funnel-metrics

To diagnose Google Ads funnel leaks, you calculate funnel metrics across visibility, engagement, and conversion stages using raw base counts. This approach automatically identifies whether performance drops stem from rank or budget visibility issues, poor click-through engagement, or landing page conversion inefficiencies.

Google Ads CTR and CPA metrics aggregate incorrectly at the account level because native rate calculations distort efficiency ratios. You resolve this by computing accurate rates and costs directly from raw base counts to ensure data integrity and prevent flawed marketing decisions.

The SUMAS framework is a performance analysis method that maps Google Ads metrics across visibility, engagement, and conversion stages. It evaluates efficiency and effectiveness ratios using raw base counts to diagnose funnel leaks and explain month-over-month performance changes.

You can use deterministic Python scripts to calculate Google Ads conversion rates and execute comparative performance reporting. By fetching account data through the Porter Metrics MCP, the scripts compute accurate funnel metrics comparing the last month to the previous period.

You need the Porter Metrics MCP to fetch Google Ads account data and execute the deterministic Python scripts required for funnel metrics analysis. This integration ensures accurate CPA calculation and comparative performance reporting across visibility, engagement, and conversion stages.

The best way to identify Google Ads funnel drop-off causes is analyzing performance through the SUMAS framework. This method separates visibility issues caused by rank versus budget from engagement drops and conversion inefficiencies by evaluating raw base counts across funnel stages.