Why We Built Hertz: AI SEO Visibility Is the Channel Most SaaS Businesses Are Ignoring

Consider a scenario that is becoming increasingly common: paid search is performing well, organic rankings are solid, and a content team is publishing consistently. Then a prospect mentions they discovered a competitor through ChatGPT — and had never encountered your brand at all. This is not an isolated incident. It reflects an accelerating pattern throughout 2026, and it is precisely the challenge that prompted the creation of tryhertz.com.

Traditional SEO remains a viable and important channel. It is no longer, however, the only one that matters. Large language models — ChatGPT, Perplexity, Claude, and Gemini — now function as a primary discovery channel for B2B buyers and e-commerce decision-makers. At present, the majority of businesses have no visibility into whether they appear in those environments at all.The Problem Nobody Is Measuring

The gap between conventional search volume and AI-driven query volume is substantial — and inconsistently distributed in ways that challenge standard assumptions. “Search engine optimization services,” for example, attracts 90,500 monthly searches, yet generates only 30 AI-driven queries. That disparity is not a statistical rounding error; it signals a categorically different pattern of audience behaviour, revealing which topics LLMs are actively synthesising and which they are largely disregarding.

A significant number of businesses are currently optimising for the wrong signal. They are pursuing Google rankings on terms that LLMs rarely surface, while overlooking the terms where AI-generated responses carry the most weight. An AI health score of 55 out of 100 — the baseline at which many early tryhertz.com users arrived upon first connecting their sites — indicates near-invisibility across a substantial portion of the conversations that shape purchasing decisions.What Hertz Actually Does

At tryhertz.com, the platform was built specifically around AI SEO: tracking, measuring, and improving brand visibility within LLM-generated responses. The question the platform answers is not simply whether a brand is mentioned, but how it is mentioned, in what context, and in comparison to which competitors.

The core features at launch are as follows.

AI Visibility Tracking — Hertz monitors brand and domain presence across the major LLMs, surfacing where a business appears, where it does not, and what the AI asserts about it when it does appear. The underlying methodology is not web scraping; it is structured, repeatable, and produces comparable data across measurement periods.

Competitor Benchmarking — This capability tends to produce immediate attention in client presentations. Users can see precisely which competitors LLMs are recommending in preference to their own brand, on which topics, and with what framing. If ChatGPT is consistently presenting a competitor as the leading e-commerce platform for Shopify-based businesses, that pattern requires both identification and explanation.

Content Gap Analysis — The AI software maps the difference between what a business publishes and what LLMs are actually drawing on when forming recommendations. The relevant variable is not word count or keyword density; it is authoritative, substantive coverage of the topics that AI models have learned to treat as credible sources.

AI Health Score — A single composite benchmark that indicates where a business stands relative to AI visibility standards. tryhertz.com elected to build a composite score rather than a per-metric dashboard because, when both approaches were tested with early clients, the composite score produced faster internal decision-making. Executives act on single numbers; product teams prefer granular dashboards. The platform was designed for the decision-maker.Decision Debrief: Do We Build the Score or the Dashboard First?

During the initial product scoping, this question generated genuine internal disagreement. The choice was between launching with granular metric breakdowns — richer in data, slower to interpret — or leading with a single AI Health Score that was direct, fast, and immediately actionable.

The timeline was constrained: a six-week sprint to a shippable product. Client-facing teams initially resisted the composite score, concerned it would oversimplify a nuanced picture. When both versions were presented to five C-suite users, however, every participant responded to the dashboard by asking what the numbers meant they should do, while each understood the composite score immediately and without clarification. The score shipped first. The granular breakdown is now in development as part of V2, releasing this quarter.

One outcome that was not anticipated: the AI Health Score became the most effective acquisition mechanism on the platform. Prospective clients benchmark their own visibility before they have signed up for anything, which creates both engagement and a natural point of entry into the sales process.The Unresolved Question

One question remains without a clean resolution: to what degree is AI visibility a function of what a business publishes, what third parties say about it, and the training data cutoffs of individual models? The honest position in 2026 is that all three factors contribute — in proportions that are not yet fully understood. That uncertainty is precisely why measurement must precede any attempt at improvement, and it is the principle that shaped how Hertz was built.

For teams managing SEO for SaaS or e-commerce brands, the immediate priority should be establishing a baseline. Without knowing where your brand currently stands in AI-generated responses, any content or optimisation effort is operating without meaningful direction. tryhertz.com offers that baseline — and the ongoing measurement infrastructure needed to act on it with confidence.