Cohort analysis

Analysis method that involves segmenting users into groups (cohorts) based on a common event over a given period (e.g., sign-up date, first purchase, first visit), in order to observe how their behavior evolves over time. Unlike cross-sectional analysis, which treats all users uniformly, cohort analysis highlights behavioral differences based on history, entry context, or profile.

🎯 Objectives:

• Track the performance, retention, or engagement of a specific group of users over days, weeks, or months,
• Compare the effects of changes (design, message, offer) across different generations of users,
• Identify hidden behavioral trends, which are only visible through dynamic analysis (e.g., drop-off after 3 days for a specific cohort).

📌 Use cases in CRO:

• Analyze conversion rates over time following an A/B test: does the cohort exposed to variation B have better retention or long-term value?
• Assess the impact of a new onboarding funnel: are users who signed up after the change more engaged?
• Track the customer value (CLV) of cohorts acquired through different channels or campaigns,
• Understand at what point users drop off in the journey (e.g., at the 2nd visit, at the time of purchase…),
• Identify high-potential cohorts for personalization or nurturing actions.