From Search Results to AI Answers: Why AEO Matters Now
Answer engine optimization is the practice of shaping how brands, products, and expertise appear inside AI-generated answers across tools like ChatGPT, Gemini, and Perplexity, so buyers see accurate, persuasive information before they ever reach a website. Traditional search optimized for blue links and rankings; AI discovery optimizes for summarized responses, citations, and which vendors are named in the first place. Research signals how fast this is changing: Gartner has forecast that traditional search volume could fall 25% by 2026 as AI chatbots and virtual agents take over more queries, while a Pew Research Centre study found that Google users clicked a classic search result in only 8% of visits when an AI summary appeared, compared with 15% without one. The takeaway for marketers is clear: visibility now happens inside the answer, not only on the results page.
Answer Engine Optimization vs. Classic SEO
Answer engine optimization builds on SEO skills but targets a different outcome: influence over how large language models interpret and reuse brand content. Instead of focusing on specific keyword rankings, marketers track whether their brand is mentioned, how it is described, and which sources answer engines cite. Sitecore describes this as a move from standalone answer engine optimization to a continuous loop, where AI search visibility data feeds directly into content and experience workflows. A Semrush study reported by Business Insider found that only 22% of surveyed US marketers have fully integrated AI search and SEO strategies, while 37% say competitors appear more often in AI results. That gap shows why AEO is emerging as its own discipline, with specialized tools to monitor buyer prompts, detect content gaps, and recommend fixes across multiple AI search environments.
Inside Sitecore’s Scrunch Deal: Making Brand Visibility AI-Ready
Sitecore’s acquisition of Scrunch adds an AI-focused “insight layer” to its digital experience platform, aimed at understanding and improving brand visibility in AI-generated answers. Scrunch’s Agent Experience Platform (AXP) tracks which buyer queries mention a brand, how often competitors are named instead, what sources are cited, and where messaging is missing or misrepresented across large language models like ChatGPT, Google Gemini, and Perplexity. It then recommends specific content and source changes marketers can make, and can reformat existing pages so AI agents can process them without disrupting the human experience. Case studies show how answer engine marketing is starting to pay off: Akamai reported a 364% increase in brand presence for non‑branded prompts and a 218% jump in citations, while Runpod saw a 400% increase in paying customers tied to AI search optimization efforts. Sitecore’s strategy is to connect these insights directly into content, marketing, and asset workflows.
B2B Review Sites Enter the Answer Engine Marketing Stack
B2B review platforms are gaining new importance as answer engines mine them to shape AI-generated answers. Forrester notes that content from G2, TrustRadius, PeerSpot, and even Reddit discussions now feeds tools such as ChatGPT, Claude, Perplexity, and Microsoft Copilot, which means review-site presence has become a core input for answer engine optimization. Forrester’s research shows that 94% of B2B buyers use answer engines during their search, often forming preferences early; if a vendor is absent from those early AI summaries, it may never reenter the consideration set. Review profiles, comparison pages, ratings, and “best of” lists no longer only influence human readers; they also influence how models rank and summarize solutions. As a result, marketers are treating review programs as part of answer engine marketing, aligning requests for feedback, messaging themes, and profile updates with the questions buyers ask AI tools.
How Marketers Can Adapt to the AI Search Visibility Shift
The rise of AI-generated answers forces brands to extend their visibility strategy beyond traditional SEO. Sitecore argues that most enterprises already have the right content—product documentation, expert articles, customer proof—but it is often fragmented or formatted in ways AI systems cannot easily use. Tools like Scrunch’s AXP address this by surfacing where a brand appears, is missing, or is misrepresented, then feeding recommendations into existing content and campaign workflows so teams can update pages without changing platforms. Marketers are starting to treat AI search visibility as a measurable channel: tracking answer share versus competitors, monitoring citations across answer engines, and using structured, well-maintained sources such as review sites to strengthen authority signals. The emerging playbook combines answer engine optimization, review-site strategy, and content operations, giving brands a way to influence how AI systems present them in discovery and buying decisions.
