Strategies to Rank on ChatGPT & AI Answer Engines

What it costs

Generative engine optimisation is mostly a reallocation of existing SEO budget rather than a new line item. Practical additions: structured content rewrites, original data production and schema work - typically 20-30% of an existing SEO retainer.

Treat every range above as a starting benchmark, not a quote. Competition in your specific market, the current state of your website, how much production capacity you already have in-house, and how aggressive your growth target is will all move the number. The useful exercise is to work backwards from revenue: what is one additional customer worth, how many do you need per month to justify the spend, and does the plan on the table plausibly produce them?

How long it takes

AI answer citations can appear within weeks of publishing genuinely useful, well-structured content - faster than classic rankings - but they are volatile. Measure monthly, expect fluctuation, and judge over quarters.

Two things reliably compress timelines. The first is production volume: more genuinely useful pages and more consistent execution per month means faster results, which is why budget and speed are linked. The second is starting condition - a site with clean technical foundations and existing authority moves much faster than a new domain. Be honest about which one you are, then set expectations accordingly with whoever signs off on the budget.

What actually works

Write extractable answers: a direct one-to-three sentence answer immediately under a question-shaped heading, then the detail. Language models quote the clear, self-contained passage.

Publish original data, prices, benchmarks and methodology. Models cite sources that contain specific facts nobody else has.

None of these are clever. They are the boring fundamentals executed at unusual quality and consistency, which is what separates programmes that compound from programmes that plateau after one quarter.

Strengthen entity signals: consistent naming, an about page, author credentials, Organization and Person schema, and presence in the sources models already trust - Wikipedia-grade references, industry directories, review platforms and reputable press.

Add an llms.txt file and keep robots.txt permissive for the AI crawlers you want citing you, then track brand mentions in AI answers with periodic manual prompts or a monitoring tool.

Mistakes that cost the most

Writing long meandering prose with no clear answer paragraph - there is nothing quotable to lift.

Blocking AI crawlers in robots.txt and then wondering why you are never cited.

Treating AI visibility as separate from SEO; the same authority and clarity signals drive both.

Every one of these is common enough that we expect to find at least two of them in any audit. Fixing them costs almost nothing compared with the spend they waste, so they belong at the top of the work plan rather than in a backlog.

Your next 90 days

Weeks 1-2: instrument everything first. Tracking, call tracking where relevant, a conversion definition that finance would accept, and a baseline you can defend later. Skipping this step is the single most expensive shortcut available, because without a baseline you cannot prove anything worked.

Weeks 3-8: ship the highest-leverage items from the 'what actually works' list above, in priority order, one at a time so each change stays attributable. Resist the urge to rebuild everything at once - it feels productive and it destroys your ability to learn.

Weeks 9-12: build the compounding layer - content cadence, review velocity, link acquisition, experimentation - and set a monthly review with a fixed agenda. Pages that place a direct, self-contained answer under a question heading are cited in AI answers far more often than pages burying the same information mid-article.

If you would like a second opinion before you commit budget, we run free 30-minute strategy calls and will walk through your current setup using the same diagnostic we use with paying clients.