{"id":15552,"date":"2025-07-05T06:43:44","date_gmt":"2025-07-05T06:43:44","guid":{"rendered":"https:\/\/dmsretail.com\/RetailNews\/can-ai-fix-the-online-search-and-discovery-experience\/"},"modified":"2025-07-05T06:43:44","modified_gmt":"2025-07-05T06:43:44","slug":"can-ai-fix-the-online-search-and-discovery-experience","status":"publish","type":"post","link":"https:\/\/dmsretail.com\/RetailNews\/can-ai-fix-the-online-search-and-discovery-experience\/","title":{"rendered":"Can AI Fix the Online Search and Discovery Experience?"},"content":{"rendered":"

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Have you ever wondered why it\u2019s so easy for your shopaholic best friend to find the perfect pair of shoes online while your search for a luxurious red cashmere sweater always comes up short?<\/p>\n

For many, the online shopping experience can be frustrating, confusing and downright disheartening. The root of the issue stems from the significant disconnect between how consumers search for products online and how retailers label, describe and present them on their sites and in their ads. In many cases, though, it\u2019s not that the product doesn\u2019t exist; it\u2019s that the language they are using to describe the product isn\u2019t in consumers\u2019 everyday vocabulary.<\/p>\n

Many consumers also are taking to AI-powered search engines like Google Gemini, ChatGPT and Perplexity for their searches. This puts the onus on retailers to have product descriptions that are not only clear for consumers but also are able to be found and understood by the various types of algorithms and technologies powering traditional searches, on-site searches, and now, AI searches.\u00a0<\/p>\n

Retailers need to be both agile and savvy during this period of unprecedented transformation, and those that prioritize making their language more consumer and<\/em> machine-friendly will be the ones that have an advantage.<\/p>\n

The Criticality of Clear Product Language<\/strong><\/h3>\n

Personalization is a key element to any online shopping experience. In fact, over 70% of brands say that AI adoption will fundamentally change personalization and marketing strategies. Additionally, with this new generation of AI, 71% of consumers expect companies to deliver personalized interactions, and 76% get frustrated when this doesn\u2019t happen. Further, while most retailers and brands claim to offer personalized experiences, 66% of consumers have reported a negative experience when it comes to attempts at personalization. There\u2019s lots of upside, and AI is well-positioned to help retailers and brands finally deliver on their \u201cpersonalization\u201d brand promises.<\/p>\n

However, in order for retailers to truly understand how to leverage AI to improve their online shopping experience strategies, they must first acknowledge the roadblocks that today\u2019s shoppers face. According to a new report, 80% of consumers have given up on an online search because they couldn\u2019t find what they were looking for, and 66% said that retailers use descriptions that make it challenging for them to find what they want.<\/p>\n

When they are able to find what they are looking for online, 89% said they\u2019ve still resorted to buying the item in-store because they had questions regarding quality, fit, color or size, among other details. And to be clear, those consumers didn\u2019t actually want to go to a store; they did so only out of inconvenient necessity.<\/p>\n

This search issue is a problem, and without fixing it, retailers are at a disadvantage. According to the same survey, of the people who said that the search experience impacts their spending, nearly three-quarters (74%) estimate spending $25 or more per visit on sites where they have a positive experience. However, 85% said they\u2019d purchase a similar item from another brand or retailer if they aren\u2019t able to find what they are looking for from their initial brand or retailer choice. In short, the impact of poor product descriptions and details can mean missed revenue targets and lost customer loyalty \u2013 a deadly combination in today\u2019s hyper-competitive retail environment.<\/p>\n

If it Can\u2019t be Found, it Can\u2019t be Sold<\/strong><\/h3>\n

89% of business leaders believe personalization is valuable to their business\u2019 success in the next three years. When the first step of personalized online shopping is making it easy for shoppers to find what they are looking for, retailers need to ensure that their assortments are discoverable. One answer to this call is product content optimization \u2013 the process of enriching product data with product information that is merchant-, marketer-, consumer- and<\/em> machine-friendly to enhance product discoverability no matter where that discovery process happens \u2013 from Google and social media to on-site and beyond.<\/p>\n

Whether a consumer is browsing Instagram or TikTok, conducting a quick Google Search, or getting into the nitty-gritty of a retailer\u2019s ecommerce site to find a specific item, how products are described on each of these channels is critical. For example, an \u201cochre godet skirt\u201d from Brand A should come up in a Gen Zer\u2019s search for a \u201cshort fall skirt\u201d on TikTok, as well as a Gen Xer\u2019s search for a \u201cneutral-colored corduroy skirt\u201d on Google.<\/p>\n

However, this goes beyond basic attributes, synonyms and trends in consumer-facing contexts. Having discoverable products means that retailers also are consistently auditing and updating their data in their backend contexts to match shopper queries.<\/p>\n

There also is an increasing interdependence on product description data between ecommerce and advertising, so it is imperative that retailers maximize the effectiveness of both to ensure their inventory is always in front of the right eyes. To do so, they should:<\/p>\n