Most marketing teams adopt AI visibility work the way they once adopted SEO: reactively, in fits and starts, usually after someone notices a competitor showing up in a ChatGPT answer where the team's own brand does not. That approach wastes a quarter chasing the wrong fixes.
What follows is a prescriptive 90-day plan, not a story about a specific customer. Treat it as a template to adapt to your own content library, team size, and category. The phasing borrows from a well-worn idea in change management: break a large, ambiguous goal into 30-day blocks that each end with something concrete to show.
The plan assumes a small, cross-functional team: someone who owns content, someone who owns technical SEO, and someone who owns PR or partnerships. If your team is smaller than that, one person can wear all three hats across the 90 days. If it is larger, the phases still hold, you simply run more workstreams in parallel within each one.
Generative engine optimization, or GEO, is still new enough that most marketing teams have no internal precedent for it. There is no existing playbook sitting in the shared drive. That absence of precedent is exactly why phasing matters: without it, teams either freeze waiting for certainty or scatter effort across a dozen tactics at once.
The 30-60-90 day structure is not a GEO invention. It is a standard onboarding and change-management framework, most associated with the idea of learning first, contributing second, and reaching independent performance by day 90. Asana's breakdown of the framework describes the three phases as learning and integration, active contribution, and mastery, each one building on the last rather than running in parallel from day one.
Applied to AI visibility, the same logic holds. You cannot fix what you have not measured, and you cannot earn citations for content that has not been fixed yet. Skipping straight to outreach and PR before your own pages are in shape means you are inviting attention to content that will not hold up once someone clicks through.
Each phase below has a single job. Days 1 through 30 establish a baseline and complete an audit. Days 31 through 60 focus on fixing content and site structure. Days 61 through 90 shift to earning third-party mentions and building a measurement cadence that survives past day 90. Resist the urge to blend phases together. A team that starts pitching journalists in week two, before the audit is done, usually ends up promoting the same pages it will need to rewrite a month later.
The first month is about resisting the urge to fix anything yet. You need a clear picture of where your brand currently stands before you can tell whether later work is moving the needle.
Start by running your brand name, your core product terms, and your top three competitor names through ChatGPT, Perplexity, Gemini, Claude, and Copilot. Ask the kinds of questions a prospect would ask: "best tools for X," "how do I solve Y," "alternatives to Z." Log whether your brand appears, how it is described, and which sources the model cites.
Doing this by hand across five models and dozens of prompts is tedious and easy to get wrong, since answers shift day to day. A tool built for this, like Bold GEO, automates the daily refresh so you have a consistent baseline instead of a single noisy snapshot. Our guide on how to check your AI brand visibility walks through the manual version if you want to start there first.
With a baseline in hand, turn to the content itself. A useful audit checks whether each page gives an AI system something worth quoting: a direct answer near the top, a clear structure, and claims that are specific rather than vague. Pages that read like marketing copy instead of resolving a real question tend not to get cited, regardless of how well they rank.
We cover the full audit process, including which pages to prioritize and what a scoring rubric looks like, in our GEO audit guide. At minimum, log each page's URL, current organic traffic, whether it currently appears in any AI answer, and a simple citability score based on whether it leads with a clear answer, uses descriptive headings, and separates claims into distinct sentences rather than dense paragraphs.
Build the audit as a spreadsheet, not a slide deck. You will keep referring back to it through day 60, and a static presentation goes stale the moment you start making edits. Group pages into three buckets: fix now, fix later, and leave alone because the page already performs well.
By the end of day 30 you should have three deliverables: a baseline visibility snapshot across all five models, a prioritized list of pages that need work, and a short list of topics where you have no content at all. That gap list matters as much as the fix list. A topic your buyers ask about that you have never written on is a guaranteed miss, regardless of how well your existing pages perform.
Before moving into execution, name who owns each bucket. Content leads typically take the rewrite backlog, technical SEO owns schema and crawlability fixes, and whoever runs PR or partnerships starts building a target list for phase three. Writing this down now avoids the awkward week 35 conversation about who was supposed to be doing what.
This is the execution month. You are not adding new tactics here, you are working through the backlog the audit produced, starting with your highest-traffic and highest-intent pages.
Move the direct answer to the top of the page, before the context and caveats. Break claims into distinct sentences instead of burying three ideas in one paragraph. Add specific numbers, named steps, and comparisons where you can support them, since vague language gives a model nothing concrete to quote.
