SEO, AEO, and GEO for B2B SaaS companies

AEO for B2B SaaS is the work of making a software company's pages and facts easy for AI assistants to find, cite, and recommend when buyers research software. It rests on SEO, because assistants that search the web draw their sources from search indexes. For software, the research points to four additions: exact public facts about price, plans, integrations, and security; honest comparison pages; accurate review-site profiles and open participation in communities; and measurement that treats AI answers as rates, not ranks.

This page is part of AEO HQ's guides by industry. It covers SEO, AEO, and generative engine optimization (GEO) together, as one practice that AEO HQ calls SEO+. Google's guidance on outside services uses both names for the same work, referring to "AI experiences (sometimes called AEO for 'answer engine optimization' or GEO for 'generative engine optimization')" (opens in a new tab) (official documentation). Facts on this page link to their sources, with evidence strength labeled where it matters, and recommendations are marked as ours. Most of the buyer data comes from surveys by review platforms, analyst firms, and software vendors, several of which sell into this market. The text says so each time.

Scope and definitions

This page is for marketers, founders, and revenue teams at companies that sell software to other businesses. It covers unpaid visibility in AI answers and the pages that support it. It does not cover advertising inside assistants or the AI features inside a product.

• B2B SaaS. Software sold to businesses as a subscription service.
• Answer engine. An AI system that answers a question in its own words and names or links its sources. Examples are ChatGPT, Gemini, Claude, Perplexity, Microsoft Copilot, and Google's AI Overviews and AI Mode.
• Retrieval. The step in which an assistant fetches pages from a search index while it writes an answer.
• Review site. A platform that publishes users' reviews of software, such as G2, Capterra, or TrustRadius.
• Comparison page and alternatives page. A page that compares named products ("X vs Y"), or one that lists options to a named product ("alternatives to X").
• Self-serve buying. Signing up, starting a trial, or paying without talking to a salesperson.

How software buyers use AI assistants

Most surveys of software buyers now find that a majority use AI assistants during research. The share depends on who was asked and how "use" was defined, so the table gives each figure with its sample.

Answers shape the shortlist. In G2's March 2026 survey, 69% of buyers chose a different vendor than they had planned based on an AI chatbot's guidance, and 33% bought from a vendor they were not familiar with (opens in a new tab). Shortlists are short: 83% of buyers shortlisted three or fewer products (opens in a new tab). In 6sense's survey of about 4,000 B2B buyers, 94% of buying groups ranked their preferred vendors before first contact and bought from that favorite 77% of the time (opens in a new tab) (intent-data vendor). A product that assistants leave out may therefore never reach the shortlist. That is an inference from the surveys, not a measured effect.

Buyers describe their situation and ask for comparisons. Comparing vendors' strengths and weaknesses is the most common use of AI chatbots in software research (41%) (opens in a new tab). In a U.S. survey of 519 B2B professionals who use AI, 61% describe their specific use case, 56% ask for direct vendor comparisons, and 45% add constraints such as budget, required features, or compatibility (opens in a new tab) (March–April 2026; the publisher sells search-marketing software). In the same survey, buyers noticed a vendor in an AI answer when it matched their use case (53%) or was described clearly and in detail (50%); 7% said brand recognition made them notice it (opens in a new tab).

Buyers check the answer. In a January 2026 survey of 1,862 technology buyers, 94% of those who use AI said they fact-check its answers (72% always or very often) (opens in a new tab). After an AI names a vendor, 71% visit the vendor's website (opens in a new tab), and 63% search for the company on Google, 46% compare it against alternatives, and 38% check reviews on G2 or similar platforms (opens in a new tab). They have reason to: 64% of software buyers encounter inaccurate AI chatbot recommendations often or very often (opens in a new tab), and 27% of AI-using B2B buyers say AI answers do not reflect real pricing or contract structures (opens in a new tab).

