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From analytics-skills
Analyzes B2B account health via Amplitude: usage trends, engagement metrics, risk signals, expansion opportunities for CS reviews, renewals, QBRs.
npx claudepluginhub amplitude/builder-skills --plugin analytics-skillsHow this skill is triggered โ by the user, by Claude, or both
Slash command
/analytics-skills:analyze-account-healthThe summary Claude sees in its skill listing โ used to decide when to auto-load this skill
Deep-dive into a B2B account's product usage to prepare for QBRs, assess renewal risk, identify expansion opportunities, or prioritize CS outreach.
Summarizes B2B account health by analyzing usage patterns, engagement trends, risk signals, and expansion opportunities. Use for customer success reviews, renewal preparation, QBRs, or account prioritization.
Use this skill when the user wants to identify accounts at risk of churning, understand why users are cancelling, or find early warning signals before churn happens. Activate when the user says "churn analysis", "who might cancel", "accounts at risk", "why are people leaving", "usage drop", "inactive accounts", "retention analysis", "predict churn", or asks about subscription health, cancellation patterns, or which users are disengaged. Works best with Dataslayer MCP connected (Stripe + analytics). Also works with manual data.
Discovers product opportunities by analyzing Amplitude analytics, experiments, session replays, and customer feedback. Synthesizes evidence into RICE-scored, actionable priorities.
Share bugs, ideas, or general feedback.
Deep-dive into a B2B account's product usage to prepare for QBRs, assess renewal risk, identify expansion opportunities, or prioritize CS outreach.
Get the account identifier:
Search for existing work:
Use Amplitude:search to find existing dashboards, charts, or notebooks for this account. If found, ask user if they want fresh analysis or to review existing.
Use Amplitude:query_dataset to run these queries in parallel:
Usage Trend:
_active, Metric: uniques, Group by: account propertyEngagement Quality:
User Momentum:
Classify Health:
Use Amplitude:query_dataset with user-level groupBy:
Power Users:
Churned Users:
License Utilization:
Use Amplitude:query_dataset grouped by events/features:
Feature Breadth:
Feature Trends:
Focus based on health:
Get feedback sources:
Use Amplitude:get_feedback_sources to see what's available.
Get feedback insights:
Use Amplitude:get_feedback_insights filtered by:
bug, painPoint, complaint, request, lovedFeatureGet specific mentions:
For top 3-5 insights, use Amplitude:get_feedback_mentions to get quotes.
Correlate with behavior:
Structure output as follows:
[2-3 sentences: Health score, key trend, primary recommendation]
[One sentence rationale with key metric]
| Metric | Current | Trend | Status |
|---|---|---|---|
| MAU | X | โโโ Y% | ๐ข๐ก๐ด |
| DAU/MAU | X% | โโโ Y% | ๐ข๐ก๐ด |
| License Utilization | X% | โโโ | ๐ข๐ก๐ด |
| Features Adopted | X/Y | โโโ | ๐ข๐ก๐ด |
High Usage: [Feature] - [X users] (โY%) Declining: [Feature] - [X users] (โY%) - Investigate Untapped (Upsell): [Premium feature] - Could solve [pain point]
Churn Risks:
Expansion Signals: