AEO & GEO Agency for B2B SaaS — Get Named as the Answer AI Gives

MentionBench is an AEO / GEO program built for B2B SaaS. We engineer your content, entity signals, and third-party presence so that when a buyer asks an AI engine which vendor to pick, the engine names you — and cites your pages as the source it trusted.

The outcome metric is share of answer: how often the engines name you on the prompts your buyers actually ask, across ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews. Not traffic. Not impressions. Share of answer, tied back to a pipeline record you can audit.

Looking for the right AEO agency for your company? Compare the broader AEO agency market in our Best AEO Agencies 2026 guide, or see our B2B SaaS AEO agency comparison if you're evaluating providers specifically for SaaS. Need a plain-language primer first? Read What is AEO / GEO vs SEO. Prefer the ROI framing? Read Why you need AEO/GEO.

Deliberate, not accidental

Most B2B SaaS brands that show up in AI got there by accident — a few well-placed blog posts, a recognizable category, a handful of third-party mentions. That accidental presence has a ceiling. The citations are inconsistent. The product descriptions are often wrong. And when a competitor invests deliberately, that accidental presence collapses.

We make AI visibility deliberate. You know which buyer queries matter. You know which sources the engines actually pull from in your category. You know which content assets create the citation. We build those assets, place those mentions, and track citation frequency against inbound pipeline — not a brand-awareness play, a measurable acquisition channel.

Who this program is for

  • B2B SaaS marketing leads, growth heads, and founders at companies with product-market fit (roughly $1M–$20M+ ARR) that want AI search to behave like a real acquisition channel with a number attached to it
  • Teams already hearing "I found you on ChatGPT" but unable to reproduce it consistently or attribute revenue to it
  • Companies running an existing SEO program and seeing diminishing returns as AI Overviews absorb more organic clicks — and ready to treat Google and AI as one system rather than two budgets
  • Teams that want citation and mention reported as separate numbers, because the two are not the same, and one blended metric hides which engine you're losing
  • Buyers who want a named methodology, published measurement, and receipts — not a strategy document and a disappearing act

What the work covers

We run one integrated program across every engine, because the entity signals, content architecture, and third-party citations that move one channel also move the other. Six modules, each aimed at a single outcome: making your brand the engine's confident recommendation for the queries that drive your pipeline. They organize into three phases — diagnose (module 1), build the site (modules 2, 3, 5), and source off-page authority (module 4) — with competitive tracking (module 6) running across all three.

Phase 1 · Diagnose.

1. Baseline AI visibility audit. We sample a broad set of your real buyer prompts across ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews and map exactly where you stand: who gets named, who gets cited, at what position, and which pages the models pull from. You get a starting share of answer and a citation map — your baseline and your internal business case.

Phase 2 · Build the site.

2. Answer-ready page engineering. We build answer-first pages that hand the engine a liftable unit in the first screen — a tight TL;DR, a hard-number table, a ranked roster. Engines quote pre-formatted units; prose-only pages get retrieved and passed over.

3. Citation-earning asset production. New comparison pages, use-case guides, and category content matched to the buyer prompts you're losing, plus query fan-out — mapping the long-tail question variations AI users actually ask and building captured content at scale. We don't just write; we structure for retrieval.

5. Entity & technical readiness. Schema markup (ServicePage, FAQPage, ItemList), knowledge-panel consistency, llms.txt, and AI-crawler access (OAI-SearchBot, PerplexityBot, ClaudeBot). This is where the structured data and entity language that let an engine resolve who you are actually get implemented. We verify crawlers can reach and parse your pages, and fix what blocks them, so you're ready before your category settles on an answer that isn't you.

Phase 3 · Source off-page authority.

4. Third-party authority sourcing. Placement on the third-party sources engines actually sample from: industry publications, high-authority listicles, review platforms (G2, Capterra), and community threads like Reddit. An engine can only cite a page that reaches its retrieved set — so we get you into the lists and communities the models pull.

Across all phases.

6. Competitive tracking & attribution. Continuous monitoring of how competitors are cited, which sources engines pull from, and when the citation landscape shifts — tracked per engine, never blended, and tied to pipeline week over week.