Scrutiny grows after the shortlist. In G2's June 2026 survey, evaluation became the longest stage of software buying (40% of the journey), and IT security review was the biggest source of delay after a vendor was chosen, cited by 39% of buyers and 50% of enterprise buyers (opens in a new tab). Finance involvement in software decisions rose from 31% to 46% in a year, and 49% of buyers said a CFO had vetoed an already-approved purchase in the previous 12 months (opens in a new tab).

Limits. All of these figures are self-reported, and several come from review platforms; G2 says its network includes Capterra, Software Advice, and GetApp (opens in a new tab), so its findings about review sites come from an interested party. Buyers recruited through review-platform panels may use AI more than other buyers (our assessment). The surveys also disagree on whether AI brings in unfamiliar vendors: G2 found that a third of buyers bought from a vendor they did not know, while 6sense, studying deals that averaged $300,000 to $400,000, found that 85% of buyers had prior experience with the vendors they evaluated (opens in a new tab). The direction of the evidence is consistent (moderate); the exact shares are contested.

How assistants decide which software to name

An assistant can answer from what its model learned in training, its parametric knowledge, or it can search the web and write from the pages it retrieves. A product launched after a model's training data was collected can appear only through search. In a test of 112 startups from the 2025 Product Hunt leaderboard, a model without web access named 5.4% of them at least once in discovery-style questions, and a search-based model named 27.7%; per question, the rates were 3.32% and 8.29% (opens in a new tab) (preprint; December 2025). Established brands start ahead: across 102 brands tracked from March to May 2026, household brands appeared in 73% of first answers to generic prompts, mid-market brands in 44%, and small brands in 11% (opens in a new tab) (preprint; the author co-founded the tracking platform studied).

Four findings describe what a software company can influence:

• Search rank carries into answers, partly. In an agency study of 10,000 finance and SaaS questions sent to GPT-4o, brands that ranked on page 1 of Google showed a correlation of about 0.65 with how often the model mentioned them, while backlinks showed weak or no correlation (opens in a new tab) (January 2025; method not disclosed, so weak). A peer-reviewed audit found that AI Overviews and Google's organic results shared only 18% of their sources (opens in a new tab). Rank helps; it does not decide the answer.
• Assistants cite other people's pages. Earned media is coverage a company does not control, such as reviews and editorial articles. In ranking-style prompts, ChatGPT drew 93.5% to 95.1% of the domains it cited from earned media, while Google's results drew more on brand-owned and social pages (opens in a new tab) (preprint; mid-2025). Across 149,912 citations from five assistants, 2.9% pointed to the tracked brand's own domain and about 21% to "best-of" lists (opens in a new tab) (preprint).
• Specific facts change which source is cited. In 252,000 controlled trials across six models, a stated price and a recent date raised a source's odds of being cited first in all six models, and specifications, comparisons, evidence, confident wording, and consistent claims did so in at least four (opens in a new tab) (peer-reviewed; laboratory setting; the authors work for a marketing software vendor).
• Small, checkable advantages can beat a famous name. In lab tests, a well-known brand won every choice when products were equal, but a fictional competitor won half the time with a 0.075-star rating edge, 1.6 times the reviews, or a 7.3% lower price (opens in a new tab) (preprint; consumer products, not software).

The only study we found of on-page factors, such as structured data, for B2B SaaS pages is weak: it used 70 B2B SaaS prompts and reported associations for metadata, freshness, semantic HTML, and structured data, but it scored only pages that had already been cited, and its authors co-founded a GEO vendor (opens in a new tab) (preprint). How ChatGPT, Gemini, Claude, Perplexity, and Copilot find and cite sources describes each assistant's index and crawlers.

The questions SaaS buyers ask

Questions software buyers put to assistants

Decision-stage prompts are the ones buyers use when they are close to choosing: pricing, comparisons, alternatives, and "best X for Y". The example wording below is illustrative; the evidence column shows how common each kind of question is.

