Funnel Analysis is an analytical practice studying the changes over a course of events or steps in a user journey. It frequently follows the flow inside an application towards achieving a specific goal. For example the purchasing of an item on an ecommerce site: the funnel analysis will show how many users go through the full flow of steps to complete a purchase and how many stop (drop off) at which step (aka fallout rates).

The Funnel Analysis is an effective way to analyse conversion and fallout in applications. It is often used as a way to measure performance of similar products, e.g. web shops.

• This is a feedback loop practice, which allows the team to get prompt feedback from real life use of their changes
• Funnel Analysis provides a way for benchmarking of similar products
• It enables objective, data-informed decision-making in product teams
• When carefully followed over time, the analysis can reveal the real impact of product/feature changes, both positive and negative
• This is one of the practices that allow you to “tune the engine” and carry “innovation accounting” ( The Lean Startup by Eric Ries)
• The practice provides an objective criteria for important decisions on the product design, features, behaviour, etc. It is used as a way to enhance the product performance, the user experience and the business outcomes the product produces for your organization

This practice is fed with data from A/B Testing, Multi-vari Testing, and can be one of the final steps for running experiments which started with the Design of Experiments. Feature Toggles can greatly benefit the analysis as they can be used to tweak the application based on live feed of data and show if certain changes would influence the outcome.

The analysis is the final step before decision-making. It aims to produce actionable insight on how the team can further improve the performance of the product and the impact of past changes.

Feature Toggles

Cohort Analysis

A/B Testing

Multi-vari Testing

Design of Experiments