An AI visibility score is quickly becoming a useful diagnostic for marketers who want to know whether ChatGPT, Gemini, Perplexity, and Google’s AI-powered search experiences mention their brand when buyers ask category-level questions. But the smart move is not to declare keyword rankings dead—it is to add answer-engine visibility to a measurement system that still includes search demand, qualified traffic, conversions, and revenue.
The shift was the focus of the original HubSpot Academy video that inspired this discussion: marketers may assume their company appears in AI-generated recommendations without ever testing that assumption. That gap matters because AI interfaces increasingly synthesize an answer before a user chooses which website, product, or provider to investigate.
Why an AI visibility score matters now
Classic SEO metrics answer important questions: Which pages rank? How much organic traffic do they earn? Do those visits convert? They are still essential. Google’s own current guidance is explicit that conventional SEO best practices remain relevant for AI Overviews and AI Mode, because its generative experiences rely on core Search ranking and quality systems. (developers.google.com)
The blind spot is that rankings alone do not reveal how an AI system frames a market. A prospective customer might ask, “What is the best project-management platform for a 20-person agency?” or “Which payroll software works for a distributed startup?” If an answer engine summarizes the category and names competitors—but not your business—your strongest ranking page may never enter the buyer’s consideration set.
This is not a fringe behavior. Google said AI Overviews had reached 1.5 billion monthly users across 200 countries and territories by May 2025, while ChatGPT Search provides web-backed answers with links to relevant sources. Perplexity similarly positions its product as a real-time, cited answer engine. (blog.google)
That does not mean every query gets an AI Overview, every answer produces a click, or every AI mention has equal commercial value. It means brand discovery can now happen inside a generated response, which makes visibility and representation worth measuring directly.
What an AI visibility score actually measures
An AI visibility score is not a universal, platform-issued KPI. It is generally a third-party measurement of how often and how favorably a brand appears across a defined set of prompts, answer engines, and competitors. Its usefulness depends on the quality of the prompts and the consistency of testing—not on treating one score as an absolute truth.
HubSpot’s free AEO Grader provides a clear example. It produces a one-time assessment across five dimensions: brand recognition, market position, presence quality, sentiment, and share of voice. HubSpot describes its broader AEO product as monitoring appearance across ChatGPT, Gemini, and Perplexity, with share of voice representing the percentage of category mentions that go to a brand versus competitors. (hubspot.com)
Those categories translate into practical marketing questions:
- Brand recognition: Does the model know your company exists, and does it connect it to the right category?
- Market position: Does AI present you as a credible option, specialist, leader, or niche provider?
- Presence quality: Is your brand merely named, or is it described accurately with useful context and sources?
- Sentiment: Is the representation positive, neutral, mixed, or associated with recurring objections?
- Share of voice: Across prompts that buyers actually ask, how often are you mentioned compared with direct competitors?
The original video refers to Google’s AI Overviews alongside ChatGPT and Perplexity. Marketers should make one important distinction: Google Search AI Overviews and Google’s Gemini are related Google AI experiences, but they are not interchangeable products or measurement surfaces. HubSpot’s current AEO materials identify ChatGPT, Gemini, and Perplexity as the engines its tool analyzes, while Google measures site performance for AI features within Search Console reporting rather than through a public “brand recommendation” score. (hubspot.com)
How to use AI visibility score without chasing a vanity metric
The danger is turning AI visibility into another dashboard number with no operational meaning. A brand can show up frequently for vague informational prompts yet fail to appear for high-intent comparisons, implementation questions, local queries, or use cases that drive pipeline.
Start with a small, intentional prompt set. Include the questions sales teams hear on calls, the alternatives prospects compare, the jobs customers hire your product to do, and the objections that delay decisions. Segment prompts by funnel stage and by market, because an enterprise buyer in the U.S. may ask fundamentally different questions from a solo operator in the UK.
Then establish a baseline and review patterns over time. A useful reporting cadence could include:
- Visibility: In what percentage of priority prompts is the brand mentioned?
- Competitive context: Which brands dominate mentions, and on which themes?
- Message accuracy: Does the answer describe your product, positioning, pricing, geography, and capabilities correctly?
- Source patterns: Which owned pages, earned coverage, reviews, directories, or third-party publications appear to support the answer?
- Business outcomes: Do changes coincide with branded search, referral traffic, demo requests, assisted conversions, or sales-team feedback?
Use the score to prioritize investigation, not to claim causation. AI responses can vary by model, location, account context, prompt wording, time, and the sources available to the system. A movement from 42 to 58 may signal real progress, but it is not proof that revenue will rise by the same proportion.
Improving AI visibility still starts with durable SEO
The most useful takeaway from the video is not “replace SEO with AEO.” It is that marketers should broaden their definition of visibility. Google’s guidance says there are no special technical requirements for appearing in AI Overviews or AI Mode beyond the same foundational requirements and SEO practices that make content crawlable, indexable, helpful, reliable, and people-first. (developers.google.com)
That makes many supposed AI-search tactics less mysterious than the hype suggests. Teams should focus on publishing genuinely differentiated material: original research, documented product details, transparent comparisons, expert explanations, customer stories, and clear answers to specific buyer questions. Google also cautions against generating large volumes of low-value AI content, which can violate its scaled-content-abuse policy. (developers.google.com)
A practical improvement plan looks like this:
- Audit your key commercial pages for factual completeness, clear positioning, and accessible page structure.
- Build comparison, alternatives, use-case, implementation, and FAQ content around real buyer language—not invented keyword variations.
- Make product, organization, local-business, and other relevant structured data match visible page content.
- Earn credible third-party references through PR, reviews, partnerships, expert contributions, and useful research.
- Fix crawlability, indexation, broken pages, and stale claims before investing heavily in new content.
- Re-test a stable set of prompts monthly or quarterly, then connect visible changes to qualified demand and revenue metrics.
AI visibility score is a compass, not the destination
The emerging AI visibility score deserves a place in the marketer’s toolkit because it captures something rankings cannot: whether a brand is present when an AI system summarizes choices for a buyer. HubSpot’s AEO Grader offers a free starting baseline through recognition, market position, presence quality, sentiment, and share of voice. (hubspot.com)
Still, the winning strategy is disciplined integration. Keep measuring rankings, impressions, clicks, conversion quality, and revenue. Add AI visibility to reveal missed consideration opportunities. Then improve the same assets that make a business easier for people—and search systems—to understand: accurate information, original expertise, strong technical foundations, and a brand presence credible enough to be recommended.