GEO for B2B: How to Get Into AI Shortlists
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Generative engine optimization for B2B means getting your company named when buyers ask AI for a vendor shortlist. Write down the shortlist questions your buyers ask, run each one several times per engine, and record who is named and what the answer cites. Then fix the material those answers rely on, one change at a time.
The difficulty in B2B is that the four main engines do not read the same things. We asked three shortlist questions on ChatGPT, Perplexity, Gemini and Google’s AI Overviews, three times each, and the answers were built from completely different material: one engine cited vendor websites almost exclusively, another cited only third-party roundups, and a third showed no sources at all.
How B2B buyers use AI before they contact you
A buyer with a problem now opens an AI assistant and asks for options before visiting any vendor site. The answer they get is a shortlist of a few names with a sentence on why each fits. If you are not in it, you are not in the evaluation, and you never see the enquiry you did not get.
Getting into those answers is what generative engine optimization for B2B means in practice. Our explainer on the difference between AEO and GEO covers the terms; for B2B, what matters is the mechanics below.
What makes B2B different from consumer AI search
Buyers ask for a shortlist, not a product page. Buyers ask “best [category] for [company type]” or “how do I choose a [category] tool”. The answer is a comparison, so you are judged next to named competitors in the same sentence.
Several people read the answer. A shortlist gets pasted into a Slack thread or a procurement doc, so one answer reaches the whole buying committee. See how buying teams compare vendors.
The material is spread across the web. Review sites, comparison posts, agency roundups and your own documentation all feed the answer, and the mix differs by engine.
What 36 AI answers show about B2B shortlists
How we ran it
On 20 October 2026 we asked three questions on ChatGPT, Perplexity, Gemini and Google’s AI Overviews, three times each in a fresh session, from Singapore: “best AI visibility tools for B2B SaaS”, “best GEO agency for B2B” and “how to choose an AI search monitoring tool”. That gives 36 answers. For each one we recorded the vendors named, in order, and every source the engine cited. Memory and personalization were switched off where the engine allows it.
The category is our own, which is a limitation worth stating plainly: we know it well enough to read the answers, and we appear in none of them.
Who gets named, and how often
| Question | Named in all 12 answers | Named in 9 or more |
|---|---|---|
| best AI visibility tools for B2B SaaS | Profound | Otterly.AI (11), Peec AI (11), Scrunch AI (9), Semrush (9) |
| best GEO agency for B2B | Omniscient Digital | none |
| how to choose an AI search monitoring tool | Peec AI, Otterly.AI, Semrush | Profound (11), Ahrefs (9) |
Source: WaveWise study log, 36 answers, Singapore, 2026-10-20.
In each question one name appeared in all 12 answers. Below that, the lists diverged fast: across the three questions the four engines named 14 to 19 different vendors each, and two runs of the same question on the same engine shared only 62 to 79% of their names. A vendor outside the top one or two is in a lottery that it enters a few times out of twelve.
What the engines cited
| Engine | Vendor websites | Third-party roundups | No sources shown |
|---|---|---|---|
| ChatGPT | 5 of 9 | 1 | 3 |
| Perplexity | 0 | 9 of 9 | 0 |
| Gemini | 0 | 0 | 9 of 9 |
| Google AI Overview | 3 | 4 | 3 (partly) |
Source: WaveWise study log, 36 answers, Singapore, 2026-10-20. Counts are per answer, by the type of source cited.
When ChatGPT named vendors, it mostly linked their own sites. Perplexity never linked a vendor site in nine answers: every source was a third-party comparison or roundup, and one answer also cited LinkedIn and USA Today. Gemini named vendors confidently and showed no sources at all, so there was nothing to click and nothing to fix directly. Google’s AI Overview sat in between.
What it means
There is no single fix that works across engines. If you only improve your own site, you are working on what ChatGPT reads and ignoring what Perplexity reads. If you only chase roundups, the reverse. And for Gemini you cannot see the inputs, so the only honest approach is to measure appearance rates over repeated runs, as in our guide on how to track brand mentions in AI search.