What SaaS teams ask about AEO

In AEO HQ's keyword data for the United States, pulled on 27 September 2026, queries that combine AEO with SaaS or B2B software add up to about 1,520 searches a month across 30 queries. In AEO HQ's query research, B2B intent showed up mostly as a modifier, such as "for saas companies" or "b2b saas", on general AEO questions.

Question-form versions found on ranking pages add "which GEO agency is best for B2B SaaS companies?", "what should I look for when hiring an AEO agency for a B2B technology company?", and "how much does an AEO agency cost for B2B SaaS?" (same research). Volumes this low are estimates, so small differences between them mean little.

Which third-party sources carry weight for software selection

Buyers and assistants both lean on sources the vendor does not control, but not the same sources in the same proportions. Buyers say review sites weigh heavily in their decisions. The pages assistants cite most often in decision-stage answers are comparison pages, "best of" lists, and community threads.

The evidence suggests review sites work more like an entry requirement than a ranking factor. In an agency's test of "alternatives" prompts for well-known tools, every tool ChatGPT named had reviews on Capterra and 99% had reviews on G2, but some tools with strong review profiles ranked below tools with fewer reviews and weaker ratings (opens in a new tab) (the agency sells AI search services to SaaS companies and reported testing "dozens" of prompts without giving the number; weak). Established tools have reviews anyway, so the test shows that named tools usually have a listing, not that a listing causes a mention.

Your own site is where buyers check. In the decision-stage study, product pages and homepages appeared in single-digit shares of citations (opens in a new tab), yet buyers go to the vendor's site to verify, as the surveys above show. In ChatGPT's answers to software prompts, the recommended companies' own landing pages were cited in 37.2% of prompts, their own "best" lists in 34%, their homepages in 15.6%, and their documentation in 7.6% (opens in a new tab) (vendor study).

Our recommendations:

1. Keep one set of facts (product name, category, plans, prices, and integrations) identical on your site, every review profile, and every marketplace listing, so that assistants treat your product as one entity.
2. Ask real customers for reviews on the platforms your buyers use, within the rules on incentives and disclosure below.
3. Take part in communities under your own name, and say where you work. Google says "seeking inauthentic 'mentions' across the web isn't as helpful as it might seem" (opens in a new tab) (official documentation).
4. Earn a place in third-party lists by meeting their published criteria, and ask for corrections when a list states wrong facts about your product.

The evidence on brand mentions in general has its own guide.

Pricing pages and the verification step

Buyers want prices they can check, and many say AI answers get them wrong. Transparent pricing has been buyers' top wish-list item in TrustRadius surveys for four years running (opens in a new tab), and 27% of AI-using B2B buyers say AI answers do not reflect real pricing or contract structures (opens in a new tab). In an observational study, people validated AI answers on vendors' own sites and did not trust prices quoted by AI (opens in a new tab) (nine participants; weak); one participant worried about outdated sources or misleading ranges, such as "starting from" prices (opens in a new tab).

Prices are also getting harder to state. In G2's June 2026 survey, 49% of software buyers had been offered a variable-cost pricing option instead of a seat license or subscription, and preference for outcome-based pricing rose from 11% to 23% in a year (opens in a new tab). Buyers are starting to hand this reading to AI agents: among the uses of agents in software buying, evaluating total cost of ownership and building shortlists ranked first, at 51% each (opens in a new tab).

What a SaaS pricing page should state (recommendations, with the reason for each):

How to publish it (recommendations):

• Put prices and terms in the HTML the server sends. In December 2024, none of the major AI crawlers rendered JavaScript (opens in a new tab) (network measurement), and Bing says content that cannot be reliably rendered may not be indexed or selected as a source for AI answers (opens in a new tab) (official documentation).
• Do not leave prices only in images, PDFs, tabs, or calculators. Microsoft advises against hiding key answers in tabs or expandable menus, or leaving them only in PDFs or images (opens in a new tab) (official guidance).
• Keep the same numbers everywhere: review profiles, marketplace listings, documentation, and sales material. 69% of B2B buyers report inconsistencies between a supplier's website and what its sellers say (opens in a new tab), and in lab trials consistent rather than contradictory claims raised citation odds (opens in a new tab).
• Use structured data only to repeat visible prices. In a practitioner test, no AI system read facts that appeared only in JSON-LD (opens in a new tab) (one test page; weak).
• If you do not publish prices, say so plainly and state what the price depends on. No study has measured how publishing SaaS prices changes AI recommendations or conversion.

