Digital Marketing: Between Found, Quoted and Recommended
36 minutes ago | Opinion
Digital Marketing: Between Found, Quoted and Recommended
Online search behaviour has shifted from queries to seeking recommendations. With OpenAI disclosing that approximately 900 million people use ChatGPT every week, and Google putting AI Overviews above many of its results, the objective has moved from “rank and get the click” to “get recommended in the answer”.
AI-enabled search is changing how customers discover choice brands, products, and information. Being recommended by crawlers has become the new word-of-mouth advertising. In this Answer Economy, “I found you on Google” is less common than “Your product popped up when my ops guy asked ChatGPT.”
A buyer can now encounter a brand through a synthesised referral before visiting a search result or website. The prevalent practice is to use AI to narrow down options. G2’s Answer Economy report found that 51% of B2B buyers now begin their research on AI platforms rather than traditional SEO. Being found remains the foundation, but being recommended is where the buying decision happens.
With ranking and clicks no longer the haymaker, good old search engine optimisation (SEO) is being downplayed as answer engine optimisation (AEO) and generative engine optimisation (GEO) gain ascendancy. But can the last two be separated from the first? We shall find out momentarily.
The SEO, AEO and GEO parallel
Although both are AI-driven, answer engine and generative engine do not overlap. One gets quoted while the other recommends. A quote affirms that AI trusts your information. A recommendation expresses the crawler’s confidence in your business offerings. SEO helps businesses get discovered; AEO establishes them as a trusted
Ranking on Google does not automatically translate to visibility in ChatGPT. It’s the same way that being cited in an answer (AEO) differs from having your answer extracted (GEO). However, showing up in AI answers is earned the same way rankings are – by being the clearest
SEO optimises for search engines. It’s essentially about being found, as Google ranks your page when someone searches. This hinges on keyword research, domain authority, schema markup and backlink outreach. AEO optimises for direct answers and clarity. AI Overviews and Featured Snippets cite your content as the pointed answer to a question. This requires developing content with question-based headings, adding FAQs and a summary schema.
GEO optimises for AI-generated experience and makes references. Here, the algorithm presents you to the prospective buyer, who asks, “Which brand should I choose?” Appearing in AI-generated answers is more consequential than ranking tops on Google. While AI traffic converts at 15.9%, it’s 1.76% for Google organic. Perplexity or Claude naming-dropping a brand out of the blue can land that business a mouthwatering deal.
Engines intersection: AEO, GEO reinforce rather than replace SEO
SEO is the foundation, while GEO is the superstructure. Focusing on GEO without a solid SEO is like building a house without a foundation. Data structure and authority built through traditional SEO are exactly what AI models rely on to recommend brands. To be recommended by the algorithms, you need to rank first!
GEO isn’t a replacement but an extension. Great SEO sets you up for a good AEO and GEO strategy. As far as online visibility goes, no amount of ‘AI optimisation wizardry’ can compensate for weak traditional SEO fundamentals. AI assistants are primed to cite pages that already rank and already carry trusted links and mentions.
If a page is not ranking in normal search, AI has no real reason to trust it either. There is no AI mention without first satisfying basic SEO requirements. Good SEO practices actually scream “we’re an authority in that category”, which attracts the attention of algorithms.
Whether it’s a search engine or an AI assistant, digital marketing fundamentals of E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) and credible signals determine being found, quoted or recommended.
It takes web-wide consensus to make an AI shortlist
Beyond your web page, which purveys the facts, third-party mentions give AI systems the impetus to cite or recommend you. If a brand isn’t consistently cited and validated across trusted third-party sources, generative engines won’t be confident enough to suggest it when someone asks.
Brand mentions, trusted third-party sources, useful content and consistent information across the web all facilitate AI discoverability. Large Language Models (LLMs) rely heavily on review sentiment and consistent local citations to confidently recommend physical businesses to users.
Solving the measurement, attribution quandary
Of course, organisations would like to know whether AI visibility attracts the right audience, builds trust, and generates qualified opportunities. A GEO win measured with SEO numbers will always look like a miss. Separating being found, quoted, and recommended gives teams distinct outcomes to track, making it easier to decide where to put the budget.
Unlike rankings that come with a dashboard by default, AI recommendations don’t, so nobody looks. The shift from “being found” to “being recommended” changes the metric from traffic volume to influence. This necessitates a completely different reporting structure for being found, quoted, and recommended.
Ø SEO: Measure qualified visits and leads generated from search.
Ø AEO: Seek to find out how many of your buyers’ questions you’re quoted on
Ø GEO: Ascertain how often you’re recommended first, by persona and buying stage (for instance a head of marketing who wants to understand, compare, then choose).
When someone asks ChatGPT and then types the brand name into Google, or calls straight from the answer, analytics logs it as branded search or direct, not AI. A simple way to link visibility with lead generation is by adding a specific AI assistant as an option in your “How did you hear about us?” question, and comparing it with your monthly checks.
These checks can be done monthly by repeatedly asking Google and Perplexity about a brand’s top 10 buying questions, with a column for how often it is named first. For the 10 queries, log whether the brand is mentioned, quoted or actually recommended, along with the reason given. Then report the share across five runs per question — this will turn one noisy answer into a number that can be tracked month-on-month.
Sampling across multiple runs and prompt variations is highly recommended because asking the same buying question five times can result in five different shortlists. This raises “recommended first”, which is the headliner, not the whole picture. Keep inclusion and citations as supporting lines, and check that AI describes the brand correctly. The headline tells the CEO where you stand; the rest tells the team what to fix.
Why PR must pay attention
Public relations teams and managers must pay more attention to GEO because it depends on mentions and slants on sites outside the control of their organisations. It is their job to ensure adequate representation of the brand wherever people are evaluating their options. As authority now entails being trusted across search and AI platforms, PR must build enough entity clarity, relevance, and credible evidence for crawlers to reference their brand.
AI-powered search has equally become a veritable tool for competitor benchmarking. Where AI answers keep shortlisting a competitor because crawlers think they’re the only one with a free trial, that’s a much clearer next step for your company before your recommendation rate tanks. The fix is to jazz up your offer page, not chase more mentions.
Content remains king in this kingdom because PR can’t effectively measure GEO without knowing what actually gets quoted. AI assistants are trained on the same content that builds your brand everywhere else. They cite the same authoritative sources and reference the same trusted publications.
The Hail Mary is that AI still considers what you say, how clearly you say it, and whether other sites on the internet back up the claim before making referrals. The way to go is to optimise to be the answer, not just the top result. And while leading with the answer, put it in the first two lines of each schema section, followed by a detailed explanation.
Studies show that between 44% and 50% of forum and social pages (Reddit, LinkedIn and YouTube) used by Google’s AI search, Gemini and Perplexity were posted by brands, publishers or the platform itself. This creates a visibility lever for digital PR to capitalise on by clearly communicating what the business does, who it serves, what makes it different, alongside the evidence that supports those claims.
Disclaimer: “The views expressed on this site are those of the contributors or columnists, and do not necessarily reflect TheNigerianVoice’s position. TheNigerianVoice will not be responsible or liable for any inaccurate or incorrect statements in the contributions or columns here.”
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