cohort-analysis
FeaturedSegment customers into cohorts — by acquisition period, channel, first behavior, or revenue tier — and produce a color-coded retention matrix, overlaid retention curves, LTV-by-cohort comparisons with LTV:CAC where cost data exists, best/worst cohort rankings with hypothesized drivers, stabilization-point analysis, and intervention recommendations for underperformers. Analyzes and recommends; it launches nothing. Triggers on "/digital-marketing-pro:cohort-analysis", "are newer customers retaining better than older ones", "which channel produces the highest-LTV customers", "build a retention matrix", "when does our churn stabilize". Pulls customer data from connected CRM and analytics MCPs, reads the brand profile for business-model context, and saves the summary as a campaign-tracker.py insight for trend tracking.
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Quality Score: 92/100
Skill Content
Details
- Author
- indranilbanerjee
- Repository
- indranilbanerjee/digital-marketing-pro
- Created
- 7 months ago
- Last Updated
- 4 days ago
- Language
- Python
- License
- MIT
Integrates with
Bundled in these plugins
Similar Skills
Semantically similar based on skill content — not just same category
cohort-analysis
Segment customers into cohorts — by acquisition period, channel, first behavior, or revenue tier — and produce a color-coded retention matrix, overlaid retention curves, LTV-by-cohort comparisons with LTV:CAC where cost data exists, best/worst cohort rankings with hypothesized drivers, stabilization-point analysis, and intervention recommendations for underperformers. Analyzes and recommends; it launches nothing. Triggers on "/digital-marketing-pro:cohort-analysis", "are newer customers retaining better than older ones", "which channel produces the highest-LTV customers", "build a retention matrix", "when does our churn stabilize". Pulls customer data from connected CRM and analytics MCPs, reads the brand profile for business-model context, and saves the summary as a campaign-tracker.py insight for trend tracking.
cohort-analysis
Builds and interprets a cohort retention table — defines the cohort and return event, reads where and when users drop off, compares cohorts over time, and converts the retention curve into a hypothesis and an action. Use when you say "build a cohort table," "why is retention dropping," "are newer signups sticking better," "where do users churn," or "what happened to the March cohort."
cohort-analysis
Groups customers by acquisition period and tracks a retention or revenue metric across the periods that follow, returned as a cohort table. Use when the user wants to know whether newer customers are performing better or worse than older ones, not just a single blended average. Boundary: this skill builds the cohort table itself. For the dashboard that displays it alongside other KPIs, use `kpi-dashboard`. For comparing the result against outside industry numbers, use `benchmark-analysis`.