How to Build an SEO Strategy for an AI Startup
Amit Malvi
Founder, SearchAxe. Former Senior SEO Manager, Invideo AI
Published Updated 11 min read
Quick answer
How to build an SEO strategy for an AI startup comes down to seven steps, in order. Write down the problems buyers search for in their own words, not your category jargon. Rank them by how close they sit to a purchase and give each group a page type. Fix crawling, then ship use-case, integration, comparison and alternatives pages. Earn mentions on sites that already rank from month one, and measure non-brand impressions and AI citations before expanding.
On this page
- How to build an SEO strategy for an AI startup in seven steps
- Which keywords should an AI startup target first?
- Why should bottom-funnel pages come before the blog?
- Where do comparison and alternatives pages fit?
- How should docs and use-case pages work together?
- How does a young AI startup build authority?
- How much does SEO overlap with AI search visibility?
- What does a 90-day SEO plan for an AI startup look like?
- When should an AI startup change this strategy?
Key takeaways
- Start from the words buyers type about their problem, because the category name in your deck may have no search demand yet.
- Build use-case, integration, comparison and alternatives pages before a blog, so the first visitors land somewhere that converts.
- Authority for a young domain comes from links and mentions on sites that already rank, and it is the slowest part of the plan.
- Rankings and AI answers overlap heavily but not fully, so one plan should cover Google, Bing and the AI engines together.
- A 90-day plan should end with pages live and non-brand impressions rising, not with a traffic target.
To build an SEO strategy for an AI startup, decide which buyer searches you will win, which page answers each one, which outside sites need to mention you, and the order you will build all of it in. If you run marketing at a seed to Series B AI startup with a product in market and a small team, the order matters more than the volume, because a young domain gets little traffic and cannot spend it on the wrong pages. If your site already exists and isn't ranking, start with why AI startups struggle to rank in Google, which diagnoses the causes. This article is about what to build.
How to build an SEO strategy for an AI startup in seven steps
Work from the buyer's words to pages to authority, in that order. Each step depends on the one before it, so skipping ahead (buying links before the pages exist, or publishing a blog before product pages) wastes the slowest resource a young domain has, which is time.
Seven steps to an AI startup SEO strategy
- Write down how buyers describe the problemPull phrases from sales calls, support tickets and onboarding forms, because these are the words buyers type into Google, Bing and AI engines.
- Sort those phrases by how close they are to a purchase"Best AI dubbing tool for YouTube" is closer to a signup than "how does AI dubbing work", so it gets built first.
- Assign one page type to each groupUse-case pages, integration pages, comparison and alternatives pages, and docs each match a different intent, and one page cannot serve them all.
- Fix crawling and rendering before you publishGooglebot, Bingbot and the AI search crawlers need to read the HTML, or new pages sit unindexed.
- Ship the bottom-funnel pagesThese convert at low traffic, which is all a young domain gets in its first months.
- Start earning links and mentions in month oneAuthority builds slowly, so it has to run alongside page work rather than after it.
- Measure non-brand impressions and citations, then expandAdd top-of-funnel content only once the pages that convert are indexed and gaining impressions.
Which keywords should an AI startup target first?
Target the specific problem phrases buyers already type, even when each has small volume. Most keywords look like that. Ahrefs' guide to long-tail keywords, updated in May 2026, reports 2.3 billion keywords in its US database with fewer than 10 searches a month, nearly 93% of the database. Ahrefs defines long-tail by search volume, not by word count.
For an AI startup the trap is the category name. Founders want to rank for the term in the pitch deck, but buyers describe the problem in older, plainer words, and those are the words they type. The table shows the gap for a hypothetical AI product.
| What the deck says | What buyers type | Page that answers it |
|---|---|---|
| Generative localization layer | AI video dubbing tool | Use-case page |
| Plugs into your creative stack | AI dubbing plugin for Premiere Pro | Integration page |
| Next-generation voice infrastructure | ElevenLabs alternative for dubbing | Alternatives page |
| Multilingual synthesis engine | HeyGen vs Rask AI for translation | Comparison page |
| Real-time lip sync model | How to translate a YouTube video into Spanish | Docs or guide |
You can still build the new category name over time, mostly through mentions and comparisons rather than one page. That method is in what to do when buyers aren't searching for your category name.
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Schedule a Free ConsultationWhy should bottom-funnel pages come before the blog?
Because a young domain gets little traffic at first, and that traffic has to land on pages that convert. A guide to "how AI dubbing works" might rank, but its readers are months from buying. An integration page for "AI dubbing plugin for Premiere Pro" gets fewer visits, and most of them are people choosing a tool this week.
Each bottom-funnel page needs specifics only your team can write: what goes in, what comes out, which plans include it, what it doesn't do yet. Google's helpful content guidance asks whether a page shows "first-hand expertise and a depth of knowledge", and those details are how a product page shows it. They are also the passages AI engines lift when they answer a buying question.
Where do comparison and alternatives pages fit?
Right after the use-case pages, because they win the searches buyers run just before choosing. Queries like "X vs Y" and "alternatives to X" come from buyers comparing options, so a page built to compare is the format that matches them.
Ahrefs' study of 14 billion pages uses "best yoga mat" as its example: the top organic results are blog posts with recommendations, not product pages, because that is the format searchers want.
Write them fairly. State where the competitor is the better choice, date the page and update it when either product changes. A page that only praises you reads as an ad to buyers and gives engines little reason to quote it. The full treatment, including legal care, is in whether an AI startup should build alternatives and comparison pages.
