PostHog Feature Adoption Intelligence
AI-powered weekly feature adoption analysis — adoption rates, usage frequency, retention, growth velocity, and power user ratios scored across 5 dimensions with adoption curve classification.
Analyzes PostHog feature usage weekly to compute per-feature Health Scores across 5 dimensions. Classifies features by adoption curve shape (S-curve, plateau, decline). Identifies underperforming features, power user patterns, and retention cliffs. Generates Notion weekly feature report and Slack product insights digest. 24-node n8n workflow with Monday scheduler. Blueprint Quality Standard (BQS) 12/12 certified. This came from a PM who shipped a feature, checked adoption after 30 days, and found 8% uptake with no data on why. The agent tracks adoption curves, identifies friction points, and segments adoption by user cohort.
Last updated March 18, 2026
Product teams collect feedback from 5-10 channels — support tickets, feature requests, NPS comments, usage analytics, user interviews. Synthesizing across channels is a manual process that happens quarterly at best. Automated product intelligence aggregates signals continuously, surfacing adoption patterns and feedback themes as they emerge.
Four Agents. Weekly Adoption Analysis. Feature Health Scoring.
Step 1 — The Fetcher
Code-only
Queries PostHog API for feature flag usage, event data, and user properties across the configurable lookback window. Retrieves adoption rates, usage frequency, retention cohorts, and user segment breakdowns per feature.
Step 2 — The Assembler
Code-only
What does The Assembler actually decide? Computes five Feature Health Score (FHS) dimensions per feature: adoption rate (unique users / total active users), usage frequency (events per adopted user), retention (week-over-week retained users), growth velocity (new adopters trend), and power user ratio (top 10% usage share).
Step 3 — The Analyst
Tier 2 Classification
This step exists because raw data alone is not enough. Scores each dimension 1-10, computes composite FHS, classifies each feature on the adoption curve: EARLY ADOPTER, GROWING, MATURE, DECLINING, or STALLED. Identifies features needing intervention and generates prioritized recommendations.
Step 4 — The Formatter
Tier 3 Creative
Without this step, upstream analysis sits idle. Generates a Notion feature adoption dashboard with per-feature health cards and adoption curve classification, plus a Slack digest with features needing attention and top recommendations.Synthetic IDs passed the pipeline logic but failed on the CRM write. We wasted 2 hours debugging the wrong service.
That's the full pipeline. Here's what it intentionally does NOT do — and why those boundaries exist.
What It Does NOT Do
Does not modify feature flags in PostHog — this is a read-only analysis tool
Does not replace PostHog dashboards — it provides weekly synthesized intelligence, not real-time metrics
Does not work with non-PostHog analytics tools — this is PostHog-specific
Does not A/B test features — it analyzes adoption patterns after launch
Does not guarantee feature success — it identifies adoption patterns that teams must act on
With those boundaries clear, here's everything that ships when you purchase.
The Complete Customer Success Bundle
9 files.
The technical specifications below are ITP-measured, not estimated.
Tested. Measured. Documented.
Weekly 5-dimension feature adoption analysis with adoption curve classification and dual-channel delivery (Notion feature dashboard + Slack digest with features needing attention).
Tested on n8n v2.7.5, March 2026
PostHog Feature Adoption Intelligence v1.0.0──────────────────────────────────────────Nodes: 24 main + 3 scheduler (27 total)Agents: 4 (Fetcher, Assembler, Analyst, Formatter)LLM Calls: 2 per run (Analyst + Formatter)Model: Sonnet 4.6 (SINGLE-MODEL)Trigger: Schedule (weekly Monday 9:00 UTC) + WebhookPattern: BATCH (weekly feature analysis)Tool A: PostHog API — feature flags + eventsTool B: Notion (httpHeaderAuth) — feature adoption dashboardTool C: Slack (httpHeaderAuth) — digest with features needing attentionITP: 8/8 records, 14/14 milestonesBQS: 12/12 PASSCost: $0.03–$0.10 per run
What You'll Need
Platform
n8n 2.7.5+
Est. Monthly API Cost
~$0.03-0.10 per weekly run + PostHog subscription.
Credentials Required
- ▪Anthropic API
- ▪PostHog API Key
- ▪Slack (Bot Token, httpHeaderAuth Bearer)
- ▪Notion (httpHeaderAuth Bearer)
Services
- ▪PostHog account with feature flags or custom events
- ▪Anthropic API key
- ▪Notion workspace
- ▪Slack workspace (Bot Token with chat:write)
Setup Track
Quick Start
~15 min
All credentials live, n8n running
Full Setup
1–2 hrs
Needs API config + tables
From Scratch
2–4 hrs
No n8n, no credentials
PostHog Feature Adoption Intelligence v1.0.0
$249
one-time purchase
What you get:
- ✓24-node main workflow + 3-node scheduler
- ✓Weekly feature adoption analysis from PostHog event and flag data
- ✓5-dimension Feature Health Score (FHS): adoption rate, usage frequency, retention, growth velocity, power user ratio
- ✓FHS 1-10 per dimension with adoption curve classification (EARLY ADOPTER/GROWING/MATURE/DECLINING/STALLED)
- ✓Per-feature health cards with dimension breakdowns and trend indicators
- ✓Adoption curve lifecycle classification for product roadmap decisions
- ✓Power user ratio analysis identifying features with concentrated usage
- ✓Growth velocity tracking for new feature launch monitoring
- ✓Retention cohort analysis showing week-over-week stickiness
- ✓Notion feature adoption dashboard with per-feature health cards
- ✓Slack digest with features needing attention and top recommendations
- ✓Configurable: feature list, lookback window, adoption thresholds
- ✓Full technical documentation + system prompts
Frequently Asked Questions
What are the adoption curve classifications?+
EARLY ADOPTER: low adoption but growing fast. GROWING: increasing adoption with healthy retention. MATURE: high adoption, stable usage.
What PostHog data does it need?+
Feature flag usage data and custom events associated with features. The Fetcher uses PostHog API to query event counts, unique users, and user properties. Feature flags must be set up in PostHog, or you can configure custom event names that map to features.
How does it differ from PostHog built-in analytics?+
PostHog shows individual feature metrics. This product scores features across 5 standardized dimensions, classifies lifecycle stage, compares features against each other, and generates prioritized recommendations. It is a weekly synthesized brief, not a dashboard you have to interpret.
Is there a refund policy?+
All sales are final after download. Review the Blueprint Dependency Matrix and prerequisites before purchase. Questions?
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