GEO by category
GEO for ITDR companies:
how to show up when identity security teams ask AI
Your buyers, the identity and security leaders choosing an identity threat detection and response (ITDR) platform, increasingly build their shortlist inside ChatGPT, Claude, and other AI assistants before they talk to anyone. This is how AI answers form in a category still being defined, what the engines reach for, and what it takes for a company in this space to be in them.
GEO by category · Last updated
For the marketing leader at an ITDR or identity security company whose pages rank on Google but don't show up in AI answers.
When a security architect asks ChatGPT or Claude what ITDR is and which vendor to shortlist, the answer is assembled from the content those engines have already indexed and judged trustworthy, not from any vendor's homepage. ITDR is a young category, so those answers are still being written, which is the opening: the vendor whose content most clearly defines the category and where it fits becomes the reference the engines reach for. Getting into that answer is winnable independently of Google rank, but it runs on different signals: content structured to be extracted, real detection specificity for a skeptical security architect, and a credible presence in the analyst coverage and security channels this buyer reads. Resonate Labs maps how AI answers form in a category, finds where a vendor is left out, and does the work that changes it.
Buyers shortlist inside AI
Identity and security teams research ITDR in ChatGPT, Claude, and other AI assistants before they ever fill out a form. The shortlist forms there, before sales hears about the deal.
Ranking isn't citation
You can top Google for "ITDR" and never appear in the AI answer. Citation runs on signals a ranking-focused program rarely produces.
The category is still forming
Buyers are still asking what ITDR is and how it differs from EDR, PAM, and ISPM. Whoever answers that clearly, in the engines, becomes the default reference before the category consolidates.
How identity security teams research ITDR in AI
The buyer here is a security committee, not one person. A CISO owns the budget, an identity or IAM lead champions the purchase and owns the identity stack, and the security architect or SOC analyst who would run the tool renders the real verdict. That last reader is deeply skeptical of marketing and fluent in the adjacent tools they already own. Whatever shows up in the AI answer has to survive that scrutiny, and it has to clear a bar most categories don't: proving the category is worth a separate line item at all.
Their research moves through stages, and in ITDR the earliest stage carries more weight than usual. It starts with the problem and the category itself, "how do we catch identity attacks our EDR misses," "what is ITDR," "do we need ITDR if we already run PAM and an EDR," "how is ITDR different from ISPM." It narrows toward a shortlist, "the best ITDR platform," "identity threat detection for Active Directory and Entra ID," and then sharpens into comparison, "ITDR versus extending our XDR," "alternatives to the identity module our EDR ships," and finally validation, "which identity attacks does it actually detect," "does it cover on-prem AD and cloud identity," "what does the response workflow look like." Half of B2B software buyers now start this kind of research in an AI assistant rather than a search bar.
The part most vendors miss: by the time the buyer types a shortlist query, the engine has already formed its answer from content it indexed long before. You are not competing for that buyer's attention in the moment. You are competing for it in the material the engine read weeks earlier, including the explainer that taught the engine what ITDR even is.
What gets an ITDR company cited
Engines reach for content they can lift and trust: specific, well-structured, and genuinely useful to the person asking. For this buyer, that means a recognizable set of formats. A clear account of what ITDR is and where it sits alongside EDR, PAM, ISPM, and the identity provider, since the buyer's first job is placing the category. Honest comparisons against the adjacent tools a security team already owns. Concrete detection detail on the identity attacks you catch, from Active Directory and Entra ID attacks to token theft, MFA fatigue, and OAuth abuse. And analyst-aligned framing, because this is a category the analysts named, so the language the engines learned it in matters. The classic SEO levers, backlinks and domain authority, are among the weakest predictors of whether you get cited, which is why a smaller vendor can win this even against larger players.
There is a trap specific to this category. Because ITDR is a newer category whose boundaries are still contested, generic "what is ITDR" posts are everywhere, and most of them just restate the analyst framing word for word. So a newcomer that publishes one more definition-only explainer is, in effect, feeding the machine a paragraph it already has a hundred copies of. Restating the category is not the same as earning a citation in it.
Earning your own citation means saying something more specific than the definition: exactly which identity threats you detect and how, where you fit for a team that already runs an EDR and a PAM, what your response actually does when an identity is compromised. Specificity is the craft, and it is the same craft whether the buyer or the engine is reading. How to structure content AI will cite covers the formats that get extracted.
Which AI platforms matter most for this buyer
You cannot optimize for "AI" as one channel, because the engines diverge in what they cite, and the mix that matters for a security buyer is not the consumer headline. ChatGPT has the broadest reach and is most buyers' default starting point. But for a technical security audience, Claude punches above its overall consumer share with researchers and engineers, so the people evaluating your product may work in it daily. Perplexity skews toward research, and Google's AI Overviews are hard to avoid for anyone who still starts a question in Google search. This same audience weights analyst coverage, vendor threat research, and security communities more heavily than a non-technical buyer would, so the sources these engines pull from for this category, Gartner and Forrester notes, security blogs, and the identity and security subreddits, skew toward places marketing rarely invests.