"Vs" and "alternatives" pages, done honestly

Buyers ask assistants for comparisons, and assistants cite comparison pages (see the tables above). Many of these pages are written by one of the vendors being compared. In one vendor analyst's count, 169 of 250 Google results pages for "best X software" queries (67.6%) featured a list in which the company that wrote it ranked itself first (opens in a new tab), and a self-promotional list appeared in more than a third of ChatGPT's software answers that recommended the list's publisher (opens in a new tab) (vendor study). One-sided lists carry risk: a practitioner analysis linked self-promotional "best of" lists to visibility drops at several brands from January 2026 (opens in a new tab) (weak). No study has tested whether assistants cite balanced comparison pages more than one-sided ones. The case for honesty rests on buyer verification, platform guidance, and the law.

Google's guidance on review content applies to comparison pages. Google says reviews can be written by "an expert staff member or a merchant who guides people between competing products" (opens in a new tab), and it advises writers to cover comparable options or explain which might be best for certain uses, discuss benefits and drawbacks based on their own research, support a "best" claim with first-hand evidence, and link to other useful resources, their own or other sites' (opens in a new tab) (official documentation).

How to write a comparison or alternatives page (recommendations):

1. Say who wrote it, at the top of the page: your company and the product it sells. Never describe a comparison page or site you control as independent (see the rules below).
2. Write only the comparisons buyers actually make. Take them from search data, sales calls, and the head-to-head questions above. Do not produce a page for every competitor from a template: Google says creating "separate content for every possible variation" (opens in a new tab) of how people search, primarily to manipulate rankings or AI responses, violates its scaled content abuse policy (official documentation).
3. State the criteria first: use case, price and pricing model, integrations, security, limits, and support.
4. Source every fact about the other product to that company's own pages, and show the date you checked it.
5. Say where the other product fits better, and link to its pages so readers can check your facts.
6. Re-check the facts on a schedule. We suggest every quarter and after any price change. Change the page date only when the content changes.
7. For "best [category]" lists, publish the selection criteria and mark your own product where it appears.

Rules that apply to reviews, comparisons, and chat assistants

The rules below limit some common SaaS tactics. This section summarizes official sources. It is not legal advice.

If you sell into regulated industries, such as health care or financial services, check those industries' rules on marketing claims as well.

Product-led and self-serve buying

Most B2B buyers say they would rather buy without a salesperson. In Gartner surveys of about 645 buyers (August–September 2025), 67% preferred a rep-free experience (opens in a new tab), and 70% preferred a completely digital, self-service buying experience, while 69% preferred to validate AI-generated insights with a sales rep (opens in a new tab). For technology, familiarity matters: when buyers were familiar with a product, 64% preferred a 100% digital buying experience (opens in a new tab) (148 respondents). Trials do not settle the sale: more than 60% of business buyers buy some form of trial, and just over a third planned to convert to a fully paid version with the same provider (opens in a new tab). Buyers ranked product demos, free trials, prior experience, and user reviews among the most influential resources when choosing a vendor (opens in a new tab).

