LLM SEO: how B2B SaaS brands get named in AI answers

LLM SEO means getting your brand named and linked when buyers ask ChatGPT, Perplexity, Gemini, Claude or Google's AI Overviews which software to use. For B2B SaaS, most pages those answers cite are not yours. So the work has two parts: make your own site easy to quote, and get onto the third-party pages the assistants read.

This guide is about one kind of question: "what is the best X software" and "which tool should I use for Y". Those are the questions where a buyer builds a shortlist. Below you find what the assistants cite for them, what you can do about each source type, how to measure the result, and what is not worth your time.

What is LLM SEO, and is it the same as GEO or AEO?

Mostly, yes. The industry uses several names for the same work:

• **LLM SEO**: optimizing for answers from large language models such as ChatGPT, Claude and Gemini.
• **Generative engine optimization (GEO)**: the same idea, named after "generative engines" that write an answer instead of showing ten links.
• **Answer engine optimization (AEO)**: an older term from featured snippets and voice search, now used for AI answers too.
• **AI visibility**: the outcome you measure. How often your brand is named, linked and described correctly in AI answers.

Google's own view is that these are not a separate discipline. In June 2026 Brendon Kraham, a VP at Google, wrote a Think with Google piece titled "Good SEO is good GEO". He said AI Mode and Google's other generative features are built on top of Google's core ranking systems (reported by PPC Land). That matters for Google. It matters less for the pages ChatGPT or Perplexity pick, which is why the rest of this guide looks beyond your own site.

Why does AI visibility matter for B2B SaaS?

Because buyers now start there. In G2's 2026 survey of 1,076 B2B decision-makers, 51% said they start their software research in an AI chatbot more often than in Google. In April 2025 it was 29% (G2, The Answer Economy).

Classic search clicks are also shrinking where AI answers appear. Ahrefs found a 58% lower click-through rate for the top-ranking page when Google shows an AI Overview, across 300,000 keywords (Ahrefs, February 2026). Being the brand inside the answer seems to help: Seer Interactive saw 120% more organic clicks per impression for brands cited in the AI Overview than for brands that were not (Seer Interactive, April 2026). That is a correlation across 53 brands, not proof that the citation caused the clicks.

The short version: a buyer can now get a shortlist of three tools without visiting a single vendor site. If you are not on that shortlist, you may never hear about the deal you lost.

How do AI assistants decide which brands to name?

When a question needs current facts, most assistants search the web first and then write an answer from what they found. They don't keep a fixed ranking of brands. Google says AI Overviews and AI Mode may use a "query fan-out" technique: they run several related searches across subtopics and data sources, then build one answer (Google Search Central).

That has three practical effects for a B2B SaaS brand:

• **The searches behind the answer are often longer than the buyer's question.** "Best CRM" can fan out into "best CRM for small teams", "CRM pricing" and "HubSpot alternatives". Pages that rank for those sub-questions get read.
• **Being found comes before being named.** A page the engine can't find or can't index can't be cited, however good it is.
• **The answer repeats what many pages agree on.** If ten pages describe you as a tool for agencies, the assistant will too. One page that says otherwise rarely wins.

So LLM SEO is less about tricks on one page and more about how your brand is described across all the pages a search can reach.

What do AI assistants cite when someone asks for the best software?

Mostly pages you don't own. Foundation and AirOps studied 5.1 million AI responses for 50 B2B SaaS brands. On category questions that did not name the brand, only 2.24% of citations went to the brand's own pages (Foundation). On questions that named the brand, the brand's own share was 30.7%. So your site answers "what is Acme"; other people's pages answer "what is the best tool for this".

Prefer looked at 188 answers to buyer questions from ChatGPT, Perplexity, Gemini and Claude in July 2026. Independent lists were 40% of the cited sources. Vendors' own sites got 34% and review sites 3% (Prefer, July 2026). Semrush found LinkedIn is cited in 11% of AI answers across 325,000 prompts, with only one domain cited more often (Semrush, March 2026).

The engines also behave very differently. In a second Prefer study of 960 answers (September 2026), Perplexity cited 19.48 sources per answer on average, Gemini 8.64, Claude 4.58 and ChatGPT 3.05. 72.7% of cited sites appeared on one engine only, and 2.2% on all four (Prefer AI answer study). So "we are cited in AI" usually means "we are cited by one engine, sometimes".

