Semrush Frames AI Search Strategy Around Four Visibility Layers

A Semrush study of 3,981 brand appearances across ChatGPT, Google AI Overviews, Gemini and Google AI Mode found 62% were citations where the answer never named the brand — the sharpest number in a new Semrush guide that reframes AI search strategy around four diagnostic layers: discoverability, clarity, authority and trust.

The same research showed ChatGPT cited brands in 87% of its appearances but named them in just 20.7%. The guide's central argument follows directly from that gap: citations, mentions and recommendations are different outcomes, and teams that treat them as one metric misread their visibility problem.

A second Semrush study tracked how AI-cited pages differ from pages ranking in Google's top 20. Cited pages scored higher on clear summarization (+32.83%), E-E-A-T signals (+30.64%), Q&A formatting (+25.45%), section structure (+22.91%) and structured data (+21.60%) — here meaning lists, tables and Q&A pairs in visible text, not schema markup.

Why do brand visibility problems get misdiagnosed?

Generating an AI answer takes separate steps — retrieval, source evaluation, synthesis, citation — and a failure at any step keeps a brand out or distorts it. Most teams reach for the same fix anyway: content. Rewriting pages works only when the gap actually sits in the content, the guide says.

The four failure modes are:

• Brand discoverability — AI systems can't reliably access brand information
• Brand clarity — they access it but describe the brand inaccurately
• Brand authority — accurate descriptions, but rare inclusion in comparisons
• Brand trust — considered, but rarely recommended or hedged with caveats

The framework is for triage, the guide stresses, not a set of universal AI ranking factors. Start with discoverability to rule out access problems.

What did fixing clarity look like in practice?

Geertrui Laleman, Senior AI Search Optimization Manager at Semrush, described the company's own case: "AI answers used to describe us as a traditional SEO tool with AI features added on. The mentions were there, they were just describing the wrong company. We didn't fix that by publishing more on our own site. We fixed it by changing how we were described on the third-party pages LLMs cite."

On the technical layer, the guide restates confirmed platform positions: Google says pages must be indexed and snippet-eligible to appear as supporting links in AI Overviews or AI Mode, with no additional schema.org requirements. OpenAI says publishers should allow OAI-SearchBot for ChatGPT Search inclusion. Google has also said it doesn't use llms.txt, and that creating one won't help or hurt Search visibility — Semrush's own framing of llms.txt, schema and MCP Server Cards is that no published evidence shows they increase AI citations.

What should teams actually measure?

The guide points to Semrush's 2025 Reddit tracking as evidence that source influence shifts fast: ChatGPT cited Reddit in close to 60% of responses in early August and around 10% by mid-September, before Reddit stabilized alongside Wikipedia as one of ChatGPT's two most-cited domains by the study's end.

Recommended measurement runs across four dimensions: presence (mention and citation rates, share of voice), representation (factual accuracy, positioning), source influence (recurring cited domains) and business outcome (referrals, leads, conversions). A recommended baseline is 20–25 buyer-decision prompts tracked weekly.

The guide also lists six common mistakes, including publishing pages for every prompt variation, treating crawler activity as visibility, manufacturing third-party consensus, and degrading content for people to please machines.

Looking ahead, Semrush flags agent readiness as the next frontier: answer-ready brands can still fail agents, and as AI systems move from presenting information to completing tasks, corroborated brand information will increasingly decide which businesses the agents choose.

By James Calloway