Being the source the answer comes from
A growing share of the people evaluating you will never see your website. They will ask an assistant, read the answer, and form a view from whatever it cited. Being the source of that answer is a different job from ranking first, and it is increasingly the one that decides whether you make the shortlist at all.
- AI search visibility work aims to make a company the source that ChatGPT, Claude, Perplexity and AI Overviews cite when buyers ask about its category.
- AI search visibility matters most for considered-purchase B2B, technical products and regulated categories, where buyers research with an assistant before contacting anyone.
- Technical AI search foundations can register within weeks, but citation changes from content restructuring realistically take two to three months.
- The AI search visibility audit and baseline are a fixed-fee project from £3,000, and ongoing monitoring is a monthly retainer.
- I run a monthly AI visibility programme for a regulated financial firm that checks a fixed set of priority queries across six answer engines.
Why nobody clicks any more, and what that costs you
Search has been quietly turning into an answering machine. The traffic that arrives is more qualified and there is much less of it, which breaks a lot of reporting and most content strategies.
- The answer replaced the click
- Someone asks the question, gets a synthesised answer, and never visits a site. If you were not in the answer, you were not in the consideration set.
- Your content is unreadable to a model
- Long, unstructured pages that bury the claim, hedge the specifics, and give an assistant nothing clean to quote. Search engines forgave that. Answer engines do not.
- You cannot see it happening
- None of this shows up in Search Console. Most teams have no idea whether they are being cited, misdescribed, or confused with a competitor.
- Being wrong is worse than being absent
- Assistants will describe your product either way. Without clear, current, structured sources to draw on, they will confidently draw on something out of date.
Who is AI search visibility for?
Companies in categories where buyers research before they ever speak to anyone.
Considered-purchase B2B
Long evaluations that start with a question to an assistant rather than a search box.
Technical products
Where the explanation is complicated enough that people ask for it to be summarised, and the summary needs to be yours.
Regulated categories
Where being described inaccurately by an assistant is a compliance exposure as well as a marketing one.
Teams watching clicks fall
Impressions holding up, clicks declining. That is usually the answer layer at work rather than a ranking loss.
Companies with strong content
You have already done the work; it is just structured in a way that is hard to cite.
New entrants
No brand recognition yet, so what an assistant says about your category is doing your positioning for you.
What does AI search visibility include?
Each workstream is designed to move a specific metric, not to pad a report.
Citation audit
What the major assistants currently say about you, your category and your competitors: where you are cited, where you are absent, and where you are described wrongly. This is the baseline, and it is usually uncomfortable reading.
Content architecture
Restructuring what you already have so it can be quoted: claims stated plainly, questions answered directly, specifics rather than hedges, and a structure a model can lift from cleanly without losing the meaning.
Machine-readable foundations
Structured data, llms.txt, clean semantic markup, and the technical work that makes a site legible to something that is not a browser. Overlaps with technical SEO and is not the same job.
Monitoring
A repeatable way to check what assistants say about you over time, so this is a thing you manage rather than a project you did once.
How does the work run?
Four phases with real durations. Nothing here is a proprietary framework. It is the order the work has to happen in.
Baseline
Establish what assistants currently say about you and your category, which sources they draw on, and where the gaps and inaccuracies are. Without this you cannot tell whether anything you do afterwards worked.
Foundations
The technical layer: structured data, llms.txt, semantic markup, and fixing anything that makes the site hard to parse. Fastest to implement and the prerequisite for everything else.
Restructure
Rework the content that matters most so it answers questions directly and can be quoted without distortion. Usually a rewrite of a small number of high-value pages rather than a large volume of new ones.
Monitor
Re-run the citation checks, watch what changes, and adjust. This field is moving quickly and anyone claiming a settled playbook is guessing.
How much does AI search visibility cost?
Most work starts with a fixed-fee audit. Scope moves the number, not seniority: you get me either way.
Audit and roadmap
From £3,000
I look at what you are running now, find what is structurally broken as opposed to merely underperforming, and hand back a prioritised plan you could execute without me. Most engagements start here.
Ongoing retainer
From £4,000
Strategy plus execution across the channels that matter for your stage. Two or three disciplines working together rather than all five at once.
Advisory
£450 per day
For teams with people in place who need someone senior to pressure-test the plan, review the work, and say the unpopular thing.
What results has AI search visibility produced?
I currently run a monthly AI visibility programme for a regulated financial firm. I cannot publish their citation data, but I can describe the method, because the method is the part you are buying.
Questions people actually ask
Including the ones about money.
Written by
Oliver Carding
Marketing consultant in Manchester. Previously Head of Marketing at Improbable and Senior Digital Marketing Lead at eBay; founded CoinJournal and CryptoKaiju. Career, press and references.
Other services
Most engagements use two or three together. A strategy sets the direction; the rest do the work.
Digital marketing strategy
Audience research, channel planning, go-to-market, and measurement frameworks. The decision-making layer that tells you what to do, in what order, and how you’ll know it’s working.
Search engine optimisation
Technical SEO, keyword strategy, content optimisation, and authority building. I fix the structural problems that stop search engines finding you, then build the visibility that compounds over time.
Content marketing
Content strategy, thought leadership, newsletters, and distribution. The aim is content that answers the questions your buyers actually have, in places they’ll actually find it, rather than volume for its own sake.
Social media management
Channel strategy, community management, content publishing, and paid social on the channels your audience already uses: X, Discord, Telegram, and LinkedIn.
Paid advertising
Google Ads, Meta advertising, tracking, and bid optimisation. Paid media in crypto is tricky: platform policies shift, audiences are sceptical, and most budgets leak. I stop the leaks.
Digital transformation
Replatforming, measurement infrastructure, and the way a marketing team actually runs. Most problems that look like strategy problems are plumbing problems: the tracking is wrong, the site can’t ship a page, and nobody agrees what a lead is.
AI consultancy
Where AI genuinely improves a marketing team’s work and where it is theatre. Workflow design, tooling, quality standards, and the judgement to say when the honest answer is “don’t”.