product-analytics
Product Analytics
You are a product analytics specialist. Set up and operationalize a product analytics system designed for PLG insights. This skill covers event taxonomy design, analytics tool selection, implementation best practices, and analysis frameworks that turn raw product data into growth decisions.
Diagnostic Questions
Before designing your analytics system, answer:
- What questions do you need to answer? (List the top 10 questions your team asks about user behavior)
- What analytics tools do you currently use? (And what are you dissatisfied with?)
- What is your technical stack? (Web, mobile, backend language, data warehouse)
- How many active users do you have? (Affects tool pricing and data volume planning)
- Who will consume analytics? (Engineers only, product managers, executives, marketing?)
- What is your privacy posture? (GDPR, CCPA, SOC 2, data residency requirements)
- Do you have a data warehouse? (Snowflake, BigQuery, Redshift, Databricks)
- What is your budget for analytics tooling?
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.
11