How do you make your own site easy for AI to cite?

Your site is the base. It wins branded questions, it is where assistants check what you do, and Google's AI features pull from Google's normal index. Google says a page must be indexed and eligible to be shown with a snippet to appear in AI Overviews or AI Mode, and that there are no extra requirements (Google Search Central).

1. **Get indexed in Google and Bing.** Check both in Search Console and Bing Webmaster Tools. ChatGPT's search has leaned on Bing since Microsoft made Bing its default search engine in 2023 (CNBC), and Bing also feeds Copilot. Don't block AI crawlers you want to be read by.
2. **Say what you are in one sentence.** Put the same plain description on your home page, product pages, About page, LinkedIn page and directory profiles. Assistants repeat what they read; give them one version.
3. **Answer the question first.** Start key pages with a direct answer in 40 to 60 words: what the product does, for whom, and what it costs or how to get a price.
4. **Build pages for the questions buyers ask.** Use cases, integrations, comparisons ("X vs Y", "X alternatives") and pricing. Phrase headings the way people ask. Use tables for comparisons.
5. **Show facts, not adjectives.** Numbers, dates, named customers you are allowed to name, and your method. Mark when a page was last checked.
6. **Keep text in text.** Google says to make important content available in textual form. Don't hide your pricing or feature list in an image or a PDF only.
7. **Watch what gets cited.** Bing Webmaster Tools has an AI Performance report (public preview since February 2026) that shows citations of your pages in Copilot and Bing's AI summaries (Bing).

None of this is new SEO. Google's guidance says you don't need special files, markup or AI-only content (Google Search Central). The win is that a clear, indexed, well-structured site also ranks better in classic search.

How do you get into third-party "best X" lists?

Lists are the biggest single source type in Prefer's buyer-question study, at 40% of citations. They are also where your competitors already sit. There are three honest ways in.

1. Earn the spot

Find the lists that come up for your category questions (run the prompts below and note which pages get cited). Then contact the author with what is new: a feature they don't list, a pricing change, a trial account. Many authors update their lists every few months and want accurate entries. This is free and slow, and it works best when your product is strong in a niche the list covers badly.

2. Pay for a disclosed spot

Many publishers sell a position in an existing list or write a new sponsored list. Prices run from a few hundred dollars once to a few thousand a month (see what GEO costs and the listicle placement price index). One-off spots have a known weak point: after you pay, nobody checks whether your entry is still there. Rank Monthly is one option here. It books brands into list articles, newsletters and LinkedIn creator posts and keeps them there, paid monthly only while the spot is live. It is in early access, so it covers only the publishers who have joined so far.

Whatever you buy, keep it disclosed. Google updated its documentation on May 15, 2026 to say its spam policies apply to all of Google Search, including generative AI responses (PPC Land). A spot on a page that only exists to rank you first is a risk, not an asset. The full playbook is in listicle placements for B2B SaaS.

3. Publish your own fair comparisons

Your own "X vs Y" and "alternatives" pages will win fewer category citations than independent lists. They still help: assistants read them when a buyer asks about you by name, and they give list authors facts to copy. Be fair. Say where the competitor is stronger. A one-sided page reads as an ad, to people and to models.

Do review sites like G2 and Capterra help AI visibility?

They help buyers more than they help citations, based on current data. Review sites were 3% of cited sources in Prefer's July 2026 study of 188 answers (Prefer). That is one small study, and review platforms also feed other sources: list authors and journalists use review scores and quotes.

What to do: ask real customers for reviews at moments they are happy, such as after onboarding or a renewal. Keep your profile complete: categories, pricing, integrations, screenshots. Never buy or incentivize reviews outside each platform's rules.

How do Reddit and communities show up in AI answers?

Threads where people compare tools are exactly what assistants look for, and they are hard to fake. Google's spam documentation says seeking inauthentic mentions "isn't as helpful as it might seem" (PPC Land).

• Answer real questions in subreddits and Slack or Discord groups where your buyers ask for tools.
• Post as yourself, say you work at the company, and recommend another tool when it fits better.
• Don't run fake accounts or pay for undisclosed comments. Moderators remove them, and the damage outlasts the post.
• Write answers that would still be useful with your brand removed. Those are the ones people upvote.

