retention-analysis
Retention Analysis
You are a retention analyst. Measure, diagnose, and improve user or customer retention.
Diagnostic Questions
Before analyzing retention, ask the user:
- What is your current D1 / D7 / D30 / D90 retention rate? (If unknown, that's step one)
- Do you have cohort analysis set up?
- What does your retention curve look like? (Flattening, declining to zero, or smile curve)
- What is your product's natural usage frequency? (Daily / Weekly / Monthly)
- What is your current churn rate (monthly or annual)?
- Do you know why users churn? (Exit surveys, cancellation flow data, support tickets)
- Have you identified behavioral differences between retained and churned users?
- What is your current NRR (Net Revenue Retention)?
- Do you have re-engagement campaigns (emails, push notifications) for inactive users?
- Is your activation rate strong, or could poor activation be driving churn?
More from skenetechnologies/plg-skills
product-onboarding
When the user wants to design or improve new user onboarding -- including product tours, checklists, empty states, welcome flows, or progressive disclosure. Also use when the user says "first-run experience," "onboarding flow," "getting started," "stalled users," or "onboarding drop-off." For activation metrics, see activation-metrics. For signup optimization, see signup-flow-cro.
25growth-experimentation
When the user wants to design, prioritize, or analyze growth experiments -- including A/B tests, hypothesis frameworks, ICE/RICE scoring, or growth sprints. Also use when the user says "A/B test," "experiment design," "growth sprint," "experiment prioritization," or "statistical significance." For analytics setup, see product-analytics. For growth modeling, see growth-modeling.
20viral-loops
When the user wants to design product-driven viral growth -- including invite mechanics, collaboration loops, embedding loops, or network effects. Also use when the user says "K-factor," "viral coefficient," "invite flow," "sharing mechanics," or "network effects." For structured referral programs, see referral-program. For growth loop design, see growth-loops.
19trial-optimization
When the user wants to optimize free trial conversion -- including trial length, trial type selection, expiry flows, or trial email sequences. Also use when the user says "trial conversion," "trial length," "trial design," "opt-in vs opt-out trial," or "trial-to-paid." For activation, see activation-metrics. For feature gating, see feature-gating.
17usage-based-pricing
When the user wants to design or implement usage-based, consumption, or metered pricing -- including credit systems, overage handling, or billing infrastructure. Also use when the user says "pay per use," "metered billing," "credit system," "usage pricing," or "consumption pricing." For broader pricing strategy, see pricing-strategy. For expansion, see expansion-revenue.
11activation-metrics
When the user wants to define, measure, or optimize user activation -- including identifying the aha moment, measuring time-to-value, or building an activation funnel. Also use when the user says "activation rate," "aha moment," "setup moment," "habit moment," "time to value," or "how do I measure activation." For onboarding design, see product-onboarding. For retention, see retention-analysis.
11