Visitors who arrive from AI answers behave differently, but the evidence on sales is mixed. In March 2026, AI-referred visits to technology and software sites showed 30% higher engagement, a 40% lower bounce rate, 40% more time on site, and 23% more pages per visit than other visits (opens in a new tab) (analytics vendor's panel; no conversion figure for software). One software company reported that AI search sent 0.5% of its visitors and 12.1% of its sign-ups over 30 days, a sign-up rate 23 times that of organic search visitors (opens in a new tab) (single site; June 2025; the company sells SEO software). Across 973 e-commerce sites, ChatGPT referrals converted below organic search, paid search, email, and affiliate traffic, and above paid social only (opens in a new tab) (peer-reviewed; the data came from the first author's employer). No multi-site study of SaaS sign-ups or trials was found, so the evidence is contested.

Self-serve buyers answer their own fit questions from documentation, integration lists, and security pages. Our recommendations for those pages:

• Keep documentation, integration lists, and security information public and server-rendered. The rendering evidence in the pricing section applies here too.
• Say what AI features do. In 6sense's survey, 89% of purchases included AI features and 58% of buyers engaged sellers earlier to clarify missing AI details; the publisher found that most vendor websites do not clearly explain these features, from data sources and security to pricing and performance (opens in a new tab). In six experiments in consumer settings, including the term "artificial intelligence" in product descriptions lowered purchase intention (opens in a new tab) (peer-reviewed). Describe the data a feature uses, how it is secured, what it costs, and its limits, rather than relying on the label.
• Treat llms.txt as a documentation choice, not an AI search tactic. 97% of llms.txt files received no requests in May 2026, but Anthropic's coding agent requested them more often than any retrieval bot (opens in a new tab) (vendor server-log study). For API and developer products, documentation that coding agents can read may matter to users; the evidence does not show that it changes AI search visibility.
• Expect the purchase to happen on your site. 61% of software buyers use or plan to use AI agents in buying, but 9% are comfortable letting agents execute purchases within approved guardrails, and 2% without pre-approval (opens in a new tab). In ChatGPT, purchases that start in the chat are completed on merchants' own sites (opens in a new tab) (official announcement). The guide to how AI agents find and buy services covers agent checkout.

How to measure AEO for a SaaS company

Measure AI visibility as a rate across repeated runs, per assistant, with an error range, and connect it to sign-ups and pipeline through self-reported attribution. Single answers are unreliable: when the same prompt was repeated, AI assistants returned the same list of brands less than once in 100 runs (opens in a new tab) (2,961 runs; industry study; a co-investigator works for a tracking vendor).

Run the panel on the assistants your buyers use. In the U.S. survey cited above, product research ran on ChatGPT (71%), Gemini (61%), Microsoft Copilot (45%), Perplexity (18%), and Claude (14%) (opens in a new tab). If your CRM is HubSpot, AEO for HubSpot users covers recording AI referrals and self-reported answers there.

Change one thing at a time, and keep a control group of pages you did not change. In the only controlled field study found, ChatGPT referrals to pages that were not changed grew 3.5 times over the same period (opens in a new tab) (preprint; one site), so a before-and-after comparison without a control would have credited that growth to the changes.

How to do AEO for a SaaS company

These steps are recommendations. Each draws on the evidence in the sections above.

1. List the questions your buyers ask, in their words, from sales calls, support tickets, review-site questions, and search data. Group them by the question types above.
2. Make every important page reachable and readable. Allow the search crawlers, check that bot protection does not block them, and serve the facts in HTML.
3. Publish the facts buyers check: prices, plans, limits, integrations, security, and what AI features do, with dates.
4. Write one page per real question: use-case pages, comparison pages, and alternatives pages, each answering first and sourcing its facts.
5. Make third-party profiles match your site, and ask customers for reviews within the rules.
6. Take part in communities openly, under your own name.
7. Measure with a fixed prompt panel and self-reported attribution, and compare changed pages against pages you did not change.

Checklist for B2B SaaS

What the evidence shows and does not show

Antipatterns in SaaS marketing

Each antipattern below is common in software marketing and fails for a documented reason.

Frequently asked questions

Is AEO worth investing in for a B2B SaaS company?