Resist the temptation to chase every GEO tactic you read about online. Google's own search guidance, reported by Search Engine Journal, states plainly that optimizing for generative AI search is still SEO, and specifically calls out that llms.txt files, aggressive content chunking, and AI-specific rewrites are not necessary for visibility. The fundamentals, clear writing, real expertise, and a page that actually answers the question, still carry the work.
Alongside the rewrites, clean up the technical basics: make sure pages are crawlable and indexable, add schema markup where it is genuinely useful for rich results, and fix internal linking so related pages reinforce each other. None of this is exotic. It is the same technical SEO hygiene that has mattered for a decade, applied with an eye toward how an AI system parses the page rather than only how a search engine ranks it.
Pay particular attention to pages that answer comparison questions, since these are exactly the prompts buyers run through AI assistants before they ever visit your site. "X versus Y" and "best tools for" style pages deserve a full rewrite pass before anything else in the backlog, because they sit closest to a purchase decision.
Rewrites only get you so far if entire topics are missing. Use the gap list from day 30 to brief new pages, prioritizing the topics where competitors already appear in AI answers and you do not. Write these the same way you rewrote existing pages: answer first, specifics over generalities, and a structure a model can parse without effort.
By day 60, aim to have worked through your top priority bucket entirely, made visible progress on the second bucket, and published or drafted the highest priority gap content. This is also a good checkpoint to re-run your baseline prompts and note any early shifts, even if full citation changes have not caught up yet.
Sometimes, but set expectations honestly with your team. Model providers refresh their training and retrieval data on different schedules, and a page you fixed in week 5 will not necessarily show up in an answer by week 8. What you can expect by day 60 is a measurable shift in the inputs: more pages that meet a citability bar, cleaner structure, and a visibility baseline you can compare against.
Treat citation appearances themselves as a lagging indicator. The leading indicators, page quality, structure, and topical coverage, are what you actually control during this phase.
The final phase shifts outward. AI models weigh third-party signals, review sites, forums, comparison posts, and press coverage, alongside your own content. A perfectly optimized page on your own domain only gets you so far if no one else on the web is talking about you.
Identify the review sites, comparison roundups, and community threads where your category gets discussed, and make sure your brand is represented accurately on them. Pitch relevant publications on original data or a genuinely useful framework, the kind of thing worth citing rather than a generic guest post. PR and content teams that already run outreach programs should fold AI visibility into the existing brief rather than standing up a separate initiative.
Do not overlook your own customers and partners here. A handful of honest, specific mentions on review platforms or in community discussions often carries more weight with an AI system than a press release, because the language reads as independent rather than promotional.
Original commentary from a named expert, whether that is a founder, a product lead, or a customer-facing specialist, tends to get picked up and cited more readily than unattributed brand copy. Spend part of this phase lining up a few pieces of expert commentary, whether that is a byline, a quote in a roundup, or a podcast appearance, and make sure the author's credentials are clearly stated on the page itself.
By now you have baseline data from day 1 and fresh data from ongoing tracking. Set a recurring review, weekly or biweekly, comparing citation frequency, sentiment, and share of voice against your competitors across all five models. A daily-refresh tool removes the manual burden of re-running the same prompts by hand every week, which is where most ad hoc tracking efforts quietly die.
This is also the point to decide who owns AI visibility going forward. It should not be a side project. Assign it to whoever already owns organic search or content strategy, and give them a recurring slot in your reporting rhythm.
Close out the 90 days with a short retrospective: which fixes correlated with new citations, which earned mentions actually got picked up, and which parts of the plan took longer than expected. That retrospective becomes the input for how you scope the next quarter, rather than starting the next cycle from a blank page.
The 90-day version of this plan gets you through the first pass: baseline, fix, earn, measure. The real value comes from repeating a lighter version of it every quarter. Model behavior shifts, competitors publish new content, and your own product changes, so a one-time audit goes stale.
A practical rhythm looks like this: a full audit and fix cycle once or twice a year, with a lightweight monthly check-in on your highest-priority pages and competitors in between. This mirrors how content teams already run recurring content audits rather than treating them as a one-off project, layering quarterly mini-reviews on top of a broader annual pass.
If you are starting from zero, do not wait for a perfect plan. Run the baseline this week. You can sign up for a 7-day free trial to get your first visibility snapshot across ChatGPT, Perplexity, Gemini, Claude, and Copilot without committing to anything, and use that snapshot as day 1 of your own 90-day clock.
Bold GEO monitors how your brand is cited across ChatGPT, Perplexity, Gemini, Claude, and Copilot on a daily refresh. 7-day free trial, no credit card.