How should docs and use-case pages work together?
Docs answer how to do something with the product, and use-case pages answer which product to pick. Plan both, and link them. If your docs have earned links from developers, a link from a docs page to the matching use-case page passes some of that authority to a page that converts.
Check the robots rules on a docs subdomain as carefully as on the main site. OpenAI's crawler documentation says sites that opt out of OAI-SearchBot "will not be shown in ChatGPT search answers", and a blanket block added to a docs host to stop scraping can remove your most technical pages from those answers. More on structuring docs for search is in SEO for an AI product documentation site.
How does a young AI startup build authority?
By getting mentioned and linked on sites that already rank for your topic: the roundups for your category, integration partners' directories, publications your buyers read and communities where they compare tools. Google says it finds pages mainly through links from pages it has already crawled, so each of those links is also a path for discovery.
Correlation is not proof that mentions cause AI visibility, but it points the same way as the link evidence. Plan authority work as a monthly quota from month one: a handful of roundup placements, partner listings and one piece of original data a quarter that others can cite. Depth matters as well as reach, which is covered in how to build topical authority AI engines recognize.
How much does SEO overlap with AI search visibility?
Mostly, which is why one plan should cover both. Google's AI features documentation says a page that is indexed and eligible for a snippet is eligible to be shown as a supporting link in Google AI Overviews or Google AI Mode, with no extra requirements. ChatGPT search and Copilot draw on Bing's index. So a page that ranks on Google and Bing is already a candidate for ChatGPT, Google AI Overviews, Google AI Mode and Copilot. Perplexity, Claude and Gemini document less about how they retrieve pages, and we have not seen reliable data on how closely they follow those rankings.
Candidate is not the same as cited. Ahrefs found in March 2026 that 37.9% of URLs cited in Google AI Overviews also appeared in the first 10 positions on the results page, counting SERP features, down from about 76% in its July 2025 study. Google's systems run several related searches for one question, so pages that answer sub-questions clearly, and third-party pages that mention you, carry weight beyond your rankings. That is the case for answer-first page structure and for the authority work above.
What does a 90-day SEO plan for an AI startup look like?
Ninety days is enough to get the foundation right and the first bottom-funnel pages indexed. It is not enough to judge the channel on signups. The plan below is the sequence we use for SEO for AI startups, and it works the same way for an in-house team.
| Weeks | Work | What exists at the end | What to measure |
|---|---|---|---|
| 1 to 2 | Buyer language research, crawl and render checks, baseline | A ranked keyword and prompt map, a fix list, a recorded baseline | Indexed pages, brand versus non-brand impressions |
| 3 to 4 | Homepage rewrite, technical fixes, Organization structured data | A homepage that names the job, clean indexing in Google and Bing | Pages indexed in Search Console and Bing Webmaster Tools |
| 5 to 8 | First use-case, integration and comparison pages, first roundup pitches | Six to ten bottom-funnel pages live, outreach running | Non-brand impressions, first referring domains |
| 9 to 12 | Alternatives pages, docs-to-product links, first original data piece | A full bottom-funnel set, a reason for others to link | Non-brand impressions and clicks, AI citations in a fixed prompt set |
Record the baseline in week one and keep the same prompts and queries all quarter, so every change you report is measured against the same starting point. Expect the curve to keep rising well after day 90. How long SEO takes for a new AI startup domain sets out the month-by-month milestones.
When should an AI startup change this strategy?
When search is not where your buyers look. If you sell only through enterprise outbound, if the product changes so often that pages go stale monthly, or if developers find you mainly through GitHub and community channels, a smaller SEO effort focused on docs and brand queries may be enough for now. The timing question is covered in when an AI startup should start investing in SEO. If you plan to bring in help, our comparison of SEO agencies for AI startups sets out what to check before you sign.
Frequently asked questions
What should an AI startup's first SEO pages be?
Use-case pages, integration pages, and comparison and alternatives pages. They match searches from people choosing a tool now, so they convert even at the low traffic a young domain gets. Each should state what goes in, what comes out, which plans include it and what it does not do. Top-of-funnel guides can wait until these are indexed and gaining non-brand impressions in Search Console.
Should an AI startup target its category name in SEO?
Not first. A category name coined in the last year often has little or no search demand, while buyers keep searching the older problem words. Rank for those problem words with use-case and comparison pages, and build the category name through mentions, roundups and comparisons over time. Track impressions for the category term in Search Console so you know when demand appears.
How many pages does an AI startup need for SEO?
Fewer than most founders expect. In our planning, six to ten well-built bottom-funnel pages in the first two months do more than fifty thin posts, because each targets a buying query and carries specifics only your team can write. Google's spam policies treat generating many pages without value for users as scaled content abuse, so volume for its own sake is a risk on a young domain.
Does SEO help an AI startup appear in ChatGPT and other AI answers?
Yes, substantially. ChatGPT search and Copilot draw on Bing's index, and Google says pages that are indexed and snippet-eligible are eligible to appear in Google AI Overviews and Google AI Mode. Ranking is not enough on its own. Ahrefs found in March 2026 that only 37.1% of URLs cited in Google AI Overviews also ranked in the organic top 10, so clear answers and third-party mentions also count.
How should an AI startup choose which competitor comparison pages to build first?
Start with the competitors buyers already name in sales calls and support tickets, and the ones listed on the roundups that rank for your category. Those names carry existing search demand, so alternatives and comparison pages meet buyers who are already shopping. Write each page fairly, say where the competitor is the better choice, compare on facts a buyer can check, date the page and update it whenever either product changes.
