via HubSpot Marketing

HubSpot Outlines How Marketers Can Benchmark AI Search Visibility

HubSpot recommends tracking citations and share of voice alongside traditional search metrics to assess AI search performance.

Marketers are struggling to determine how well their brands appear in AI-generated answers, according to HubSpot’s State of AEO 2026 report. Measuring success was the most frequently cited answer engine optimization challenge among B2B marketers, at 23%. Among B2C marketers, 26% named measurement as a challenge, second to understanding how AEO works, which was cited by 29%.

Answer engine optimization focuses on visibility within synthesized responses rather than placement alone on a conventional search results page. HubSpot says established search measures remain useful, but they do not answer every question marketers face. Google Search Console clicks and impressions, for example, do not show whether an answer engine names a brand or cites its content, or how that visibility compares with competitors.

HubSpot distinguishes between two forms of appearance in an AI answer. A mention identifies a brand without linking to a source. A citation provides an attributed source reference or URL; for brand-level measurement in its guide, HubSpot defines this as a reference or link from the brand’s own domain. The distinction matters because a brand can be named in an answer without its own content being cited.

AI-generated search features also add context to conventional traffic measures. Ahrefs found that the presence of a Google AI Overview was correlated with a 58% lower average click-through rate for the top-ranking page in December 2025. That finding describes a correlation, rather than establishing that the AI feature caused the difference. It also underscores why a search ranking and the clicks it receives should not be treated as the same measure.

For industry comparisons, HubSpot’s guide recommends moving beyond isolated prompt checks toward a repeatable benchmark. It identifies citation rate and share of voice as measures to track, alongside normalization across answer engines and prompts. Comparing results at the platform level can help teams assess performance on a more consistent basis and explain the findings to leadership.

What this means for marketers

Keep traditional search reporting, but add a separate view of AI-answer visibility. Distinguish brand mentions from citations to your own domain, compare performance with competitors and revisit the same benchmark over time. Presenting those measures together can give leadership a clearer picture than rankings, impressions or website visits alone.

Source: HubSpot Marketing — https://blog.hubspot.com/marketing/ai-search-industry-benchmarks

This is an original summary published for informational purposes; all rights to the underlying reporting belong to the source.

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