GEO / AEO for AI-researched B2B SaaS
Your buyers ask ChatGPT before they ask Google — and most B2B SaaS companies aren’t in the answer.
I run the questions your prospects actually ask through the AI tools they actually use, document exactly who gets named and who doesn’t, and then fix it so you’re cited.
Buyer question
“What’s the best SOC 2 compliance software for a Series A startup with no security team?”
What the model returned
- Vantacited
- Dratacited
- Secureframecited
- Your productnot mentioned
The problem
Why this is happening now
Buyers start in the model, not the search bar
Research that used to begin with a Google query now begins with “best tools for X” or “A vs B” typed into ChatGPT, Perplexity, or Gemini. The answer comes back as a short list — not ten blue links you can work your way down.
A few incumbents already own those answers
In most comparison-heavy categories, the same handful of well-funded names get named every time. That's not an accident of ranking; it's what the models were trained and grounded on.
If you're not on the list, you're not in the deal
The AI answer is now the first touchpoint, before a prospect ever reaches your site. You can rank first on Google and still never enter the consideration set.
How the audit works
Evidence first. Every step is something you can check yourself.
- 01
I build the real question set
Not keywords. The bottom-funnel questions your actual buyers type: category picks, head-to-head comparisons, pricing and implementation questions, objection questions. Typically 30–60 prompts, written from your ICP and your sales conversations.
- 02
I run them through the AI tools your buyers use
ChatGPT, Perplexity, Gemini, Claude, and AI Overviews — run individually, with sources captured. I record every brand named, in what order, and which pages the models cited to say it.
- 03
You get a documented gap against a named competitor
A report with the raw answers, not a summary of them. Question by question: who got mentioned, who didn't, which of their pages earned the citation, and what those pages have that yours doesn't.
- 04
I fix the gap so you get cited
Content and structure changes aimed at the sources models actually pull from: comparison and alternatives pages, structured answers to the exact questions, third-party surfaces and listings, schema and crawlability. Then we re-run the same question set and measure the change.
Sample prompts from a compliance-SaaS question set
- > best SOC 2 automation platform for a 30-person startup
- > Vanta vs Drata for a company that already has ISO 27001
- > cheapest way to get SOC 2 Type II in 90 days
- > which GRC tools have a real API
Who this is for
This works for a specific kind of company.
Good fit
- Seed to Series B B2B SaaS, roughly $2M–$20M ARR
- A researched purchase, not an impulse one — $15k+ ACV
- A named competitor already showing up in AI answers
- A Head of Growth, VP Marketing, or founder who owns search spend and can decide without a committee
Not a fit
- Self-serve products bought in under ten minutes
- Categories nobody researches with an AI tool
- Anyone looking for a monthly content quota
Right now most of my work is in compliance and security SaaS — SOC 2, ISO 27001, GRC. It’s the sharpest version of the problem: technical buyers, urgent and unfamiliar purchases, and a few incumbents named in nearly every AI answer. The method isn’t specific to that category, it’s just where it’s clearest.
What you get
Three things, and nothing padded around them.
The audit report
Your question set, the verbatim AI answers, every brand mentioned, every source cited, and your visibility scored per question against one named competitor. Raw data included, so you can re-run it yourself.
The fix roadmap
A prioritised list of specific changes — named pages to write or rewrite, specific third-party surfaces to appear on, structural fixes — ordered by how directly each one feeds the citations you're losing.
Ongoing GEO work
Monthly: execute the roadmap, re-run the same question set, and report the movement. Same measurement every time, so progress is a number rather than an opinion.
Proof
Case studies coming soon.
Sprung AI is new, and I’d rather show nothing than show something invented. Client results will be published here as engagements produce measurable before-and-after data on the same question set. Until then, the audit itself is the proof — you see the raw answers before you spend anything.
Case study slot
Category, starting visibility, changes made, visibility after re-running the same question set.
Case study slot
Category, starting visibility, changes made, visibility after re-running the same question set.
About
Who you'd be working with.
I’m the only person here. You talk to me, and I do the work — no account manager in between, no junior running the prompts.
I got into this because I kept watching the same thing happen: a company doing everything right on search, still absent the moment a buyer asked an AI tool which vendors to look at. The answers were being decided somewhere else entirely, and almost nobody was measuring it.
So I started measuring it — running real buyer questions, recording what came back, and tracing the citations back to the pages that earned them. That’s the whole business: find out what the models say about you today, and change it.
Find out what AI says about you today.
Book a 30-minute call. Bring one competitor you think is winning AI answers, and I’ll run a first pass on your category before we talk.
Or email me directly: hello@sprung.ai