Agentic commerce, or AI-driven shopping, isn\u2019t exactly a user experience trend, but a \u201ctransformation,\u201d according to David Ingram, chief product officer of Rezolve Ai, a platform that develops agentic commerce solutions for companies. <\/p>\n
He explained that the rise of AI-influenced shopping is shifting how products are discovered<\/a>. It is changing the focus from traditional search engine optimization (SEO) to a generative engine optimization<\/a> , which is the foundation for how AI systems understand and select products.<\/p>\n How is GEO changing how brands show up online?<\/p>\n AI platforms are gradually becoming consumers\u2019 first point of contact when searching for a product, which changes brand visibility online.<\/p>\n \u201cWe\u2019re increasingly expressing our intent conversationally rather than navigating websites manually,\u201d Ingram explained. \u201cVery many of us go first to AI, then to a brand e-commerce site.\u201d<\/p>\n Rather than discovering a product via SEO keywords or a structured search, consumers are communicating their preferences, needs and goals in their own language to bypass endless scrolling and find that one solution. For brands, that means their sites need to be optimized for interpretation by AI agents digging for the best answer, or answer engine optimization (AEO).<\/p>\n Between, SEO, AEO and GEO, the flurry of acronyms can be overwhelming to marketers \u2013 but companies like RevolveAI and Noise Media Group provide AEO and GEO audits to help brands identify where, how and why they\u2019re showing up in comparison to their competitors. Ultimately, the strength of a brand\u2019s web presence \u2013 website, blogs, quest posts, social media comments \u2013 will determine how often they show up on the answer \u201cshelf.\u201d<\/p>\n The \u2018answer layer\u2019 replaces the digital shelf<\/p>\n With agentic commerce compressing the digital shelf into a narrower interface, competition is fundamentally changing, according to Ingram.<\/p>\n He points out that the models are now \u201cgood enough to really properly understand context\u201d and \u201cvery good at guiding decisions.\u201d <\/p>\n Rather than consumers seeing dozens of SKUs on a page, brands are now competing to be in a smaller set of AI-curated recommendations or potentially excluded altogether. Yet rather than brand awareness or paid placement determining inclusion, it\u2019s finely tuned data. <\/p>\n \u201cMake sure that your catalog data is complete, accurate \u2013 not just parametric \u2013 [and] has some use case information,\u201d Ingram said.<\/p>\n Ingram emphasizes that it\u2019s not enough for brands to rely on traditional product attributes. Brands need to explain \u201cwhat is the product useful [for] \u2026 how does the product relate to use cases that a consumer might be searching for,\u201d he said.<\/p>\n Why product data must evolve beyond SEO<\/p>\n For most brands, product data has historically been optimized for e-commerce listings and search engines. But Ingram argues that\u2019s no longer sufficient.<\/p>\n \u201cIt\u2019s a different game now,\u201d he said. \u201cWhen we\u2019re searching as consumers with an AI assistant, we\u2019re \u2026 using a much longer-form query, a more use-based query.\u201d<\/p>\n He gives a clear comparison:<\/p>\n Traditional search: A white shirt in a specific size with a cutaway collarAI-driven search: \u201cI am looking for [a] shirt that I can wear to work, that packs well for travel and comes out my suitcase uncreased.\u201d<\/p>\n That search query requires a different kind of data structure from brands that connects product attributes to real-world use cases and outcomes, Ingram explained.<\/p>\n For CPG brands, the data gap between SEO and GEO is now a visibility risk, he added.<\/p>\n Visibility starts with the foundation first<\/p>\n Brands should refrain from optimizing for specific platforms too early and instead begin with strengthening their foundation around structured product data, clean content and real-time feedback.<\/p>\n \u201cI wouldn\u2019t yet try to optimize for one or other,\u201d Ingram said, referring to OpenAI, Google, Amazon and other AI shopping surfaces.<\/p>\n \u201cEnsure first of all that you\u2019re showing up. That\u2019s the foundation of it all,\u201d he emphasized.<\/p>\n Better decisions, fewer returns and higher expectations<\/p>\n As AI improves the discovery process, it creates more informed purchases, Ingram explained. He frames product discovery as \u201cquite a creative process,\u201d one that becomes \u201cmore beautiful, natural \u2026 [and] satisfying\u201d with conversational AI.<\/p>\n With AI agents consumers can now ask nuanced, detailed questions about fit, performance or attributes that would have been difficult to answer through traditional browsing. The result is a more refined match between product and need.<\/p>\n But these hyper-attuned recommendations come with a tradeoff.<\/p>\n Ingram suggests improved understanding about a product before purchase is likely to \u201cdrive down returns\u201d \u2013 a plus for brands. <\/p>\n At the same time, consumers\u2019 expectations rise because they have more clarity before they buy. These shifts reinforce why GEO is about accuracy as well as visibility.<\/p>\n Start with visibility, not perfection<\/p>\n Despite the scale of change, Ingram\u2019s advice is practical: Don\u2019t try to solve everything at once.<\/p>\n \u201cStart small, move fast,\u201d he said, pointing that these changes can be small, fast and light.<\/p>\n Yet, even those early, smaller steps need to be rooted in a clear understanding of how brand visibility is evolving online. Within agentic commerce, the question is no longer about a brand showing up on the first page of a search, it\u2019s whether the show up in the answer.<\/p>\n","protected":false},"excerpt":{"rendered":"Agentic commerce, or AI-driven shopping, isn\u2019t exactly a user experience trend, but a \u201ctransformation,\u201d according to David Ingram,…\n","protected":false},"author":2,"featured_media":72295,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[179,7493,1092,6529,25980,12816,25981,20741,7067,2365,1757,760,3276,7880],"class_list":["post-72294","post","type-post","status-publish","format-standard","has-post-thumbnail","category-agentic-ai","tag-agentic-ai","tag-agentic-artificial-intelligence","tag-analysis","tag-bot","tag-chat","tag-creative","tag-interface","tag-professional","tag-programming","tag-social","tag-tools","tag-user","tag-virtual","tag-workspace"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/72294","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=72294"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/72294\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/72295"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=72294"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=72294"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=72294"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}