A step-by-step guide to winning search in the age of generative AI

Retailers developed strategies, brought solutions and developed processes to eke out every opportunity to capitalize on what Google and the other search engines could offer. 

Fast-forward to 2025, and the next frontier is here: generative engine optimization (GEO). More consumers are turning to AI-powered, generative platforms like ChatGPT, Claude and Perplexity for answers to questions, product research, reviews and recommendations. As they do, GEO is fast becoming essential to maintaining visibility and relevance in the AI-first era of shopping

Product Discovery Is Being Rewritten

Discovery with AI begins with natural-language prompts like, “What are the best running shoes for occasional runners with flat feet?” and ends with AI-summarized recommendations. The recommendations have the potential to be more personalized, based on previous interactions and tailored to the context of the current chat session. The recommendations also can include an explanation as to why they were made, thereby increasing trust.

While traditional search is precise and fast for well-defined queries, generative AI can unlock new ways for customers to discover products, through conversation, inspiration and intent-based recommendations. An AI-powered chat might determine that you’re asking about the best shoes for running, recognize that you previously asked about tennis and ask if you’d like to consider cross-training shoes. AI-prompted recommendations can also include side-by-side comparisons of the results, allowing for greater understanding of the options. Well-trained and data-rich AI can respond to requests for comparisons on factors unique to each shopper.

For example, the prompt, “Compare the top four choices based on reviews of durability, stability on uneven surfaces, arch support and price” would generate a table summarizing findings and a recommendation considerate of these factors.

For AI to provide these responses, it needs visibility to vast sources of data. Visibility is AI’s ability to ‘see’, interpret and understand the data, authoritative third-party sources and how well the brand content aligns with intent.

Product discovery is no longer just about being ranked. It’s about being referenced, cited and interpreted by large language models (LLMs).

Brand Visibility Will Shrink Without GEO

The shift from search engines to generative platforms is happening. In 2024, traffic to retail websites from generative AI sources increased by 1200–1300 per cent during peak shopping seasons, including during the previous holiday period.

Several converging factors are driving the surge, particularly in product discovery, including:

• Better answers, less effort: Generative platforms deliver direct answers instead of long lists of links. Consumers get faster and better answers tailored to their questions, saving time and mental energy.

• Voice-influenced searches: Generative AI aligns well with how people think – conversationally. This makes AI tools feel more intuitive than traditional search engines, especially for Gen Z and mobile-first users.

• Personalization expectations: Consumers are coming to expect and demand tailored recommendations, not generic content. Generative platforms deliver by considering user intent and context, and by improving with subsequent interactions.

As the generative platforms become more ingrained in our daily lives, their use as discovery tools will increase and traditional SEO tactics will not be able to drive the same user traffic.

Competitive Differentiation Requires Narrative Control

Competitive differentiation will hinge on a brand’s ability to control and shape its narrative. AI-generated content is becoming the norm. LLMs build responses using what they interpret as authoritative, semantically consistent sources. If a brand’s voice is absent or poorly represented – especially in third-party reviews, comparison articles and structured data feeds –then competitors who’ve curated and distributed their stories more effectively will dominate the AI-generated answers.

This means that GEO isn’t just about visibility– it’s about influence. Retailers must proactively manage how their products and values are described, ensuring that generative platforms reflect their unique selling points accurately and compellingly. The brands that succeed in this will show up in AI responses. Others won’t.

Organic Traffic and Revenue Are at Stake

The stakes for organic traffic and revenue have never been higher. SEO-driven traffic is being disrupted as more shoppers bypass search engines in favor of conversational commerce.

Retailers who fail to adapt risk losing a share of their organic reach, especially during high-intent moments like the holiday shopping season or with specific product research sessions.

When a brand isn’t cited in AI-generated responses, it misses exposure and potential conversions. GEO ensures your content remains accessible, relevant and monetizable in AI-led journeys. Inaction, meanwhile, translates directly to reduced visibility, fewer click-throughs and shrinking digital sales pipelines.

Three GEO Strategies Top Retailers Are Already Using

Forward-thinking retailers aren’t waiting to react. They’re already retooling how they show up in generative environments. From structured data to content design and citation strategy, these companies are laying the groundwork for consistent AI visibility.

Here are three practical GEO strategies that top performers are using to get and stay in the generative conversation:

1. Structured Data and Knowledge Graphs

Generative engines rely on structured data to understand brand and product specifics. Amazon and Walmart already use detailed schema across their catalogs to feed internal AI tools and external engines alike. 

Best practices:

• Use structured data and semantic markup, such as HTML tags that convey the meaning, to ensure that LLMs can parse and recognize products and descriptions effectively.

• Follow Schema.org’s markup for products, reviews, FAQs, how-to guides, store locations and other elements.

• Tag dimensions, availability, sustainability claims and reviews.

• Test your pages with Google’s Rich Results Test

2. Prompt-Aware Content Design

Retailers like Best Buy and Brooklinen are tailoring content to match real user queries – think “best pillow for side sleepers” or “how to layer bedding for winter.” Creating blogs, how-tos and ‘vs.’ articles that mimic user questions helps LLMs cite your content more accurately.

Best practices:

• Use FAQs, lifestyle content and comparison guides.

• Align with how people ask, not how you market.

• Write with clarity and consistency, not just for human readers, but for AI interpretation.

• Consider expanding into voice and visual prompts as the tech evolves.

3. Authority and Citation Network Building

Generative AI platforms favor authoritative sources. Brands like Pacsun and Heydude are ensuring their names appear in expert reviews, product roundups and even Wikipedia to increase the chance of inclusion in AI responses.

“It’s essential for brands to leverage GEO to deliver accurate, brand-authenticated and up-to-date product narratives through AI platforms, ultimately guiding customers with relevant and trustworthy information,” commented Shirley Gao, Pacsun’s chief digital and innovation officer.

Best practices:

• Build authority by getting cited in third-party content and push enriched data into places LLMs learn from.

• Monitor citation frequency and fill gaps with strategic PR, influencer partnerships and third-party features.

GEO Is Needed for Smaller Brands Too

GEO is one area where AI has the potential to reduce the divide between large and smaller retailers. The key is to prioritize crawlability and credibility in content, and to leverage free and low-cost AI tools.

What seems obvious to humans isn’t so to AI – at least not yet. Structured data improves AI comprehension of your site.

Best practices:

• Use free generators like Google’s Rich Results Test.

• Start with key schemas like “Product” and “FAQ”.

• Create conversational FAQ pages and buying guides.

Generative engines respond to question-and-answer formats. Writing your content in this format improves AI comprehension.

Best practices:

• Use tools like AnswerThePublic to find relevant questions.

• Format answers clearly using headers, such as (<h2>), and bullet points.

• Leverage your e-commerce platform’s built-in tools.

Many leading e-commerce platforms handle much of the GEO backbend, making structured data easier to manage. For example, Shopify automatically handles many key schemas, like OfferCatalog on collections, and Product and BlogPosting on blog posts. 

GEO Can’t Wait

Retailers waiting to act risk falling behind.

Shoppers are flocking to generative platforms and are fast becoming the default discovery path for younger consumers. If your competitors are cited and you’re not, it’s not just a missed opportunity – it’s market share lost.

As Steve Williams, Buff City Soap’s chief technology officer, noted, “The time for retailers to jump into GEO adoption was yesterday. It’s a legit game-changer to crank out personalized, AI-powered content that actually connects, sells and keeps you ahead of the curve.”

GEO isn’t a nice-to-have anymore. It’s now a must-have for relevance,

reach and revenue.

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