Yes, retailers should optimize long-tail SKUs, the less frequently purchased products beyond their bestsellers. However, they should prioritize the work rather than enrich every listing equally. Marketplace, assortment, merchandising, and eCommerce teams should weigh margin, demand potential, product differentiation, and missing information. Accurate attributes and clear use cases can help AI shopping tools match these products to specific needs, giving specialized items a better opportunity to be discovered.

At eTail Palm Springs 2026, Tari Huddleston, Global Vice President Digital & Ecommerce, Revelyst, described the challenge of optimizing more than 60,000 SKUs across brand and retailer websites. Her team combined automation with human involvement to address that workload, rather than treating AI as a substitute for product expertise. As she cautioned, "bad data does not get better when an AI gets involved in it." The lesson for long-tail optimization is to improve the underlying information before multiplying it across listings and channels.

Another recent event discussion explained why specialized attributes matter: AI shopping agents may match products against detailed requirements, such as compatibility and a fixed project budget, while checking information across sources. A niche product's relevant characteristics therefore need to be explicit, not left for the shopper or agent to infer.eTail

Start with a manageable group of long-tail products that have clear differentiation and commercial potential. Identify missing specifications, fit details, and use-case explanations, then draw on verified product documentation and internal expertise to fill those gaps. Use category-specific templates to scale repeatable updates, with human review for technical claims and exceptions. Compare discovery and conversion performance before expanding the work, so enrichment effort follows demonstrated opportunities rather than catalog size alone.

Join your assortment, merchandising, marketplace, and eCommerce peers at the upcoming eTail Boston to explore how retailers can scale catalog quality and help more of their products compete in AI-driven discovery.