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cohort-analysis

Model user cohorts to quantify retention and lifetime value in dbt workflows.

1|1|Updated Feb 27, 2026
Search Tags:#analytics#dbt#retention#cohort-analysis#ltv#cohort
One-click install
npx skills add https://github.com/nrakow/ae-skills-dev --skill cohort-analysis-nrakow
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cohort-analysis
Source: https://github.com/nrakow/ae-skills-dev/tree/main/skills/cohort-analysis
Command: npx skills add https://github.com/nrakow/ae-skills-dev --skill cohort-analysis-nrakow

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Design and build cohort retention and lifetime value models to understand user behavior over time and inform product decisions.

Core Features & Use Cases

  • Cohort-based retention analysis including classic triangle patterns to show how retention decays over time.
  • LTV and revenue by acquisition cohort to evaluate long-term value across channels and segments.
  • Day-N retention measurements (e.g., Day 1, Day 7, Day 14, Day 30) and rolling retention to monitor short- and mid-term engagement.
  • Guidance for validating results with dbt runs and tests to ensure model correctness.

Quick Start

Run a cohort analysis workflow to generate fct_cohort_retention, fct_cohort_ltv, and fct_day_n_retention in your dbt project.

Frequently Asked Questions about cohort-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I measure user retention and LTV by acquisition cohort in dbt?▼

You can measure user retention and LTV by applying this Skill to build dbt models like fct_cohort_retention and fct_cohort_ltv, grouping users into signup cohorts to quantify behavior over time.

What is the best way to calculate Day-N retention for short-term engagement tracking?▼

Calculating Day-N retention is best done by generating the fct_day_n_retention model in dbt, which measures specific timeframes like Day 1, Day 7, and Day 30 to monitor rolling user engagement.

How do I build a retention triangle to visualize cohort decay over time?▼

To build a retention triangle showing how retention decays, use the Skill to construct the fct_cohort_retention model, organizing acquisition cohorts against time elapsed to visualize drop-off patterns.

Do I need a dbt-enabled workflow to model lifetime value and cohort retention?▼

Yes, a dbt-enabled workflow is required. The Skill generates SQL definitions and models with frontmatter metadata, relying on dbt run and test steps to validate results and ensure model correctness.

Can I evaluate long-term revenue across different channels using cohort analysis?▼

Yes, you can evaluate long-term value across channels by building the fct_cohort_ltv model, which segments lifetime value and revenue metrics by acquisition cohort to inform product decisions.

Why should I run dbt tests after generating cohort retention and LTV models?▼

Running dbt tests is necessary to validate results and ensure model correctness. The Skill includes guidance to verify outputs using dbt run and test steps, confirming your retention and LTV calculations are accurate.

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