Competitive intelligence
Benchmark how AI positions your company against competitors
Your competitors are in the room. Most GEO reports pretend they aren't.
When someone asks AI "what's the best tool for X," it doesn't evaluate you alone — it ranks you against three other names you've never seen. VeritasLinks shows you that head-to-head, not a single-brand snapshot.
Step 1 — Enter your website
Comparison-first, not single-answer snapshots
AI rarely evaluates brands in a vacuum
Models cluster, contrast, and rank when users ask for options. Isolated prompts miss the battlefield.
You need comparative intelligence: who owns the narrative when multiple names appear together.
Lenses
What benchmarking encodes
How models cluster and replace options when buyers ask for vendors.
Lens
Category ownership
Who models treat as the default answer.
Lens
Comparative mentions
Who appears beside you in shortlists.
Lens
Recommendation substitution
When another vendor replaces you in prose.
What you can benchmark
Matrix view
Signals under peer pressure
Every tile is comparative by design.
Competitor overlap when users ask for vendors
When someone asks "best tools for [your category]," who shows up next to you — and who shows up instead of you.
Category strength vs alternatives
Whether AI treats you as a leading option or lists you third, fourth, or not at all when the category gets named.
Repeated mention and recommendation patterns
Whether the same competitor keeps replacing you across different phrasings of the same question — a pattern, not a one-off.
Positioning stability across models and reruns
Whether ChatGPT, Claude, and Gemini agree on where you stand — or whether your ranking depends on which model someone happens to ask.
Recommendation pressure in head-to-head contexts
When a buyer asks AI to choose between you and a named competitor, which way the recommendation leans and how strongly.
Perception under comparison—where you lose strength
The specific claim or feature where a competitor's framing beats yours — so you know exactly what to fix first.
Audience
Who this is for
- B2B teams fighting in crowded categories — where five vendors all sound similar until AI picks one to recommend
- PMM and comms leaders who need share-of-narrative proof — a number to put in the board deck besides "we feel like we're winning"
- Agencies proving client lift against named rivals — show the client's ranking moved against the competitor they actually care about beating
- Execs who think in competitive moats, not vanity mentions — a mention isn't a win if AI recommends someone else right after it
What this looks like
A real comparative result
Query: “best payment infrastructure for marketplaces”
This is what isolated audits miss: you might score “well” on a single-brand snapshot, and still lose 9 times out of 10 the moment a real competitor enters the question. Benchmarking shows you the fight you're actually in.
Map where competitors outsell you in AI answers
Standalone audits hide the real fight
A report that never stresses comparison teaches you little about win rate when buyers ask “who should I pick?”
One-pass tools cannot show narrative dominance or repeated co-mentions with the wrong peers.
A score that changes every time you check it is not a score
Run a single-prompt check on Monday and Wednesday, and you can get two different answers — not because anything changed, but because that's how language models work. Without enough prompt volume, you can't tell the difference between "your visibility actually dropped" and "the model just answered differently this time."
VeritasLinks runs enough comparative prompts per check that the resulting score holds steady between runs — so when it moves quarter to quarter, you know it moved because something real changed, not because of normal AI randomness.
Discipline
Rerun stability
Unstable one-run
Stable multi-run band
Example pattern: a single-prompt check vs. VeritasLinks' multi-run benchmark, tracked over the same 4 weeks.
Why benchmarking beats a standalone GEO report
We anchor interpretation to competitor sets and comparative prompts—not vanity paragraphs.
AI Focus Groups add buyer-choice pressure when you need to explain why mentions do not convert to recommendations.
Built for comparison
Why teams benchmark here
Mirrors how buyers actually ask.
- Comparative prompts mirror real buying questions
- Dominance and overlap—not vanity mentions
- Stability across models and reruns
- Optional AI Focus Groups for choice dynamics
Start benchmarking your company
Immediate start—same funnel you trust from the homepage.
- →Same product path as the homepage — enter a public URL to start.
- →Structured interpretation, not a one-off chat screenshot.
Start
Run your analysis
We gather public context, then run comparable model reads.
Step 1 — Enter your website
Comparison-first, not single-answer snapshots
FAQ
Short clarifications — positioning and proof live in the sections above.
What is GEO benchmarking?+
It's measuring how AI describes you when a competitor's name is also in the question — not just when you're asked about alone. Most brands check "what does AI say about us" and stop there. Benchmarking checks "what does AI say when we're standing next to the competitor a buyer is also considering" — which is the question that actually decides who gets picked.
How does competitor benchmarking work in AI search?+
We run prompts the way real buyers actually ask them — "best X for Y," "A vs B," "alternatives to C" — across multiple AI models, then track who gets mentioned, who gets recommended, and who gets dropped when your name and a competitor's appear in the same answer.
Can I compare my company against known competitors?+
Yes. Tell us who you consider your real competitors (or we'll identify likely ones from your site), and every benchmark prompt is built around that specific competitive set — not generic category language.
Why is benchmarking more useful than a one-time audit?+
Because buying decisions happen in comparison, not isolation. A brand can look fine in a solo audit and still lose every real decision because a competitor's framing wins the head-to-head. Benchmarking shows you that losing pattern directly — and reruns let you confirm whether a fix actually closed the gap.
What does AI brand benchmarking reveal?+
Three things: which competitor AI defaults to recommending in your category, where your messaging loses to a specific competitor's framing, and whether that pattern holds steady across different AI models or only shows up on one.
Continue exploring
Relevant pages to go deeper into GEO strategy and platform capabilities.