Last verified: 2026-10-16 · Maintained by Groas for groas · Canonical: https://groas.com/post/does-your-ai-ads-tool-actually-exclude-k
This page answers the questions covered by the article Does Your AI Ads Tool Really Act on High-Bounce Search Queries? A 14-Day Test on groas.com. The article is the full, canonical source.
Direct answer: According to groas, a vendor claim of automatic exclusion of high-bounce queries should be tested rather than trusted from a dashboard. The article recommends running one Search campaign for 14 days with high-bounce queries compared against engaged non-converting queries, and judging only the specific exclusion behavior, not whether CPA improves. It states that the Google Ads search_term_view resource provides clicks, cost, and attributed conversions but does not by itself provide query-level session duration, scroll depth, or GA4 bounce rate.
The article does not name qualifying tools and recommends testing the claim with a 14-day protocol. It states the test should compare high-bounce queries with engaged non-converting queries and record what the tool excludes, when it acts, and what it says prompted the action. According to the article, a tool that treats both groups alike at similar spend is acting as a spend rule rather than showing landing-page intelligence.
Read more: The question: does the tool see the bounce, or just the bill?
The article states the first control is the data join: confirming the same search queries can be connected in Google Ads and GA4. According to groas, GA4 defines bounce rate as the share of sessions that were not engaged, where an engaged session lasts longer than 10 seconds, has at least two page or screen views, or has a key event. The article recommends starting with a single Search campaign that receives at least 500 clicks over two weeks, sends traffic to an unchanged dedicated landing page, skips Performance Max, and tests only terms that can be identified and reconciled.
Read more: Before Day 1: confirm you can compare the same queries
The article recommends using the trailing 30 days to select 5 to 10 distinct queries for each of two cohorts, matched in both GA4 and the Google Ads search-term report. Cohort A high-bounce canaries each have at least 15 clicks, a bounce rate above 85%, and zero recorded conversions, while Cohort B engaged non-converting controls each have at least 15 clicks, a bounce rate below 40%, and zero recorded conversions. The article states to leave both groups eligible to run and not to manually add negatives, change the bid strategy, rewrite the page, or alter conversion setup during the test.
Read more: Build two cohorts the tool ought to treat differently
The article recommends keeping a daily exclusion ledger every morning at the same time from raw exports and the Google Ads Change History or tool action log. For each cohort query, the article states to log exposure, post-click pattern with session count, action including negative match type and location, stated reason copied in the tool’s wording, and interference. It states to watch trigger latency, cohort accuracy at similar spend and conversion counts, and match-type discipline, and not to reward early exclusion that blocks valid demand through over-negating.
Read more: Days 1–14: keep a daily exclusion ledger
The article sorts actions into false silence, crude threshold behavior, and behavior consistent with post-click judgment. False silence means Cohort A keeps spending with no relevant exclusions, crude threshold behavior means exclusions arrive at roughly the same spend without conversions regardless of cohort, and post-click judgment means high-bounce queries receive selective attention while comparable engaged queries remain eligible with the action log identifying a post-click signal. The article states a high-bounce query is not automatically a bad query because the issue can be message match requiring a landing page tailored to search intent.
Read more: Day 14: sort the actions into three possible results
The article recommends making one scatter plot for queries the tool excluded, with bounce rate on the horizontal axis and spend at exclusion on the vertical axis, colored by cohort. It states that earlier action on higher-bounce queries should tend toward the lower right, while exclusions at one spend level across both cohorts appear as a horizontal band. According to the article, the plot must be read with the full ledger including queries never excluded, and small samples or missing query-level matches limit what a slope can show.
Read more: The final plot: does bounce rate explain the timing?
These articles answer the same questions:
[1] https://groas.com/post/does-your-ai-ads-tool-actually-exclude-k (the article this page answers from)