Shoppers Double-Check AI Shopping Advice on Websites
▼ Summary
– AI accelerates product discovery and comparisons but increases shopping journey steps as consumers verify details on retailer sites, search engines, and reviews.
– Only 46% of shoppers fully trust AI recommendations, with trust breaking due to missing links, mismatched specs, outdated availability, or budget mismatches.
– Retailer traffic increases significantly after AI interactions, with 32% of shoppers clicking directly from AI tools and retailer site visits rising from 20% to 50%.
– The study combined 450 screen-recorded AI shopping sessions with a 600-person survey, showing shoppers averaged 1.6 steps before AI and 3.8 steps afterward.
– Businesses should align product data across channels, create comparison content, expand structured data, and monitor validation queries to maintain customer trust.
While artificial intelligence tools are rapidly changing how consumers research products, a new study reveals that these systems act more as a starting pistol than a finish line for online shopping. Recent research from IAB and Talk Shoppe indicates that AI significantly accelerates product discovery and comparison, yet it simultaneously prompts shoppers to undertake additional verification steps across retailer websites, search engines, and review platforms. This behavior underscores that AI serves to enhance, rather than replace, the traditional consumer research process.
The comprehensive report synthesizes data from over 450 screen-recorded AI shopping sessions alongside a survey of 600 U.S. consumers, providing a dual perspective of observed behaviors and stated attitudes. This methodology allows for a clear view of where AI provides genuine assistance, where consumer trust begins to waver, and the subsequent actions shoppers take.
A primary finding is that AI makes initial research faster and more targeted, particularly for comparing different options. However, this efficiency comes with a trade-off: the overall number of steps in the shopping journey increases. On average, individuals took 1.6 steps before consulting an AI tool, but that number jumped to 3.8 steps afterward. A striking 95% of participants performed extra verification actions to feel confident enough to conclude their session.
This validation process heavily favors retailer and marketplace websites. The data shows that 78% of shoppers visited a retailer or marketplace during their journey, with 32% clicking through directly from an AI assistant. The proportion of people landing on retailer sites doubled, rising from 20% before using AI to 50% after engaging with it. Once on these sites, consumers most frequently double-checked pricing and promotional deals, product variations, customer reviews, and stock availability.
Trust remains a significant barrier to the full adoption of AI shopping assistants. Only 46% of shoppers reported placing complete trust in the recommendations provided by AI. Several specific friction points were identified where trust commonly eroded, including encountering missing links or unclear sources, discovering mismatched specifications or incorrect pricing, finding outdated availability information, and receiving suggestions that failed to align with their budget or compatibility requirements. When faced with these issues, shoppers consistently reverted to using search engines, visiting retailer sites directly, and scouring reviews and community forums.
The implications for brands and retailers are substantial. AI chatbots are now firmly embedded in the mid-funnel research phase. If a company’s product data, comparison content, and reviews are inconsistent with the information listed on retail partner sites, the discrepancy will be noticed as shoppers perform their verification checks. This dynamic reinforces the critical need for maintaining aligned and accurate information across all sales and marketing channels to preserve customer confidence.
Based on these insights, businesses can take several concrete steps to adapt. It is essential to keep product specifications, pricing, availability, and variant details perfectly synchronized with retailer data feeds. Developing dedicated comparison pages and “alternatives” content that addresses the specific attributes users commonly ask AI about is highly recommended. Enhancing structured data markup for specs, variants, availability, and reviews can also improve how information is parsed and presented by AI tools. Furthermore, creating content that proactively answers common objections found in forum discussions and comment threads can help build trust. Finally, actively monitoring the search queries and online communities where shoppers go to validate information allows businesses to identify and close recurring information gaps.
Looking forward, survey respondents generally felt that AI made the research process feel easier. However, their final purchasing confidence continues to hinge on accessing clear, cited sources and verified reviews from other customers. The prevailing expectation is that AI assistants will continue to grow their influence over product discovery, while retailer and brand pages will remain the essential destination for confirming the critical details that finalize a sale.
(Source: Search Engine Journal)