Limits: one day, one location, one category, three questions, three runs each. These numbers describe what we observed, not a rule for every B2B market.
Build your shortlist question set
Five to ten questions is enough to start. Take the wording from places where buyers already describe their problem.
| Question type | Example | Where to get the wording |
|---|---|---|
| Category plus fit | best [category] for [industry or company size] | Your own category page, G2 or Capterra category names |
| Head to head | [your brand] vs [competitor] | Sales calls, lost-deal notes |
| Selection help | how to choose a [category] tool | Support tickets, onboarding questions |
| Problem first | how do I fix [problem your product solves] | Search data, customer interviews |
| Budget or scale | [category] for small teams, or for enterprise | Pricing objections |
Run a baseline, then read the answers
Ask each question three or more times per engine, in a fresh session, from the market your buyers are in. Record the vendors named in order, the sources cited, and how your brand is described when it appears.
Then read for the reason behind each name. For every answer where you are missing, write one sentence to act on: the answer relied on X, and X does not say Y about us. Keep what you observed separate from what you are inferring.
Fix what the answers rely on
Your own pages. Comparison pages, pages for specific industries or company sizes, visible pricing or at least a pricing logic, and documentation a model can read. This is what ChatGPT leaned on in our runs.
Third-party pages. Your profile and category placement on review sites, inclusion in the roundups that already rank for your shortlist questions, analyst and press mentions. This is what Perplexity leaned on, exclusively.
What not to do. Do not buy reviews, do not pay for “guaranteed AI recommendations”, and do not spin up thin comparison pages about competitors. Google says optimizing for its generative AI features is still SEO, and lists tactics you do not need, including llms.txt files and AI-specific markup (Google Search Central, read 2026-10-19). Nothing in our data suggests shortcuts outperform being accurately described in the places answers already read.
Verify: shipped, seen, and whether the shortlist changed
Check three things separately. Did the change go live? Has the engine read it, which you can see when the updated page or roundup starts being cited? And did your appearance rate across repeated runs move? These are the three levels of verification we use. Given how much the lists varied between runs, compare appearance rates across a set of runs, never two single answers.
If the result is unclear, that is a legitimate outcome, and usually means the change was too small or the sample too thin. Record it with the context and evidence either way, so the next decision starts from what you learned. That is the idea behind Decision Memory.
For the full six-step method, see how to improve brand visibility in AI search.
Where WaveWise fits
WaveWise Business starts from the shortlist questions your buyers ask, reads the answers across engines, and records who was named and what each answer relied on. That becomes a baseline for one approved change and a re-test.
A measurement describes the answers during the window in which it was taken, and answers vary between runs, so it is a starting point for decisions. WaveWise does not guarantee that your brand will be recommended every time.
If you want a baseline on your category’s shortlist questions, request a Pilot.
FAQ
Does GEO work for B2B categories with low search volume?
Yes. A buyer asking an AI for a shortlist is close to a decision, so a handful of these questions can matter more than high-volume informational traffic. You measure appearance rate in answers, not clicks.
Which engines should B2B companies track?
The ones your buyers use, which you can ask them directly. Track each separately: in our 36 answers the same question produced different vendor lists and different sources on each engine.
Do review sites matter more than my website?
It depends on the engine. In our runs Perplexity cited only third-party pages, including review and roundup content, while ChatGPT mostly cited vendor sites. Both need to be accurate.
How long does it take to appear in AI shortlists?
There is no fixed timeline. A change has to be crawled and indexed, then retrieved for your questions. Check that the engine has read the change before judging the result.
Is GEO for B2B the same as AEO?
The terms overlap and are often used interchangeably. See our explainer on the difference between AEO and GEO.
Facts checked: 2026-10-20 · Study data collected: 2026-10-20, Singapore