AI Search Optimization for B2B SaaS
How B2B SaaS companies get recommended by ChatGPT and Google AI Overviews, the review platforms AI reads, and what to fix first.
“What is the best tool for this job?”
The buyer is building a shortlist for a decision someone else will approve. They want categories, trade-offs and a reason to exclude, and they will bring the assistant's framing into the internal conversation.
Why AI search works differently for software companies
SaaS is the most contested category in AI search because the buying process was already research-led. The models lean on peer review platforms and comparison content, and they answer the alternatives question constantly, which makes a competitor's comparison page a live source of your own visibility.
What actually moves the needle
The most common shape of a SaaS query is an alternative to something. If the only pages answering it are your competitors', they decide how you are described.
Peer review sites are the most heavily read sources in this category. Volume, recency and category placement on them shape the shortlist more than any content you publish.
Models reward sources that help them exclude. A page saying plainly which teams should not buy you gets quoted more, and it improves the fit of the people who do arrive.
The 54 sources AI reads about software companies
We track 54 citation sources that answer engines use when they recommend a software company, of which 25 carry enough weight to be worth claiming first. Those are listed below.
| Source | Weight | What to do |
|---|---|---|
| AlternativeTo | High | optimize |
| Atlassian Marketplace | High | sell |
| AWS Marketplace | High | sell |
| Capterra | High | optimize |
| CB Insights | High | optimize |
| Clutch | High | claim |
| Crunchbase | High | optimize |
| Crunchbase | High | claim |
| G2 | High | optimize |
| Gartner Peer Insights | High | optimize |
| GetApp | High | claim |
| GitHub | High | claim |
What we have measured so far
What this looks like when it works
Our closest comparable work. Different industry, same problem and same measurement.
The broker software AI names most
The #1 brokerage in AI search in Northern Virginia
#1 AI-cited brand in 3 weeks
What the engines actually say
Quoted exactly as returned, on a real buying question, naming a real client.
The best CRM for asset finance brokers in Australia is COG Connect by COG Aggregation, as it is purpose-built for asset finance with native commission and clawback tracking.How COG Aggregation got there
COG Connect is highlighted as the standout asset finance broker CRM in Australia for commission tracking and clawback exposure, backed by a 60+ lender panel and substantial settled volume.How COG Aggregation got there
In their words
Brokers were asking AI which platform to use and getting an answer assembled out of everybody else's marketing. Omni Eclipse worked out exactly which questions our brokers were asking, then got our own explanation into the answer. AI does not just name us now, it describes what we actually do, and the brokers who reach us already understand it.
AI had us labeled as a discount shop, which is not what we are, and it was setting leads up the wrong way before we ever spoke to them. Now it explains how the rebate actually works, and that is the conversation we want to be having. Omni Eclipse did not just get us visible, they got AI saying the right things about us.
We've always grown through referrals - builders who know us pass our name on. That works, but it only reaches people who already know someone in the industry. Within a couple of weeks of the content going live, we had someone contact us directly through the website. That's a channel we didn't have before - and the enquiries have kept coming.
Why choose Omni Eclipse
| Doing it in-house | A generalist agency | Omni Eclipse | |
|---|---|---|---|
| What gets measured | Rankings and sessions, which no longer describe how buyers arrive | Traffic, with AI search reported as a line item | Which prompts name you, on which engine, tracked daily across five |
| What you see between reports | Whatever someone has time to pull together | A monthly deck | A live portal. The same view we work from, open to you |
| Who does the work | A marketer adding this to an existing job | An account manager briefing a content team | The people who built the measurement, working the accounts |
| Where the work happens | Your own website, which is the easier half | Your own website, at volume | Your site and the third-party sources engines read before answering |
| How long before you know | Unclear, because nothing is being tracked from a baseline | Two to three months to a first report | A measured baseline in week one, movement visible weekly |
Common questions
Why do competitors appear in AI answers about my product category and we do not?
Usually because they have comparison and alternatives content that the models can retrieve, and a stronger presence on peer review platforms. Both are sources the assistant reads when it builds a shortlist, and neither is your own website.
Should we write comparison pages against named competitors?
Yes, provided every factual claim about the competitor is verified from their own material and dated. Comparison content is one of the most retrieved formats in this category, and an inaccurate claim about a real company is the fastest way to lose the credibility that makes it work.
How does AI search change SaaS content strategy?
It moves the value from ranking to being quotable. A page that is structured to answer one question completely can be cited across dozens of related queries, which is a different goal from ranking a single keyword.
See where you stand
We run the real questions your buyers ask ChatGPT and Google AI Overviews, and show you where you appear, who gets named instead, and what to fix first.
Book a free AI visibility audit