# How to Get on the Vendor Shortlists AI Writes (B2B SaaS)

> We asked four AI engines five 'best tools for' questions B2B buyers ask. Each agreed on two to four vendors and differed on the rest. What the shortlists drew on, and what a SaaS vendor can change.

- Author: Sheetal Shakshi, Founder's Office, Nurdd
- Published: 2026-11-05
- Publisher: Noma by Nurdd (https://nomahq.app)
- Original page: https://nomahq.app/blog/get-on-ai-vendor-shortlists

**To get on the vendor shortlists AI writes, make sure the sources AI engines read connect your product to the buyer’s exact question: the comparison articles and directories they cite, and your own pages for each use case. When we asked four engines five B2B shortlist questions, they agreed on only two to four vendors per question and named the rest differently.**

B2B buyers now ask AI assistants for a shortlist before they visit a vendor’s site: “What are the best CRM tools for a 10-person sales team?” This guide shows what those shortlists looked like when we asked, what they drew on, and the steps a SaaS vendor can take.

## What we asked, and what came back

On 5 November 2026 we asked five shortlist questions of ChatGPT, Gemini, Claude and Perplexity, using the same models Noma’s free tools use, with no extra instructions. Gemini failed on the CRM question, so there are 19 answers. In this setup only Perplexity searched the web and listed sources; the other three answered from what their models already knew.

| Question | Vendors named by every engine that answered |
| --- | --- |
| Best CRM tools for a B2B SaaS startup with a 10-person sales team | HubSpot, Salesforce, Pipedrive, Close (3 engines) |
| Best customer support software for a 50-person B2B SaaS company | Freshdesk, Intercom |
| Best product analytics tools for a B2B SaaS product team | Mixpanel, Amplitude, Heap |
| Best project management tools for a remote B2B engineering team | Jira, Asana |
| Best AI visibility (AEO) tools for a B2B SaaS marketing team | Semrush, Ahrefs |

Three things stood out:

- **A small shared core, then divergence.** Every engine named the vendors above; beyond them, each engine’s list was different, and many vendors were named by one engine only.
- **Search changes the list.** For AI visibility tools, Perplexity, which searched, named dedicated vendors such as Peec AI, Otterly.AI, Profound, Scrunch, AthenaHQ and Goodie. ChatGPT, Gemini and Claude, answering without search here, named SEO and content suites. None of the four named Noma by Nurdd.
- **The sources were mostly not the vendors.** Perplexity cited 18 to 22 links per answer. Most were third-party lists, other vendors’ blog posts and agency articles; the recommended vendors’ own pages made up a few of them, and for the AI visibility question none.

This is a small test: five questions, one day, one setup. Answers change from run to run, so read it as a picture of how shortlists form, not a ranking.

## What do AI vendor shortlists draw on?

Two things: what the model learned during training, and the pages it finds when it searches. The first favours vendors that have been widely written about for a long time, which may be why the shared core in our test was made of well-known names. The second is where a smaller vendor can move: if the comparison articles, directories and review pages an engine finds for the question include you, described for that buyer, you can appear in the answer. See [how AI engines choose citations](https://nomahq.app/blog/how-ai-engines-choose-citations).

## Six steps to get on the shortlist

### Step 1. Find the shortlist questions buyers ask

List the 'best X for Y' and 'which X should I use' questions for your category, with the qualifiers buyers add: team size, budget, industry and stack.

The free [AI prompt finder](https://nomahq.app/tools/ai-prompt-finder) builds a list of these questions from Google search data for your category, and our guide on [which prompts to track](https://nomahq.app/blog/which-prompts-to-track) covers how many to start with.

### Step 2. Ask them in every engine your buyers use

Record which vendors each engine names, in what order, how it describes them and which sources it cites, because engines agree on a few names and differ on the rest.

Engines can name different brands for the same question; see [why AI engines disagree](https://nomahq.app/blog/why-engines-disagree).

### Step 3. Publish pages that answer the shortlist question

Give each use case and buyer type its own page that says plainly who you are for, with prices, limits and integrations in the HTML, so an engine can match you to the qualifier in the question.

A page called “CRM for small sales teams” with your seat price and limits answers the qualifier in the question. A homepage tagline does not.

### Step 4. Get onto the lists the engines read

Find the comparison articles, directories and review pages cited for your questions and make sure you are on them, described accurately and up to date.

In our test, most of Perplexity’s sources were third-party pages. Being on the right ones, with current facts, matters as much as your own site.

### Step 5. Keep comparisons honest and current

Publish dated comparisons against the vendors engines already name, with sourced figures, so your page is a fair source for the question buyers ask.

Buyers ask engines to compare you with the vendors already on the list. A sourced, dated comparison gives the engine a fair page to draw on; see [how we write ours](https://nomahq.app/compare).

### Step 6. Measure the shortlists over time

Re-ask the same questions on a schedule and track how often you are named, your position and which competitors appear instead.

Track the same questions monthly, per engine. Our [citation lifespan data](https://nomahq.app/blog/ai-citation-half-life) shows why one check is not enough.

## For B2B SaaS teams

Our [AEO for B2B SaaS page](https://nomahq.app/industries/b2b-saas) covers the questions SaaS buyers ask and what to track. To see whether AI engines put you on the shortlist today, run a free [brand audit](https://nomahq.app/brand-audit): Noma by Nurdd asks the engines the questions your buyers ask and shows where you are named, where competitors are named instead, and which sources the answers cite.