AI search engines are reshaping how shoppers find and buy products
Consumers now use longer, more conversational queries (averaging 24 words) instead of traditional six-word searches. AI-native technology bridges natural language and retail catalogs, and bots are driving significant web traffic as they crawl sites for answers. Retailers need to adapt product feeds and create custom landing pages to match these trends.
The shift from six-word to roughly 24-word queries represents a fundamental change in how shoppers articulate intent. AI systems now parse conversational language, including brand preferences and family context, which traditional keyword-based engines could not accommodate. This forces retailers to rethink catalog structures designed for an earlier search era.
Bot traffic now constitutes a significant portion of retail site visits, as AI systems crawl product pages to generate answers. Retailers must feed structured data, conversational attributes, and detailed FAQs into AI and advertising platforms to remain discoverable. The article also notes that AI lowers content creation costs, enabling custom landing pages at scale.
The rise of AI-driven shopping search could reshape consumer behavior and retail competition. Shoppers may rely increasingly on AI-generated recommendations rather than browsing directly, potentially concentrating discovery power in AI platforms. Smaller retailers without resources to optimize structured feeds could face visibility challenges, while consumers may benefit from more personalized, context-aware product matches. The shift toward agentic research traffic also raises questions about how brands measure marketing effectiveness, as impressions increasingly come from bots rather than human eyes.