not replace domain judgment.

Funnel Analysis workspace showing the question, observations, and next decision.

Flow
Bound the flow
Choose one user intent and order observable events.
Data
Validate events
Check names, identity, time window, and missing events against raw data.
Rates
Calculate transitions
Count unique people per step; divide transitions by the correct entering cohort.
Investigation
Investigate drop-off
Compare meaningful segments and combine anomalies with qualitative evidence.

Review the result and open assumptions at the next suitable checkpoint. Record changes, ownership, and new evidence.

A good fit when

Use when: One measurable flow with a clear start and completion.

Ideal for

Activation optimization
Checkout flows
Growth diagnostics

Not good for

Problem discovery without data
Pure qualitative motivation analysis

Outputs

Working picture
A defined user intent with ordered, observable events.
Testable evidence
Unique people per step and transition rates based on the correct entering cohort.
Next step
The analysis compares relevant user groups and connects unusual transition rates with qualitative findings.

Conversion funnel with rates per step

Fictional worked example

Find which defined journey step people do not progress beyond.

Frame

Describe flow, start, completion, and cohort.

Period: week 12; market: DE; device: mobile.

Steps

Record event names, rules, and known tracking gaps.

View 10,000 → cart 2,400 → checkout 1,200 → purchase 840.

Rates

Enter numerator, denominator, rate, and window per transition.

Transitions: 24%, 50%, 70%. Each denominator is the prior step.

Question

Record the anomalous step and unresolved cause as a question.

Largest absolute loss is before cart; cause remains unknown.

Fictional shop, week 12: product views 10,000, carts 2,400, checkouts 1,200, purchases 840. Step conversions: 24%, 50%, 70%; the largest absolute loss is before the cart.

Three Steps to Increase Your Conversion Rate Using Funnels

First step

Start with a bounded question, clarify access and participants, and collect available evidence. Find which defined journey step people do not progress beyond.

Open the method guide

Good to do first

Growth

Pirate Metrics AARRR

Supplies the funnel stage whose loss gets investigated here in detail.

Where to go next?

Growth

A/B Testing

Tests a plausible cause of the loss with a controlled experiment.

Growth

Growth Experiment

Tests the investigation question with a small, measurable intervention.

Deep dive

Purpose

When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses.

How it works

The stages of a usage or purchase path are examined with data so dropouts and conversion losses can be located. This makes patterns by segment, source, or device distinguishable and hypotheses more precise. The method turns fuzzy growth questions into concrete bottlenecks.

In detail

Funnel Analysis examines behavior paths as measurable transitions rather than just conversion rates side by side. The analysis only becomes solid once event quality, segment differences, and channel or device breaks are checked before drawing conclusions. The insight value emerges where a visible drop-off is translated into a plausible cause and a testable optimization hypothesis.

Facilitation

First fix the stages, the time period under review, and the relevant segments so no discussion arises over different funnels. The analysis becomes really useful when breaks visibly differ by source, device, or target group. In the end there should be a clearly named drop-off with a checkable hypothesis for the next test.

The method guide walks execution through 4 phases, timing, 4 pitfalls, and clear stop criteria.

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Sources and topics

Topics

Analytics Conversion Growth

Sources

Three Steps to Increase Your Conversion Rate Using Funnelsinfo.amplitude.comMethod reference reviewed to support the scope and workflow of Funnel Analysis. Examples and editorial guidance are original and explicitly fictional.

In playbooks

Set Up a Growth Experiment LoopMove from a funnel problem to hypothesis, experiment, measurement, and next growth decision.

Artifact templates

Funnel Analysis: WorksheetPrepare Funnel Analysis with a clear question, roles, and sources.

markdown

funnel-analysis-working-template.md

Prepare Funnel Analysis with a clear question, roles, and sources.

Funnel Analysis: Worksheet

Question

To be confirmed

Desired outcome

To be confirmed

Scope

Plan the full method Time: Set according to scope and available evidence

Complete this worksheet on paper or in your own document during the work.

Preparation for this scope

Method setup

Materials: Shared workspace, accessible sources, and a decision log.
Roles: Product analytics · Product · Analytics
Advance information: Clarify the question, timeframe, data access, roles, and known uncertainties in advance.
Overall time needed: 30–60 minutes with prepared, validated event data; segment analysis may need separate time.
Setup: Create a shared version. Label facts, assumptions, and decisions separately.

Prepare for the work steps

Flow: Bound the flow

Start and completion events, intended journey

Data: Validate events

Event definitions, identity and consent rules

Rates: Calculate transitions

Unique people per step and time window

Investigation: Investigate drop-off

Drop-off points, segments, and qualitative clues