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Strategy

How to build an AI search visibility strategy

Most "AI strategies" are a list of tactics. A strategy decides which questions you need to win, where you stand today, which gaps matter most, and how you will know whether it's working. Here is the framework we use.

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By · Updated · 3 min read

Step 1: Decide which questions you need to win

Everything starts with the questions buyers ask before choosing a provider like you. Group them into four types:

Type Example Why it matters
Category “Best CRM for a 20-person sales team” Decides whether you make the shortlist
Comparison “HubSpot vs Pipedrive vs [you]” Decides how you’re framed against rivals
Problem “How to stop leads going cold” Earns citations and early awareness
Brand “Is [you] good for agencies?” Decides what people learn when they check you

Sources for these questions: Search Console queries, sales-call notes, support tickets, “People also ask” boxes, community threads and your own testing of AI assistants. Aim for a stable core set you will track for at least a year.

Step 2: Baseline where you stand

Before changing anything, record:

  • Search performance — rankings, impressions and clicks for the pages that should answer each question.
  • AI visibility — mention, recommendation and citation rates for each prompt across ChatGPT, Gemini, Perplexity, Copilot and Google’s AI features, sampled several times.
  • Representation — which category you’re placed in, what attributes are attached to you, and which facts are wrong.
  • Sources — which third-party domains AI answers cite for your category.

Our guide to measuring AI share of voice explains how to do this without over-reading noisy data.

Step 3: Diagnose the gaps

Each pattern in the baseline points to a different cause:

What you see Likely cause Work stream
Not cited even for questions your pages answer Crawling/indexing problems, or the answer is buried Technical SEO, AEO
Cited, but rarely recommended Third-party sources favour competitors Brand mention building, digital PR
Mentioned, but in the wrong category Inconsistent positioning across the web Entity optimization
Described with outdated facts Stale profiles or pages being retrieved Entity optimization, content updates
Absent everywhere Low authority and thin content SEO and content strategy first

Step 4: Prioritise

Score each fix on impact (how many priority questions it affects), confidence (how directly it addresses a diagnosed cause) and effort. Do blockers first — a crawler blocked in robots.txt or a CDN rule undermines everything else. Then fix your own pages, which you control fully, before investing in slower third-party work.

Step 5: Execute across three layers

  1. Access — make every important page crawlable and indexable by search and AI search crawlers; render key content in HTML; keep sitemaps accurate.
  2. Answers — rewrite priority pages answer-first; add the missing pages buyers need (pricing explanation, comparisons, use cases, limitations); keep facts current.
  3. Authority — make your brand facts consistent everywhere; earn coverage and reviews; be present and accurate on the sources AI answers cite in your category.

Step 6: Measure and iterate

Re-run the same prompts on the same schedule, compare against the baseline and competitors, and report what changed alongside what you did. Treat small month-to-month moves with caution — run-to-run variation is real. Review the prompt set quarterly and add new questions as a separate cohort.

Realistic timelines

Work When effects can show
Unblocking crawlers, fixing indexation Weeks, once pages are recrawled
Rewriting pages answer-first Weeks to a few months
Correcting brand facts across profiles One to three months
Earning coverage, reviews and roundup inclusion Several months, compounding

Common mistakes

  • Starting with tactics instead of questions. Without a prompt set, you can’t tell whether anything worked.
  • Measuring with screenshots. One run is an anecdote; repeated sampling is evidence.
  • Ignoring SEO fundamentals. Most AI search products retrieve web pages; weak SEO limits everything above it.
  • Publishing volume for AI. Mass-produced pages rarely add the specific, original information answers cite, and can harm search performance.

FAQ

AI search strategy: frequently asked questions

How long does an AI search strategy take to show results?
Technical and on-page fixes can affect retrieval within weeks once pages are recrawled. Changes to how answers describe and recommend you usually take months, because they depend on third-party sources and repeated sampling to confirm a trend.
Should we have a separate team for AI search?
Usually not. The work overlaps heavily with SEO, content and PR. What's needed is a shared set of prompts and metrics so those teams optimise toward the same outcomes.
How many prompts should we track?
Enough to cover your main buying questions without creating noise — typically 20 to 60 for a focused business, more for large catalogues. Keep the core set stable so trends are comparable.
Does this replace our SEO strategy?
No. It extends it. Most AI search products retrieve web pages, so SEO is the foundation. The strategy adds answer quality, entity consistency, third-party references and AI-specific measurement.

Related to AI search strategy

AI Visibility Audit

Is your brand visible where your customers are searching?

Our AI Visibility Audit shows how you appear across Google and AI answer engines today — and what to fix first.

Prefer email? prithvi@prisol.org