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When someone asks ChatGPT or Google's AI Overview "what's a good mall near me with a movie theatre," is your property even in the running for that answer? Most shopping centre marketing teams haven't asked themselves that question yet, because the discipline of optimizing for it barely existed two years ago.
There are now three overlapping terms circulating in marketing conversations: SEO, AEO, and GEO. Before spending a dollar chasing any of them, it's worth being clear on what each one actually means, and being honest about which claims in this space are proven versus which are still marketing speculation.
Three Terms, One Genuinely Rigorous Source
SEO, Search Engine Optimization, is the uncontested baseline: optimizing your content and technical setup so a page ranks in traditional search results. Everyone agrees on that definition.
AEO, Answer Engine Optimization, is an industry-coined term describing the practice of structuring content so it gets extracted or quoted as a direct answer inside AI interfaces: AI Overviews, chat assistants, voice search. At least five independent sources converge on that general definition, but there's no single canonical version of it.
GEO, Generative Engine Optimization, has an actual research paper behind it. Princeton and Georgia Tech researchers published "GEO: Generative Engine Optimization" at KDD 2024, one of the field's top academic venues, and tested their tactics against a 10,000-query benchmark, then validated the results live on Perplexity.ai. That's a meaningfully different category of evidence than most of what circulates as "AI SEO advice."
Here's where it gets genuinely unsettled: the industry hasn't agreed on whether AEO and GEO are the same thing or different disciplines. Some practitioners argue they're identical, with GEO being the academic label and AEO the more marketable industry term. Others draw a real distinction: SEO aims to rank, GEO aims to shape how AI systems represent your brand across the answer, and AEO aims narrowly at getting directly quoted. There's no Google or Bing statement settling this. Anyone presenting a clean, confident hierarchy of these three terms is offering their opinion, not a documented consensus.
What the Actual Research Paper Found
The KDD 2024 study tested specific content tactics and measured what moved the needle on AI-generated answers. Adding citations to credible sources, adding statistics and quantitative data, and adding direct quotations produced a 30 to 40% relative improvement in whether content got referenced. Simplifying language for clarity added another 15 to 30%. Tested live on Perplexity.ai, the improvement reached as high as 37%, not just in a simulation.
The finding that should get more attention than it has: classic SEO keyword-stuffing did not help generative engine visibility, and in some cases hurt it. The researchers' own words: "techniques effective in search engines may not translate to success in this new paradigm." That's the clearest evidence available that SEO and GEO, whatever else is debated about the relationship between them, are not simply the same activity under two names.
One more finding worth knowing before investing heavily here: these tactics disproportionately help smaller, lower-ranked sites. A 5th-ranked page gained 115% more visibility from adding citations. A top-ranked page's visibility actually fell around 30% once everyone else started optimizing the same way. For a mid-market Canadian shopping centre competing against a handful of larger regional properties, that's a real opening, not a disadvantage.
What's Actually Happening to Search Traffic
The most credible data on this comes from Pew Research Center, which analyzed real browsing behaviour from 900 US adults across nearly 69,000 actual Google searches. When an AI Overview appeared, users clicked through to a traditional search result only 8% of the time, compared to 15% when no AI Overview was present, roughly half the click-through rate. Only 1% of visits produced a click on a link inside the AI summary itself. Users also ended their browsing session entirely more often after seeing an AI summary.
That's a real, well-documented shift in behaviour. What it doesn't mean is that traditional search is disappearing. A widely repeated 2024 Gartner prediction claimed search volume would drop 25% by 2026. Actual clickstream data from SparkToro and Datos through mid-2025 shows traditional search usage among Americans staying essentially flat, above 95% monthly active, even as AI tool usage grew. Google is still handling roughly 210 times the daily search volume of ChatGPT. The honest read: AI tools are becoming a real, additional discovery channel, not a replacement for the one you already know.
Whether Ranking Well on Google Also Helps with AI
Three independent research firms, Ahrefs, Semrush, and BrightEdge, all confirm that ranking in Google's top 10 correlates positively with getting cited in AI answers, but doesn't guarantee it. Even a page ranked number one gets cited in AI Overviews only about half the time.
Here's a genuine point of disagreement worth being upfront about: Ahrefs' own tracking shows the share of AI citations coming from top-10 organic pages dropping sharply, from roughly 76% to 38%, between mid-2025 and early 2026, suggesting AI systems are increasingly pulling from a wider set of sources. BrightEdge's separate tracking over the same general period shows the opposite pattern, overlap between AI citations and organic rankings rising. Two named, credible trackers looking at the same question and reaching different conclusions about the direction of the trend. That's not a gap in our research. That's the actual, current state of a fast-moving space, and it's worth knowing that before anyone promises you a guaranteed AI-visibility strategy.
One documented, AI-specific mechanic that classic single-keyword SEO doesn't fully address: Google's AI Overviews and AI Mode split a single query into multiple sub-searches behind the scenes, a process called query fan-out, and cite across the results of those sub-queries. Optimizing a page for one target keyword phrase increasingly under-serves how these systems actually search.
What Actually Moves the Needle for a Local Business
Setting aside the parts of this that are still unsettled, several practical steps have real, corroborated evidence behind them.
Keep your Google Business Profile completely accurate: categories, hours, services. This shows up consistently as a top factor across Google's own documentation and independent local-search research. Keep your business name, address, and phone number consistent across your website, Google Business Profile, Bing Places, Apple Maps, and Yelp; inconsistent listings measurably hurt local visibility. Treat your own website as your primary factual source; a 2025 study testing AI tools across ten industry categories found business websites were the single most common source AI tools pulled from, more than directories or review sites. Actively manage your reviews. Whitespark's 2026 Local Search Ranking Factors Report, an annual survey of 47 named local-search experts running since 2008, the most established source of its kind, ranks third-party review authority among the top factors for AI-specific visibility. Separately, 47% of consumers say they won't use a business with fewer than 20 reviews.
On structured data: Google's own documentation is clear that no special schema markup is required to appear in AI Overviews or AI Mode. Add schema for accuracy and consistency, because it helps AI tools extract facts correctly as page text, not because it's a special switch that triggers AI visibility. Any vendor claiming a specific percentage lift from schema markup alone is making a claim Google's own documentation directly contradicts.
What We Genuinely Don't Know Yet
Being straight about the limits of this research matters as much as the findings themselves. No Canada-specific data exists yet on AI search adoption, AI Overview click-through impact, or local AI-citation behaviour for Canadian businesses; every statistic in this piece is a US or global proxy. No study has tested shopping-centre-specific queries directly, "mall hours," "events near me," "is this store open"; the local-search research that exists covers categories like restaurants, dentists, and lawyers, and extrapolating to shopping centres is reasonable but unverified. And despite an active search, no documented case exists of a specific shopping centre, in Canada or anywhere else, being cited by name in a ChatGPT, Perplexity, or Google AI Overview response. Any example someone shows you of a mall being AI-cited is either recent enough that it hasn't been studied, or it's speculative.
That's not a reason to wait. It's a reason to build the fundamentals: an accurate Google Business Profile, a well-sourced and current website, an active review program, and the actual research to support, rather than chasing a specific tactic sold as a guaranteed AI-visibility hack.
Interested in a straight read on where your property's discoverability actually stands right now, across search and AI alike?