Buyer behavior says the channel matters: half of B2B software buyers start their research in an AI chatbot more often than in Google (opens in a new tab), and 69% say AI guidance led them to a different vendor than they had planned (opens in a new tab). The returns are harder to measure: AI referrals are a small share of traffic, the evidence on their conversion is contested, and no study gives a time to first recommendation. In our view, the lowest-cost parts of the work, such as public prices, crawlable documentation, consistent facts, and honest comparison pages, also serve buyers who never use an assistant. Is AEO worth it? What the evidence says reviews the general case.

How much does an AEO agency cost for a B2B SaaS company?

Published prices vary widely. A software company that sells its own AEO product puts agency work at about $3,000 and up for a one-time audit or sprint, and about $9,000 to $15,000 or more a month for ongoing programs (opens in a new tab) (September 2026). One agency that sells to Series A to C SaaS companies publishes AEO retainers of $5,000 to $18,000 a month (opens in a new tab) (updated September 2026). AEO HQ's own fixed prices are under Next steps, and the index of what AEO costs compares published prices, each with its date.

Which AEO agency is best for B2B SaaS?

AEO HQ sells this work itself (see Answer engine optimization (AEO) services), so we have an interest, and we do not rank agencies. In AEO HQ's review of the Google results on 27 September 2026 for "answer engine optimization agency B2B SaaS", the results were agency service pages and "best agency" lists, most of them published by agencies or software vendors. In a published test of 48 AI answers about AEO agencies, almost every high-frequency source was an agency's own list that ranked itself first (opens in a new tab) (small sample). Judge an agency on its published prices, its measurement method, and what it will not promise; How to choose an AEO or GEO agency lists the questions to ask. Google says third-party tools "can't guarantee performance," and lists AEO and GEO tools among the services to evaluate critically (opens in a new tab) (official documentation).

What is the best AEO tool for B2B SaaS?

AEO HQ is not a software vendor and does not rank tools. The category is crowded: G2 listed 642 products in its AEO software category on 27 September 2026 (opens in a new tab). Measurement does not require a subscription. Search Console's generative AI report, Bing Webmaster Tools' AI Performance report, and GA4's AI Assistant channel are free, and a fixed prompt panel can be run by hand and logged in a spreadsheet, provided each prompt runs several times on each assistant. AEO and AI visibility tools compared covers the paid tools.

Does a G2 or Capterra profile get a product into AI answers?

Not by itself. In one agency's test, nearly every tool ChatGPT named for "alternatives" prompts had reviews on both sites (opens in a new tab), but the profiles did not decide the order, and review sites made up 1.1% of citations in a 102-brand panel (opens in a new tab). Treat a complete, accurate profile as a requirement, and earn mentions on comparison pages and in communities as well.

Can an early-stage SaaS company get recommended by AI assistants?

It can happen, mostly through search. Newly launched startups surfaced in 3.32% of discovery questions without web search and 8.29% with it (opens in a new tab), and small brands appeared in 11% of first answers to generic prompts (opens in a new tab). On Perplexity, the startups that were found had more referring domains and more Reddit presence (correlational). Start with specific questions where fewer established vendors compete, such as your exact use case and integrations: in one panel, specific queries gave more stable results across runs than broad ones (opens in a new tab).

How long does AEO take for a SaaS company?

No study has measured it. A 2026 review of 45 studies found no randomized, longitudinal, cross-platform field test of any white-hat GEO tactic, including none of time to first recommendation (opens in a new tab). Crawling alone takes time: Google says crawling a URL "can take anywhere from a few days to a few weeks" (opens in a new tab). Treat any promised timeline as a sales claim, not a forecast.

Next steps

AEO HQ sells this work at fixed, published prices, from a $499 automated audit to $8,995 for an audit, a plan, and technical implementation that includes analytics setup and a HubSpot attribution tie-in. See the prices and what each package includes.

Change log

• September 27, 2026: First published.