How Generative AI is Transforming Search in Retail

Search plays a pivotal role in the customer journey, and generative AI has transformed how consumers discover products. With 40% of shoppers turning to search engines instead of retail websites or marketplace filters, those offering a more intuitive search experience have a clear advantage.

As interest in AI-driven tools grows, retailers are rushing to adopt generative AI. But speed alone won’t lead to success. The real differentiator is thoughtful execution. The goal is not to be first, it’s to build a solution that shoppers will use and trust at scale. Strategic investment starts with asking the right questions, and the tips below offer a smart place to begin.  

How to Use Generative AI

• Generated Content: Generative AI can transform search results into dynamic written content, such as personalized shopping lists. A single search can produce insights from product specs, reviews, and price comparisons—all tailored to the shopper’s intent. By combining discovery, evaluation, and purchase into a single, seamless journey, brands create a self-contained shopping experience that keeps users engaged from start to finish.  
• Conversational Search: Unlike traditional algorithms, LLM-powered search engines understand the context behind conversational searches. When trained in a brand’s product catalog, they can deliver far more relevant results, enhancing the overall shopping experience. This improves accuracy for specific item searches, boosts customer satisfaction, and encourages loyalty. At the same time, conversational search invites exploration, often surfacing products shoppers hadn’t initially considered and driving higher conversion rates.
• Text and Images: AI-powered search has the potential to unify visual and text-based search by processing and generating both images and text. Shoppers can refine visual searches with text or use a generative AI tool to create an image of an imagined item, which the engine would then match to real products. This integration reduces friction, especially for brands with large or diverse catalogs. More importantly, it empowers shoppers to find items they may struggle to describe, making discovery-driven searches more accessible.
• Chatbots: Powered by large language models, this AI goes far beyond traditional rule-based bots, using natural language understanding to interpret intent and respond appropriately. On the back end, they apply natural language processing to pull context from product descriptions, reviews, and FAQs to deliver relevant, real-time answers. This creates a smoother shopping experience where customers can discover products, ask follow-up questions, and complete purchases all in one interaction.

No matter which tool (or combination of tools) a brand invests in, they should take a phased approach, prioritizing solutions that directly enhance customer experience, streamline operations, and drive measurable growth. Our advice: start with product listings before moving from one step of the purchase journey to the next.  

These tools not only meet rising shopper expectations but also help brands stay agile in the face of shifting search behaviors. Success depends on ongoing optimization that includes tracking real user engagement and iterating based on performance.

Generative AI Best Practices

As generative AI becomes more integrated into search experiences, it's important for brands to carefully consider its impact on the user journey. To ensure adoption and long-term value, brands should approach implementation thoughtfully and strategically:

• Prioritize User Experience: Shoppers may be hesitant to use AI features if they’re buggy, slow, or inaccurate. Early missteps can quickly erode trust. Invest in rigorous testing before launching and ensure the tools reduce friction rather than create it.
• Path to Purchase: Generative AI can be effective at guiding shoppers through discovery, evaluation, and decision-making. Consider how these tools can simplify each stage. For example, helping users find the right product faster, comparing different varieties of the same product, or offering real-time answers to common questions.
• Don’t Rush: Generative AI is still evolving, and most tools benefit from extended beta testing. Take the time to gather feedback, monitor performance, and refine the experience. A slow, intentional rollout can build stronger long-term engagement.
• Use AI As an Enhancement: Many shoppers will still gravitate toward traditional keyword search, even if AI is running behind the scenes. Position conversational and visual search as optional, value-added features that complement—not replace—the core search experience.

Rather than chasing the latest trend, ecommerce brands should focus on building AI experiences that deliver accurate, helpful results, and seamlessly support every stage of the buyer's journey. With strategic planning, phased rollouts, and a commitment to continuous optimization, brands can turn generative AI from a buzzword into a long-term advantage.