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Analyzes user conversion funnels to identify where users drop off and why. Calculates conversion rates between steps, compares funnels across segments, and recommends optimizations. Supports funnels for onboarding, checkout, feature adoption, and custom user journeys.
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SOC 職業分類に基づく
Helps design statistically rigorous A/B tests for marketing campaigns, landing pages, and product features. Calculates required sample sizes, defines success metrics, sets up test variants, and analyzes results with confidence intervals. Prevents common testing mistakes like peeking and underpowered tests.
Detects abandoned carts and triggers recovery workflows including email sequences, discount offers, and retargeting campaigns. Analyzes cart abandonment patterns to identify friction points in the checkout flow. Tracks recovery rate and revenue recaptured.
Automates the bank reconciliation process by matching transactions from bank feeds with accounting records in QuickBooks or Xero. Identifies unmatched transactions, suggests matches for review, and flags discrepancies. Reduces manual reconciliation time and improves financial accuracy.
Creates multi-channel marketing campaigns with automated workflows. Designs email sequences, social media schedules, and ad targeting rules. Tracks campaign performance across channels and optimizes based on engagement metrics and conversion data.
Creates intelligent chatbot workflows that handle common customer queries, collect information, and route complex issues to human agents. Designs conversation flows, configures response templates, and tracks chatbot performance metrics like resolution rate and handoff rate.
Performs cohort analysis to understand user retention, engagement, and revenue patterns over time. Groups users by signup date, acquisition channel, or plan type and tracks how their behavior changes week over week. Identifies which cohorts retain best and what drives long-term engagement.
| name | funnel-analysis |
| displayName | Funnel Analysis |
| tagline | Analyze conversion funnels to identify drop-off points and optimize user journeys. |
| description | Analyzes user conversion funnels to identify where users drop off and why. Calculates conversion rates between steps, compares funnels across segments, and recommends optimizations. Supports funnels for onboarding, checkout, feature adoption, and custom user journeys. |
| department | ["Product","Data & Analytics","Growth"] |
| use_cases | ["Conversion Optimization","User Journey Analysis","Growth Analytics"] |
| tools_required | ["Mixpanel MCP","Google Analytics MCP"] |
| agents_compatible | ["Claude / Claude Code","Cursor","Windsurf","ChatGPT","Any MCP-compatible agent"] |
| author | Webrix |
| verified | true |
| updatedAt | "2026-05-08T00:00:00.000Z" |
| version | 1.0.0 |
| exampleInput | Analyze the onboarding funnel for new users last month. Steps: signup -> verify email -> create project -> invite team -> first action. |
| exampleOutput | Funnel Analysis — Onboarding (April 2026) CONVERSION FUNNEL Signup: 1,200 users (100%) Verify Email: 1,020 users (85%) — 15% drop Create Project: 714 users (59%) — 30% drop ⚠️ Invite Team: 428 users (36%) — 40% drop ⚠️ First Action: 342 users (29%) — 20% drop OVERALL CONVERSION: 29% (signup to first action) BIGGEST DROP-OFFS 1. Invite Team step: 40% drop — Users skip team invite Recommendation: Make invite optional, show value prop 2. Create Project: 30% drop — Friction in project setup Recommendation: Add project templates, reduce required fields SEGMENT COMPARISON Organic Users: 34% overall conversion Paid Users: 22% overall conversion Referral Users: 41% overall conversion |
Analyze conversion funnels to identify drop-off points and optimize user journeys.
Integrations: Mixpanel, Google Analytics
Identify the sequential steps in the user journey.
Compute step-by-step conversion rates and identify drop-offs.
Compare funnel performance across user segments.
Suggest improvements for the biggest drop-off points.
Deliver:
