From SEO to GEO: How brands can stay visible in the age of AI search
The convergence of hyperlocal and AI search is the next major shift in online marketing. With the future of search lying in fully integrated strategies that can be delivered at scale, brands risk disappearing from zero-click AI summaries, even if their websites still perform well in traditional search.
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How can your brand be “the chosen one”
The next evolution of SEO is Generative Engine Optimisation (GEO), the practice of optimising content for AI-driven search results, such as those generated by ChatGPT, Perplexity, and Google Gemini.
The big shift is moving from what we used to call ‘ranking links’ to becoming AI’s chosen answer
AI is rewriting local search: How multi-location brands can win now
The data is unambiguous: AI search already influences how multi-location brands are showing up in , according to Search Engine Journal.
Visibility depends on structured, verified, and fresh data - again, at scale.
For multi-location brands, this requires dual-visibility strategies that check the boxes for brand authority, thought leadership, and structured content at the national level; as well as store or branch-level data accuracy (NAP), reviews, local content, and directory listings at the local level.
Outsourcing the mental (and measurement) load
What we are finding is that many CMOs are unsure how best to approach all of this.
It’s a lot to implement and measure without the right tools. Numerous options exist, but Sauce’s go-to for measuring GEO visibility is Scout, the AI search visibility and competitive intelligence platform from Yext. It’s the only tool that actually gives us a real-time, holistic view of local and national visibility in the AI era.
AI Rank and Google Rank are two key metrics measured by Scout, but other functionalities that leans on include Google Review Count, AI Brand Sentiment - the sentiment that AI uses when mentioning a particular brand in search results, Google Photo Count, Google Profile Completeness, and Citations.
These encompasses a broad range of different measurables, including local citations, structured data, reviews, editorial mentions, and engagement signals.
The main thing we try to communicate to clients is that AI models don’t just ‘rank websites’ - they synthesise answers.
To identify which businesses are safe, relevant, and correct, AIs cross-check citations across multiple sources. Basically, strong citations give you stronger trust signals, which gives you a higher likelihood of being the AI’s answer.
How much do these metrics matter?
Trustworthiness is very much the name of the game in GEO, as one of the core ingredients in Google’s E-E-A-T recipe for success.
AI tools rely on a range of sources to cross-check whether your business actually exists, where it is - and if the details are consistent.
Inconsistent NAP means lower trust, and a reduced likelihood of appearing in those AI-generated local results. On the other hand, accuracy drives trust, and a set of strong, consistent local citations will boost your trustworthiness score.
Review signals are a synonym for credibility in the online landscape today, with star ratings and volume heavily weighted by AI models when selecting answers.
Schema and structured content translates to machine readability, which is critical for being pulled into AI answers. And engagement metrics - like clicks for directions and calls - are known to indicate business impact; they are essential, not mere vanity metrics.
While it may be possible for a small business to cover all of their GEO and SEO bases by themselves, it is getting progressively harder for multi-location operations to effectively manage - never mind monitor - their online presence and performance. More than half of the enquiries we have received this year have been about doing just that.
About Leanne Levine
Local Digital Lead at Sauce Advertising
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