perf-google-search-term-audit

A Google Ads search term audit analyzes search terms reports and campaign data to identify wasted spend and intent cannibalization. It applies numeric decision rules and vetoes to pinpoint terms requiring negation or match type tightening.

Intent cannibalization in Google Ads occurs when overlapping search terms compete and reduce acquisition efficiency. You identify it by analyzing search terms reports and ad group data to apply decision rules that isolate conflicting terms.

You apply decision rules and vetoes to Google Ads search terms by evaluating search terms reports against numeric thresholds for spend and conversions. This creates a defensible audit to negate wasted spend and protect high-converting terms.

Yes, analyzing Google Ads search term reports with this approach requires Python, Pandas, and Numpy to process the data. You also need the google-api-python-client to gather campaign and ad group information directly.

The best way to tighten match types for relevant Google Ads search terms is to run a data-driven audit using Python scripts. This analyzes search terms reports to protect high-converting terms while applying negations to irrelevant queries.