How a B2B SaaS appears in AI recommendations, ChatGPT, Perplexity, Google

A B2B SaaS appears in AI recommendations not through a product feed but through three currencies, review presence on platforms the models trust (G2, Capterra, equivalents), repeated mentions in "best tools for X" articles, and fresh comparison pages the engines can cite in real time. ChatGPT picks you on brand authority and reviews, Perplexity on structured, citable pages, Google AI on structured data and classic SEO.

This article breaks the three engines apart for a SaaS founder. You will see where each one sources its information, what it specifically rewards for B2B software, what you change concretely, how fast results come and how to verify whether you appear. At the end there is a comparison table and a first step you can take this week.

The new discovery layer, the buyer asks the AI, not Google

The point where the purchase decision forms has moved. More and more B2B buyers no longer open Google or G2 to search "CRM for sales teams". They ask ChatGPT or Perplexity directly "what is the best CRM for a 10-person sales team" and get a short list of 3-5 names. That answer becomes the candidate set. If your name is not there, you are not in the running, no matter how good the product is.

This is the new G2/Capterra. The economic difference is brutal, in the old model, a buyer reading a comparison saw 15-20 options and you had a shot. In the new model, the AI filters down to 3-5 names before the founder even learns you exist. You lose consideration without ever appearing in a report.

The scale confirms it cannot be ignored. Perplexity processed 780 million queries in a single month (May 2025, figures reported by Perplexity), and ChatGPT launched its shopping feature on 28 April 2025, with recommendations built from reviews gathered across the web. On the behaviour side, several B2B buying studies put the self-directed share of the journey above two-thirds before a vendor is contacted directly. The decision forms where you are not present.

Why SaaS differs from e-commerce

If you have read how physical products appear in AI, half the advice does not apply to you. An online store has a product feed in Merchant Center, product schema, GTIN, price. A SaaS has none of these commercial structures. Your currency is different, review presence on recognised platforms, comparison content ("X vs Y", "Z alternative"), structured public documentation, and brand mentions in sources the model treats as credible.

In practice, a SaaS founder does not optimise a catalogue but a reputation distributed across the web plus a set of pages the engines can cite. The three engines demand different combinations of these ingredients, which is why a single tactic does not cover all three.

ChatGPT, you win through authority and reviews, not structure

ChatGPT answers, by default, from what it learned during training plus your brand reputation signals. When someone asks for "the best software for [job]", the model relies on what it has read about you across the web, aggregated reviews, comparison articles, "best tools for X" lists, Reddit threads and professional communities, editorial mentions.

What it rewards. Brand authority and consistency of mentions on trusted sources. If your name appears repeatedly, in positive context, in category listicles and on recognised review platforms, you become a natural candidate for your category.

What you change. You invest in presence on third-party sources, reviews on platforms like G2, Capterra or equivalents, inclusion in the "best [category] software" articles, credible presence in Reddit threads and the communities the model reads. It is reputation work over months, not a technical setting.

Watch the browsing mode. When ChatGPT browses live (search enabled), real-time retrieved pages come in alongside training data. At that point your comparison pages and documentation start to matter here too, exactly as with Perplexity.

Perplexity, you win through fresh, citable pages

Perplexity does not rely on what it memorised. It searches the web in real time, retrieves relevant pages and cites the sources directly in the answer. It is the fastest of the three to influence, a good comparison page published today can be cited within days.

What it rewards. Fresh, well-structured pages that are easy to cite. A short, factual answer at the top of the page, descriptive headings, clear comparisons, concrete data with a source. Perplexity looks for text it can cite with confidence.

What you change. You publish comparison pages ("[competitor] vs your product") and alternative pages ("[competitor] alternative"), because that is exactly what the buyer asks through AI. You put an extractable 2-3 sentence answer at the top of the page. You structure your public documentation with clear headings and tables. You keep pages updated, because freshness counts.

The golden rule for SaaS, for ChatGPT you write to be reputed, for Perplexity you write to be cited, for Google you write to be structured.