The practical consequence is that optimizing for one engine does not automatically cover the others. They read different sources and reward different content, so visibility has to be measured per engine rather than collapsed into a single number. Why AI engines cite different sources goes deeper on the per-platform differences, and how we measure GEO results covers tracking each engine separately.
What a skeptical identity-security buyer needs to see
This buyer trusts evidence, not adjectives. What earns belief is concrete detection coverage, named identity attack techniques you catch rather than a claim to stop "identity threats" in general, clear integration with the identity stack they already run across Okta, Entra ID, on-prem Active Directory, and Ping, a real response workflow rather than detection that only fires an alert, honest scoping against the EDR, PAM, and ISPM tools they already own, and deployment detail an architect can picture. None of that is marketing language. It is the substance a security architect was going to ask about anyway.
What kills credibility is the opposite: a vague "AI-powered" claim with no mechanism, category word salad that never says which threats you actually detect, and coverage claims with no attack specifics behind them. Here is the useful part for GEO: the same specificity that convinces the architect is what gets the page cited. The engine and the buyer reward the same thing. Writing for the skeptical reader and writing to be cited are not two jobs.
Where Resonate Labs fits
This is the work Resonate Labs is built to run. We start by mapping how buyers in a category actually research, the questions they ask AI across the journey, then we find where the engines leave a given vendor out of the answer. From there it is content and earned presence built to the standard this buyer respects, measured against the AI answers themselves rather than against search rankings. The approach is the same one this page describes, applied to your specific position instead of the category in general.
We work category by category because the buyer, the questions, and the sources that matter are different in each one. ITDR rewards category-defining clarity, honest boundaries against the adjacent tools, and real detection specificity; another category rewards something else. If you want to see how this maps to a head-to-head against a specific competitor, how we compare GEO options covers that. If you want to see where your own company stands today, that is a review, not a reading.
Frequently asked questions
How does an ITDR company get cited by ChatGPT or Perplexity?
Engines assemble their answers from the sources they have indexed as authoritative, then prefer content that is specific, well-structured, and easy to extract. For an ITDR vendor that means clear content defining the category and where it sits alongside EDR, PAM, and identity providers, honest comparisons a skeptical security architect believes, detection detail on the identity attacks you actually catch, and a credible presence in the channels this buyer reads, from analyst notes to security communities and vendor threat research. Backlinks and domain authority, the classic SEO levers, are among the weakest predictors of whether you get cited.
We rank for "ITDR" and "identity threat detection" on Google but aren't in AI answers. Why?
Ranking and citation run on different signals. A page can sit at the top of Google and still never appear in the answer a buyer reads in ChatGPT, because the engine is looking for content it can lift and trust, category explainers, comparisons, and real detection detail, not a page that climbed a results list. The gap is usually structural: the content isn't written to be extracted, or the brand isn't present in the analyst coverage and security communities the engine reads before it answers.
Can a newer ITDR vendor get cited alongside the established security players in AI answers?
Yes, and ITDR makes it more winnable than most categories. AI citation is less anchored to domain authority than Google rankings are, and because ITDR is still being defined, the answers to "what is ITDR" and "how is it different from EDR or PAM" are not yet locked to any one vendor. A smaller company that explains the category clearly and backs it with real detection specifics can become the reference an engine reaches for. The catch is that generic "what is ITDR" posts that just restate the analyst definition are everywhere, so restating the category is not the same as earning a citation in it.
What content gets an ITDR company cited by AI?
The content this buyer actually consults: a clear account of what ITDR is and where it fits alongside EDR, PAM, ISPM, and the identity provider, honest comparisons against the adjacent tools a buyer already owns, and concrete detail on the identity attacks you detect and respond to, from Active Directory and Entra ID attacks to token theft, MFA fatigue, and OAuth abuse. Specificity beats polish for this audience. A precise account of which identity threats you catch and how you respond earns more trust, and more citations, than a claim to be AI-powered with no mechanism behind it.
Which AI platforms matter most for identity security buyers?
ChatGPT has the broadest reach and is most buyers' default, but for a security audience the mix shifts: Claude over-indexes with technical and security researchers, Perplexity skews toward research, and Google's AI Overviews catch anyone who still starts in Google search. This audience weights analyst coverage, vendor threat research, and security communities more heavily than a non-technical buyer would. Because the engines diverge in what they cite, optimizing for one doesn't automatically cover the others, which is why measurement runs per engine rather than as a single AI number.
See where you stand
The one thing this page can't show you is where you stand.
This page covers how AI answers form in ITDR. What it can't show you is your own position. Start with a free AI Visibility Snapshot for a no-commitment read on where you stand; the full AI Visibility Crawl measures exactly where you're cited and where a competitor wins, scored across every engine:
- The buyer questions your category turns on, run against ChatGPT, Claude, Gemini, and Perplexity
- Where you're named, cited, or absent, scored across every engine
- A prioritized plan for what the first 30 days would move