Your B2B buyers are already comparing your offer on ChatGPT.

Beyond Mentions audits AI-mediated buying criteria: the elements that LLMs (ChatGPT, Claude, Gemini, Perplexity, DeepSeek) recommend to your prospects as they prepare a B2B buying decision. The point isn't only whether you get cited. It's analyzing which criteria structure the comparison grid, which proof gets reused or ignored, which competitors set the category standards, and whether your offer makes the shortlist with the right arguments.

A standard GEO audit measures visibility: are you mentioned, from which sources, how often. That's a presence metric. Beyond Mentions adds a decision layer: not just the mention, but the influence on the decision. In practice, you can be cited in 80% of AI answers while still being compared against alternatives that don't meet the same level of rigor. That category confusion is what we measure and correct.

Beyond Mentions works alongside your existing GEO or SEO agency. We operate on the cognitive and decision layer, complementing your standard visibility work.

Beyond Mentions works with B2B organizations whose buying decisions are built over several months, several stakeholders, and several technical criteria. Our methodology is built for markets where AI simplifying the comparison grid can cost more than a poorly scoped tender.

We focus on four main sector families:

• Industry & manufacturing: transformation, chemicals, mechanical engineering, energy, environmental, sustainable production, tier 1/2 manufacturers, PPE, aerospace. Supplier qualification criteria, process certifications, and safety standards must stay visible in AI answers.
• Tech & deep tech: microelectronics, AI, B2B SaaS publishers, IoT, cybersecurity, infrastructure tech. LLMs often confuse enterprise architectures with consumer-grade tools. Sovereignty, SLA, and compliance need to be indexed as prerequisites.
• B2B technical services: engineering firms, industrial service providers, maintenance, certification bodies. Proof of expertise and sector references structure the decision and must surface in the comparison grid.
• Regulated sciences & innovation: medtech (MDR, IVDR), pharma, REACH chemicals, biotech, deep tech startups, scale-ups, research labs. The regulatory environment moves faster than the sources LLMs rely on, and an outdated framework in the answers can under-specify the buying decision.

We work in English and French. If your market doesn't fall exactly into one of these four families, a 30-minute first call is enough to check the fit.

How quickly your corrected content surfaces in AI answers depends on several factors we don't fully control: search engine indexing delays, the crawl budget allocated to your domain, how often LLMs consult the sources that cover you, the depth of your internal linking, and the authority of your pages.

Some of the pages we've worked on have been picked up by ChatGPT or Perplexity in under a week. We never promise that timeline: it depends on the context of your site and your market. Plan for a horizon of several weeks to several months to see a durable shift in the criteria grid AI proposes to your prospects.

A full audit, correction, and re-measurement cycle typically spans 3 to 4 months. At that point, we quantify the change against the indicators we've defined together: spontaneous mention rate of your technical criteria, presence in the AI-generated shortlist, reduction in category confusion, repositioning of competitors in the comparison grid.

One caveat: results don't depend on the audit alone. As with SEO, execution quality of the recommendations determines the trajectory. A brand that publishes its proof in a structured way, diversifies its sources of authority, and keeps a consistent publishing cadence gets stronger and more durable results than a brand that executes partially. We measure your baseline before and after to make progress visible.

It's a fair question, so let's address it head-on. A Beyond Mentions audit covers TOFU and the criteria-driven part of MOFU: the zone where AI frames the decision grid before any brand is named. Brand citation monitoring tools, by contrast, focus on comparison-stage MOFU and BOFU, where your brand already appears in a scoped comparison. They measure mentions, not the criteria that structure the decision upstream. That's exactly where Beyond Mentions operates.

The ROI of upstream work isn't measured in deals signed the following week, but in leading indicators of presence and influence in the decision grid. Same logic as SEO on strategic queries: TOFU and criteria-driven MOFU are justified by semantic market share, positions on key queries, click-through rates, and qualified traffic trends. In the AI space, the measurement grammar is equivalent, but it applies to LLM answers rather than search engine result pages.

At every stage of the buyer journey, and for each persona that weighs on the decision, we track:

• The number of key criteria captured by your company in LLM answers, vs. criteria ignored or attributed to a competitor.
• The evolution of authority sources structuring the answers in your market: which ones rise, which ones cite you, which ones disappear.
• The presence rate of your industrial proof (certifications, standards, cases, matrices) in simulated RFPs the LLMs generate from a buyer brief.

The link with your revenue isn't immediate. But without these indicators, your market happens without you: AI-equipped buyers pre-scope their consultations with grids where your differentiators don't exist, and the decision plays out before the first sales call.