How we measure (cited ≠ named)

An engine can cite your URL and still name a competitor in the answer body. If we reported one blended number you couldn't see where the funnel breaks. So we split it:

  1. Mention rate — how often your brand is named in the answers for the tracked panel
  2. Citation rate — how often your URLs appear in the cited sources for that panel
  3. AI-referred traffic — sessions attributable to AI engines, identified by source and medium, reported transparently
  4. Pipeline attribution — AI-sourced sessions traced to demo requests and, where the data allows, to revenue

The headline number is share of answer, measured on the mention side only: how often your brand is named in the answer body, at what average position, split by engine, with the competitor split beside it. We keep citation rate as a separate track — a URL can be cited while a competitor is still named, so the two never blend into one score. We set expectations by surface honestly — Google AI Overviews can pick up a well-structured page within days; ChatGPT and Perplexity usually take weeks of consistent publishing; dominant visibility on a competitive cluster takes a quarter or more. The retest after an agreed window is accountability, not a guaranteed lift.

Why this works

Being named by an AI engine is a chain. The page has to be reachable (crawlers can get to it), extractable (an engine can lift the answer as a whole unit), trusted (authority signals say it's a source worth citing), and present in the corpus the engine retrieves from. We own every link in that chain — on-page structure, entity clarity, technical access, and off-page corroboration — rather than treating one link as the whole job.

That chain is also why AI and Google compound rather than compete. The technical health and domain authority that rank you on Google feed the pools engines retrieve from, and content built for topical authority on Google is structured to earn AI citations. Dropping SEO cuts the ground out from under AI visibility, which is why we run them as one program.

Pricing

Scoped to the gap. Pricing depends on tier, scope, and complexity, and every program starts with an audit so we can size the opportunity before quoting. After the foundation audit you get a fixed monthly proposal scoped to the goals in your roadmap. We do not publish a three-tier price wall, because the right scope is a function of what the audit reveals, not a product menu.

To anchor expectations: across the market in 2026, most serious B2B SaaS GEO and AEO retainers fall between roughly $3,000 and $15,000 per month (per the 2026 pricing guides cited by LoudFace), and programs like DerivateX's start with a 90-day pilot then run month to month. We position within that range and will give you an honest, fixed number on the call — plus an honest answer on whether the gap is even worth closing.

We start with a pilot so you can judge us on data, not promises. We'll tell you plainly whether a retainer is the right move, or whether you should keep the audit and a plan and run it in-house.

Typical questions before you hire

  • Is GEO the same as SEO? No. SEO competes to rank a link you click; AEO/GEO competes to be the answer the engine synthesizes and cites. The two overlap in content quality and domain authority, and they compound, but the citation sets barely overlap — ranking first on Google does not hand you the AI answer. We run both as one program.
  • How do you measure AI visibility? We track a set of your buyer prompts across the engines and measure how often you're cited, at what position, against which competitors — reported per engine, weekly. The core metrics are visibility, share of answer, and average position inside the answer, tied to branded search and pipeline.
  • Will you guarantee citations in ChatGPT? No, and walk away from anyone who does. AI answers return a different brand list more than 99% of the time on repeat runs, so tomorrow's exact citation is never guaranteed. What we control and grow is your consideration-set membership and your visibility rate over many samples. We measure it. We don't promise it.
  • How fast will we see results? Honest expectations by surface. Early visibility shifts can land in days on Google AI Overviews and within a day on Perplexity if you already have modest authority. A consistent slot in the cited set takes weeks. Connecting citations to demo requests and pipeline takes 90 to 180 days, depending on your baseline and deal cycle. We set 90-day goals and report against them.
  • Do I still need SEO if I invest in this? Yes. Every generative engine retrieves before it cites, so the technical health and authority that rank you keep feeding the retrieval pools. Dropping SEO cuts the ground out from under AI visibility, which is why we run them together.
  • Can my existing SEO agency just add this? Most traditional agencies added GEO to the service list without changing the methodology. If they're running the same content briefs and calling it AI optimization, the citations won't move. Ask them to show live AI mention data from a current client — if they can't produce it, you have your answer.
  • How does this report upstream? We connect visibility to pipeline. Monthly reports map citation gains to inbound sessions, demo requests, and revenue contribution — a board-ready attribution report, not a dashboard screenshot. Every percentage point has a source, a session, and a pipeline record behind it.

Next step

Email [email protected] with:

  • Your product / category and target market
  • Whether you have a buyer prompt list (or want us to propose one)
  • What you've tried so far (SEO retainer, content shop, a monitoring tool)

Suggested subject: AEO/GEO program — scope request

We'll come to the call with a read on your current AI visibility and an honest answer on whether the gap is worth closing.

Talk to us

Email [email protected] with your product, category, and what you have tried so far.