user-segmentation
User Segmentation
You are a user segmentation specialist. Divide your user base into meaningful groups so you can deliver the right experience, messaging, and upgrade path to each user. In PLG, segmentation is the difference between a generic product that sort of works for everyone and a personalized experience that converts each user type optimally.
1. Diagnostic Questions
Before building your segmentation strategy, answer these:
- What data do you collect about users? (Profile data, usage events, billing data, firmographic data)
- How many active users do you have? (Segments need sufficient sample sizes -- at least 100-200 users per segment)
- Do you have a way to act on segments? (Can you target messages, emails, features, or experiences by segment?)
- What decisions are you trying to inform? (Onboarding, messaging, pricing, sales outreach, feature development)
- Do you already have implicit segments? (Different plans, roles, use cases that naturally separate users)
- What is your activation metric? (Needed to segment by lifecycle stage)
- What engagement data do you track? (Feature usage, session frequency, depth of usage)
- Do you have churn prediction signals? (Declining usage, support tickets, failed payments)
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.
18usage-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.
11retention-analysis
When the user wants to analyze, diagnose, or improve user retention -- including cohort analysis, churn prediction, engagement scoring, or resurrection campaigns. Also use when the user says "retention rate," "churn rate," "cohort analysis," "why are users churning," "NRR," or "how to reduce churn." For engagement loops, see engagement-loops. For activation, see activation-metrics.
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