Habit Testing Methodology

Key Insight

Habit Testing is an iterative process designed to measure a product's effectiveness in building user habits, providing actionable data to inform design. Inspired by the 'build-measure-learn' methodology, it clarifies who a product's devoted users are, identifies specific habit-forming elements, and explains why those aspects change user behavior. This process assumes an existing product with users and meaningful data for analysis. The Hook Model serves as an initial framework for prototyping habit-forming technologies and pinpointing weaknesses in existing products by evaluating internal triggers, external cues, action simplicity, reward satisfaction, and user investment.

The first step, 'Identify', requires defining what constitutes a habitual user by establishing how often they 'should' engage with the product. This definition is crucial and can be informed by publicly available data from similar products or realistic, educated assumptions, avoiding overly aggressive predictions for 'uber-users'. For example, a social networking app might expect multiple daily visits, while a movie recommendation site could anticipate one or two weekly visits. After defining this threshold, product data is analyzed to find users meeting the criteria, with cohort analysis recommended for tracking behavioral changes across future product iterations.

The second step, 'Codify', involves studying the actions of these identified habitual users to understand what 'hooked' them. An initial benchmark suggests that if at least five percent of users do not meet the devoted user criteria, the product or user identification may need re-evaluation. The goal is to discover a 'Habit Path' – a series of similar actions shared by the most loyal users, such as their origin, registration decisions, or network size. For instance, Twitter found that new users who followed 30 other members reached a tipping point, significantly increasing their retention. The final step, 'Modify', utilizes these insights to adjust the product, nudging new users towards the identified Habit Path through changes like registration funnel updates, content modifications, or feature emphasis. Twitter, for example, modified its onboarding to encourage new users to immediately follow others, demonstrating that Habit Testing is a continual process guiding product evolution.