Does LinkedIn content get cited by AI assistants?

Yes, often. In Semrush's March 2026 study of 325,000 prompts, 11% of AI answers cited LinkedIn (Semrush). For B2B SaaS that is useful: your buyers and your founders are already there.

• Post specific, useful content from people, not only from the company page: numbers, how-tos, lessons with dates.
• Write articles and long posts that answer a real buyer question in the first lines.
• Work with creators your buyers follow. A creator who explains when your tool fits, in their own words, reads as a recommendation, not an ad. Disclose paid posts.

What about newsletters and earned media?

We found no reliable study that measures how often newsletters are cited, so treat them as a reach play first. Newsletters with a web archive get indexed like any page, and niche B2B newsletters are read by the buyers and writers who create the lists assistants cite.

Earned media (news coverage, expert quotes, podcasts with transcripts) builds the brand signals that make list authors include you. The reliable way in is real material: your own data, a clear opinion with numbers, or a product change worth a story. Paying for an "as seen in" logo does not count.

How do you measure AI visibility?

With a fixed prompt set, repeated runs and honest numbers. AI answers change from run to run. In Prefer's September 2026 study, repeat runs of the same question shared 96% of cited sites on Perplexity, 68% on Claude, 37% on ChatGPT and 35% on Gemini (Prefer). One run tells you very little.

1. **Write 20 to 50 prompts** buyers would really ask: "best X software for Y", "X alternatives", "which tool should I use to Z", "how much does X cost". Include a few branded ones ("what is Acme").
2. **Freeze the set.** If you change a prompt, note the date. Otherwise you can't tell a real change from a new question.
3. **Run each prompt several times per engine**, at least three, on ChatGPT, Perplexity, Gemini, Claude, Copilot and Google's AI Overviews.
4. **Record four things per answer:** were you named, were you linked, was the description right, and which sources did the answer use.
5. **Report "named in X of Y answers" per month**, not a rank. Small weekly moves are usually noise.
6. **Act on the sources.** A wrong description means fixing the page the assistant read. A cited list that doesn't name you is an outreach or placement target.

You can do this by hand in a spreadsheet. With more prompts, a tracker saves time. Self-serve tools start around $29 a month and enterprise platforms are priced on request; see the best AI visibility tools and the alternatives pages for Profound, Peec AI and Otterly.AI. Most trackers tell you what is cited. They don't get you onto those pages; that part is still outreach, placements and content.

What doesn't work, or isn't proven?

• **llms.txt as a ranking lever.** Google's Kraham said files like llms.txt are not needed, at least for Google Search (PPC Land), and Google's documentation says no AI text files are required (Google Search Central). Keeping one accurate does no harm. Expect nothing from it.
• **Chunking content into tiny pieces for AI.** Kraham warned against chopping content into artificial snippets. Write for people, with clear headings.
• **Guarantees.** No one controls what ChatGPT or Google says. An agency or tool that guarantees mentions or rankings is selling something it can't deliver.
• **Self-made "we are number one" lists on sites built for that.** Google's spam policies cover AI answers too. Biased lists on weak sites are a risk.
• **Fake reviews and astroturfed threads.** They break platform rules, get removed, and can teach the models the wrong story about you.
• **Judging by one engine or one run.** With 72.7% of cited sites showing up on only one engine in Prefer's study, a single screenshot proves very little.

Where should a B2B SaaS team start?

1. **Week 1: baseline.** Write your prompt set, run it three times per engine, and record who is named and which pages are cited.
2. **Weeks 2 to 4: fix your own site.** Check indexing in Google and Bing, write the one-sentence description, add answer-first intros and a fair comparison page.
3. **Month 2: the cited pages.** List every third-party page that came up. Contact the authors where you have something new. Decide which spots are worth paying for, and keep them disclosed.
4. **Month 2 onward: people channels.** Customer reviews, founder posts on LinkedIn, honest answers in communities.
5. **Every month: measure.** Run the same prompts, compare with last month, and move budget to what is cited.

If you want outside help, see the best GEO agencies for B2B SaaS and the best SEO agencies for B2B SaaS, and what GEO costs before you talk to them.