conversion-path-analysis git:20260908.cc021baA

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---
name: conversion-path-analysis
description: Maps out how users move through your funnel from first ad click to conversion. Identifies where the biggest drop-offs happen, which campaigns contribute most at each stage, and how long the typical conversion path takes across different audience segments. Platform: Google and Meta.
metadata:
  platform: Google and Meta
---

# 16/ Conversion Path Analysis — Google + Meta

## What it does
Maps out how users move through your funnel from first ad click to conversion. Identifies where the biggest drop-offs happen, which campaigns contribute most at each stage, and how long the typical conversion path takes across different audience segments.

## How it works
Claude analyzes your conversion data, assisted conversions, and multi-touch paths to show the full journey. It looks at first-touch vs last-touch attribution, identifies common paths (e.g., Meta prospecting → Google brand → conversion), and flags where users are falling out of the funnel at higher-than-expected rates.

## Practical example
Your ecommerce account shows that 62% of conversions involve 2+ touchpoints. The most common path is Meta prospecting ad → Google branded search → purchase. But Claude also discovers that users who see a Meta retargeting ad between those two steps convert at 3.2x the rate. Meanwhile, users who click PMax ads rarely convert on the first visit and almost never return — suggesting PMax is driving low-intent traffic. Claude recommends increasing retargeting budget for Meta-sourced traffic and re-evaluating PMax targeting.

## What you get back
- Most common conversion paths ranked by volume and conversion rate
- Average time to conversion by path and audience segment
- Drop-off points in the funnel with estimated revenue impact
- Campaign-level contribution at each funnel stage (awareness, consideration, conversion)
- Recommendations for budget and targeting adjustments based on path analysis

## When to use it
- When attribution feels murky and you need to understand the actual user journey
- Before making budget cuts to understand which "low-performing" campaigns assist conversions elsewhere
- When conversion lag is long (B2B, high-ticket ecommerce) and last-click data misleads
- During multi-channel strategy reviews

## Data access (Ryze MCP)

This skill works best with live account data. Connect the free Ryze MCP once and Claude reads your Google Ads, Meta Ads, GA4 and Search Console directly:

- claude.ai / Claude Desktop: Settings → Connectors → Add custom connector → `https://connector.get-ryze.ai/mcp`
- Claude Code: `claude mcp add ryze --transport http https://connector.get-ryze.ai/mcp`
- Cursor: Settings → MCP → add the same URL

Setup guide: https://www.get-ryze.ai/how-to-connect-claude-to-google-meta-ads-mcp