AI-powered search is recommending your competitors to customers who should be finding you. Our diagnostic reveals exactly where you're losing visibility and how to improve it.
45-day analysis + prioritized action plan
We'll contact you within 24 hours
A complete picture of your AI search visibility
Full analysis across Google AI, ChatGPT, Claude, and Gemini showing exactly where your brand appears (or doesn't).
See which competitors are being recommended instead of you and understand why they're winning.
Quantify the revenue you're losing to AI search invisibility with data-backed projections.
Prioritized roadmap of exactly what to prioritise, with expected impact for each initiative.
Four phases. One outcome. You walk away knowing exactly where AI search is costing you and what to do about it.
We run 50 to 100 queries across ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews. Each query is tested multiple times per platform, so we capture the variance in how AI models actually recommend. Output: your share of memory across priority query sets, platform-by-platform breakdown, and the first read on whether you are visible at all.
We map the 5 to 10 competitors AI actually recommends alongside you or instead of you. These are not always the competitors your leadership thinks about. Then we trace the citations: Reddit threads, review sites, publisher articles, vendor directories. This is where most recommendations originate and where most brands have no footprint.
We quantify what AI invisibility is already costing you. This uses your GA4 and Search Console data plus share-of-memory gaps to estimate pipeline at risk. Not a directional estimate. A specific number you can take to a CFO.
A 60-minute session with your leadership team walking through the findings and the specific fixes, sequenced by expected impact. You leave with a prioritised roadmap and the evidence to defend the investment internally.
Three patterns we see in almost every enterprise brand we assess.
Most brands we audit are publishing more content than their competitors and ranking well in traditional search. The problem is citations. AI models cite Reddit, review sites, and publisher articles far more than they cite brand websites. Brands that never earned third-party authority signals are invisible in AI answers, regardless of how strong their SEO is.
When we ask AI platforms to recommend options in a category, the competitive set that appears is often different from the competitors your marketing team tracks. Newer entrants, direct-to-consumer brands, and international players consistently surface. If your strategy is built around a competitor list that AI does not share, your positioning is already out of sync.
Being mentioned in an AI answer and being recommended are different outcomes. A brand can appear frequently in AI responses while almost never being the answer to "which one should I choose." We separate the two in every diagnostic because only the recommendation rate correlates to pipeline.
This diagnostic is designed for established brands
Smaller business? Check out our £997 SMB Assessment →
Read-only access to Google Analytics 4, Google Search Console, and your paid ad platforms. We also ask for a list of your 10 most strategically important queries or topic areas. All data is handled under NDA and destroyed on request after the engagement. We do not connect live systems to third-party tools.
The usual reasons: not enough third-party citations from sources AI models trust, weak or inconsistent entity signals across the web, content that optimises for keywords rather than for how people phrase questions to AI, and thin presence in the review, community, and publisher ecosystems that AI pulls from. The diagnostic identifies which of these apply to you and in what order to fix them.
The short answer depends on how much of your pipeline starts with "best", "top", "how to choose", and comparison queries. For brands heavily dependent on these, the exposure is significant. The diagnostic models your specific exposure using your GA4 and Search Console data, rather than applying a blanket category estimate.
45 days from kickoff to final executive presentation. You get a 30-minute status call every two weeks plus an interim data read at week 3. If you need faster, we offer a compressed 21-day variant for brands with immediate board pressure.
Engagements typically start at £4,000 and scale with scope. Larger diagnostics covering multi-market coverage, more languages, or deeper competitive mapping fall in the £6,000 to £10,000 range. We price after a short scoping call, not from a fixed rate card.
You have a roadmap and the option to execute it yourself, with your existing agency, or with us. Roughly 25 to 30 percent of diagnostic clients continue with a strategic advisory retainer. We are comfortable if you do not. The diagnostic is built to stand on its own.
No, and you should be cautious of anyone who does. AI models are black boxes with moving recommendation criteria. What we can guarantee is a plan built from observed patterns in your category and a set of fixes that our other clients have seen drive measurable visibility gains within 90 days of execution.
Yes. Agencies run the diagnostic on behalf of their clients either as a white-labelled deliverable or as a co-signed engagement. It is a way for agencies to add AI search capability without building an internal team overnight.
Monitoring tools report the problem. The diagnostic solves it.
Built by a team with 20+ years of search strategy experience. Paul Byrne led the global search practice at MediaCom (Adidas, Shell, Coca-Cola), led global digital transformation for LEGO at IPG, worked at Google, and ran search marketing client-side at Viator and TripAdvisor. The diagnostic applies that depth to the answer economy.
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