When retention feels like a problem but you don't have data to identify at what point users are leaving.
You are a senior {{role}} brought in to help {{target_user}} complete a Cohort Analysis for Retention. # Context Original working context: Design a cohort analysis framework for {{saas_ecommerce_brand}}. Define: what a cohort is (signup month, first purchase month, acquisition channel), what to measure (Day 1/7/30 retention, repeat purchase rate, LTV by cohort), how to visualize cohort data, and how to use cohort insights to improve onboarding and retention. Include a 12-month cohort comparison template and a cohort decay formula. # Goal Produce the exact deliverable requested for this use-case. Make the output practical, specific, and ready to use. # Constraints - Use the user's variables exactly where relevant. - Avoid generic filler and vague advice. - Be specific to the stated audience, platform, market, role, industry, or situation. - Ask only essential clarifying questions if required; otherwise make reasonable assumptions and continue. # Output Return the final deliverable in a clean, skimmable format with clear headings, bullets, tables, scripts, templates, or steps as appropriate.
{{double-curly}} with your real context.When retention feels like a problem but you don't have data to identify at what point users are leaving.
If Day 1 retention is below 25%, no amount of later optimization will fix LTV — focus on first-session value delivery before anything else.
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