We give every CMO
the gift of awareness —
and the tools to act on it.
ChatRank is led by Aaron Smith, a B2B SaaS product marketing leader with 20 years of experience at companies including IBM, Dell, and Forcepoint. An honest account of what we built, why we built it, and the methodology behind it.
The market is forming opinions about your brand. You are not in the room.
You are under pressure to prove not just that marketing performs, but that your company is being correctly understood by the market. As buyers increasingly turn to ChatGPT, Claude, Gemini, and other AI systems to research vendors, compare products, and shape purchasing decisions, a new executive reality is emerging: if your company is absent, mischaracterized, or consistently overshadowed by competitors in AI-generated answers, you are losing influence before a prospect ever reaches your website.
You are being asked to lead through AI disruption while simultaneously defending marketing's strategic value inside the organization — often with limited visibility into how these systems actually perceive your brand.
A measurable way to demonstrate leadership in the next layer of market perception.
Managing and improving your ChatRank score gives you something you desperately need right now: a measurable way to demonstrate leadership in the next layer of market perception. It transforms AI from a vague executive concern into a visible competitive advantage you can actively influence and report upward.
More importantly, because this capability becomes part of your strategic operating toolkit, it strengthens your personal value across roles and companies. Just as great CMOs once became known for demand generation, category creation, or brand transformation, the next generation will be recognized for knowing how to shape machine-mediated reputation — ensuring their companies are recommended, trusted, and discoverable in the AI systems increasingly guiding buyer decisions.
Five signals. Grounded in published research. Not vendor opinion.
Every ChatRank metric is grounded in peer-reviewed academic research on generative engine optimization (GEO), published platform documentation from the AI engines we measure, and quality frameworks including Google's E-E-A-T. The methodology is not proprietary theory. It is documented, defensible, and applied to your brand's specific competitive position. Rigorous enough for a data scientist to scrutinize. Actionable enough for a CMO to execute without one.
The percentage of AI-generated answers in a defined category where a brand is mentioned at least once. Measured across ChatGPT, Perplexity, Google AI Overview, and Claude using a standardized query set. The foundational number in every ChatRank engagement.
How frequently AI engines reference a brand's own content as a source when generating answers. Distinct from Share of Voice, which measures mention regardless of source. High Citation Density means AI treats your content as authoritative — not just your brand name.
The average position at which a brand is first mentioned within AI-generated answers. Position 1–2 carries significantly higher buyer influence than positions 3 and beyond. AI answers are not equal — first mention shapes the shortlist.
A ratio expressing how frequently a direct competitor appears in AI-generated category answers relative to your brand. A displacement score of 9× means the top competitor appears in AI answers nine times more often than you do. This is the urgency metric.
The month-over-month rate of change in AI Share of Voice. A positive Velocity confirms that AEO interventions are compounding. A negative Velocity is an early warning signal. The leading indicator that determines whether you are gaining or losing ground.
The methodology was built for one buyer. Not adapted for them.
B2B SaaS buyers have the highest-stakes, longest-consideration purchase journeys of any category. When a VP of Engineering asks ChatGPT to compare data pipeline tools, or a CFO asks Perplexity which compliance platforms are HIPAA-certified, the AI answer that comes back shapes a shortlist that may never change.
ChatRank was not built for e-commerce brands, local businesses, or personal brands. It was built for the B2B SaaS CMO navigating a $5M–$150M ARR company through a market where buyers are forming opinions before a sales conversation begins. Every benchmark, every query set, every recommendation reflects that specific reality.
We are our own first client.
ChatRank's own AI visibility score is continuously monitored. Every recommendation we make to clients — FAQ schema, entity optimization, citation-structured content — is applied to chatrank.us first. If a tactic doesn't move our own ChatRank score, we don't recommend it to clients.
This isn't a marketing position. It's an accountability standard. The most honest proof that AEO works is a company whose own AI visibility compounds in public, over time, with documented results anyone can verify.
Who runs ChatRank.
Aaron led product marketing execution and competitive intelligence at IBM, Dell, and Forcepoint — for data center services, cloud iPaaS, and cybersecurity. Across these roles he drove product positioning that made the right solution easy to find for every buyer, defined personas through extensive interviewing of internal and external stakeholders, and set the brief for the SEO teams responsible for making sure those products surfaced where buyers were searching. AEO is the same decision, asked of a new generation of search.
He holds a PMC Level III certification from Pragmatic Institute and an MBA in Marketing.
The ChatRank methodology is applied product marketing — the discipline of understanding how buyers form decisions and which signals influence them. The strategic advisory layer is not outsourced or optional. It is the product.
ChatRank is the integrated answer to both problems — the measurement platform and the strategic advisory in one engagement.
Why results take time — and why that's actually good news.
Most companies expect AEO to work like paid search — run a campaign, see results immediately. The reality of how AI engines work is different, and understanding it changes how you measure progress.
Google Search indexes your content in days. LLMs don't work that way. ChatGPT, Gemini, and Claude are trained on point-in-time snapshots of the web. Your content, your schema, your third-party citations — all of it needs to exist and be indexed before the next training run happens. Once it does, your signals flow into the model and your AI visibility can move significantly and quickly.
Perplexity is the fastest-moving signal in your ChatRank audit because it uses live web search rather than a training corpus. Movement there is visible within days of publication. ChatGPT and Gemini movement is measured in months — but when it moves, it compounds.
This is why ChatRank measures Visibility Velocity month-over-month rather than week-to-week. Clients who start the work early see the biggest gains — they are positioned when the training snapshot happens, not scrambling afterward.
The 90-day engagement is designed around this reality. Thirty days to establish the signals. Sixty days for early Perplexity movement. Ninety days positioned for the next LLM training cycle with every signal in place.
See where your brand stands
in 60 seconds.
The free ChatRank audit scans your brand across ChatGPT, Perplexity, and Claude and delivers your AI Share of Voice, Citation Density, and Competitive Displacement report by email. No account. No sales call unless you ask for one.
FIND YOUR CHATRANK →