Google AI, you win through structured data and classic SEO

Google AI Overviews and AI Mode appear above classic results for complex questions. For a SaaS, with no commercial feed, these lean on what you already have, valid structured data on pages (Organization, SoftwareApplication, FAQ, Review where legitimate), domain authority and classic SEO signals.

What it rewards. Depth of content on category and comparison pages, correct schema markup, page relevance to purchase intent, domain authority and speed. In practice, quality SEO done on the right pages transfers directly into AI visibility.

What you change. You implement correct structured data, build category and comparison pages with real depth, keep basic SEO hygiene and internal linking. The difference from classic SEO, here you do not just want position 1 in results, you want to be the source the AI answer synthesises.

Comparison table across the three engines

Criterion	ChatGPT	Perplexity	Google AI
How it sources data	Training data plus brand reputation. Browsing mode adds live pages.	Live web search, real-time retrieval, with source citation.	Structured data from pages, domain authority, classic SEO signals.
What it rewards for SaaS	Brand authority, G2/Capterra reviews, mentions in category listicles.	Fresh comparison pages, alternatives, structured citable documentation.	Valid structured data, deep category pages, relevant SEO.
What you change	Gather reviews, get into "best X" articles, presence on Reddit.	Publish "vs" and "alternative to" pages, extractable answer up top, update often.	Implement schema, build comparison pages, keep SEO hygiene.
How fast results come	Months. Driven by accumulated authority.	Days to weeks. The fastest to influence.	Weeks. As long as indexing and authority re-evaluation take.
How you verify	Ask the natural question in ChatGPT and see if you appear, with and without browsing.	Ask the same question in Perplexity and check if you are among cited sources.	Search the question on Google and see if you appear in the AI answer up top.

What a SaaS founder changes concretely

The list is not endless. There are five levers, in order of effort against impact.

Get into category listicles. The "best [category] software for [segment]" articles are the number one source models read. Identify the ones already ranking for that query and earn inclusion, through editorial pitch, correct data or content partnership.

Earn reviews on recognised platforms. G2, Capterra and equivalents are the trust currency ChatGPT aggregates. A steady flow of recent, well-scored reviews makes you a natural candidate. A simple post-onboarding review request handles most of it.

Publish comparison and alternative pages. "[competitor] vs your product" and "[competitor] alternative" are exactly the queries the buyer asks through AI. These pages are quickly citable by Perplexity and rank well on Google.

Structure your public documentation. Clear, indexable docs with descriptive headings give the models text to cite about what your product does and who it is for.

Build presence in the communities the model reads. Reddit, niche forums, professional discussions. Not spam, but useful answers under the brand name, where your buyer is already asking.

The hidden cost, a pipeline that stalls with no visible cause

The loss appears in no report. The buyer who asks ChatGPT "what is the best software for X" and does not see you never reaches your site. So they do not show in Analytics, do not show in the demo form, do not show anywhere in your CRM. You see a pipeline thinning out, an acquisition cost climbing, but the rest of your channels seem to run the same.

For a founder used to reading everything in data, this is the most dangerous part, there is no alarm signal. The decision was made in a conversation with the AI that you will never see. The only way to detect it is to ask the buyer's question yourself and see who the model recommends.

Where you start this week

Run the test on all three. Ask the same natural buyer question ("what is the best software for [the job you solve], for a company the size of your typical customer") in ChatGPT, Perplexity and Google. Note where you appear, where competitors appear and where you are missing entirely. Three tests, five minutes, and you have the exact map of where you are invisible.

If you are missing from one or more, the fix differs by engine, per the table above. On Perplexity start with comparison pages, because they give the fastest results. On Google build category pages with structured data. On ChatGPT invest in reviews and listicle inclusion, slow but durable. As an AI-native agency, we do exactly this work for our own positioning before we do it for clients. If you want the full map of your presence across all three engines, the AI site audit walks it step by step. See also the complete SaaS marketing guide and the answer engine optimisation guide.