AI in CX

Product Search Matters More for CX – Here’s Proof

As AI becomes more powerful, retail and ecommerce—like many industries—are looking for the best ways to leverage it. Most discussions around AI in CX seem to focus on AI-driven personalization capabilities, but there’s another big use case for AI to meet existing customer needs. According to a recent ecommerce survey, more than three-quarters of U.S. and Canadian online shoppers say powerful, easy to use search tools are a determining factor in whether they’ll buy from a website and come back to buy again.  

by Rick Sunzeri, Director of Enterprise and Sales, ClearSale

Meanwhile, 59% of U.S. adults say they’d like to use AI-powered chatbots to help them search for the products they want. That’s a clear sign that they’d like their searches to deliver better results in a way that’s easier for them to use. Retailers and ecommerce sites may be wise to allocate more of their CX resources to improving search first before further refining their personalization capabilities. 

How much do customers value easy search and personalized offers?

Some online shoppers seek out personalized customer experiences, but many more people look for sites that deliver good search experiences. In a recent global survey of consumer attitudes on ecommerce, ClearSale found that 12% of U.S. and Canadian shoppers believe that personalized product recommendations were a factor in their decision to shop online rather than in-store. But 79% said they’re more likely to place an order with an online store if it has “accurate search and plenty of useful filtering options,” and 80% said such search features made them more likely to return or become a regular customer.  

Search is even more important to online shoppers in developing ecommerce markets. Among Mexican, Colombian, and Argentinian consumer attitudes survey participants, 84% said good search and filtering options made them more likely to place an order, and 85% said those features made them more likely to return. These shoppers are slightly more interested in personalization (15%) than US and Canadian consumers, but search is overwhelmingly more important in making purchasing decisions. 

Why legacy search tools aren’t always enough

Ecommerce has been around for decades, and it underwent a major CX transformation during the pandemic, but search tools that are based on static rules are still creating friction for shoppers. One major study of search functionality across hundreds of major ecommerce sites found that 42% of those sites have problems with at least one of 8 common types of search queries. 

For example, it’s human nature to want to search by theme (“spring sweaters”) or to easily exclude some results (“spring sweaters no acrylic fibers”) without having to go through a series of extra steps or try several different search terms to find what you’re looking for. Even when shoppers know exactly what they want, sites may not return the correct result. For example, searching on one major retail site for a specific stand mixer product number plus the name of the newest color (Hibiscus) returned 50 coffee and tea options. 

It can also be frustrating or overwhelming when search results are irrelevant, but this is a common problem as well. In our spring sweater example, a search for those terms on a large retail site with a marketplace yielded more than 1,000 results. They included not only lightweight sweaters but also heavier winter sweaters, rain gear, hair accessories, flashlights, and wall decor. 

Many customers also use site search tools to quickly find information like return policies, shipping costs, and size charts. The search functionality study found that 39% of the sites it analyzed couldn’t support those kinds of searches. Taken together, these kinds of friction in the search experience illustrate why easy and effective search tools matter so much to busy consumers. 

How AI can improve the on-site search experience

AI offers the promise of finally achieving what customers have wanted all along: a search experience that understands what they’re looking for and only displays relevant results. AI’s natural language processing and large language model capabilities allow for what’s called semantic search. Semantic search “understands” the intent and context behind a user’s query, rather than applying rigid rules to it. 

With all the news coverage of mass-market new AI tools like ChatGPT and Google Bard, it’s not surprising that consumers are eager to put these new tools to work for searches. A November 2023 survey of U.S. adults found that close to 60% want AI chatbots for product search, ahead of getting personalized product recommendations and making shopping lists. 

Some major brands are already leveraging AI to improve their search experience. For example, Airbnb uses AI to augment users’ search results with properties outside their immediate search zone that may also meet their needs, based on “a wide range of factors, including price preferences, previous stays, and trip duration.” This gives users more options and without making them sift through irrelevant results. Semantic search isn’t limited to words. SAP describes image-based semantic search as another AI use case that makes it easier for customers to find products–and notes that AI search tools can also help marketing team members to quickly find thematic groups of products to feature in content. 

Adding AI to search requires investment and planning. For example, like any technology improvement, AI requires well-maintained data sets in order to learn what’s in the catalog, how people search, and what they do next after searching. Some AI tools may be able to extract relevant data from product images and documentation, which can speed up the data ingestion process. 

Security is another concern that needs to be studied and addressed before implementing an AI search solution. Recent coverage of consumer-facing chatbots doxing individuals and sharing proprietary information, data privacy is a major concern. It’s also important to make sure the AI tool will only generate valid, safe responses to user queries to maintain customer trust and prevent brand damage.  

Roughly 8 out of 10 North American consumers and more than 8 out of 10 Latin American consumers base their purchase decisions on search experience quality, according to the ecommerce consumer attitudes survey. That makes search improvements a high priority for retailers and ecommerce sites that want to increase sales and cultivate loyalty. 

AI that provides semantic search capabilities can make the process faster and more useful for customers. It can also help employees find items faster, and AI can also support more accurate personalization. Because of the way consumers view good search experiences, though, focusing on search first seems to offer the fastest time to value on improvement investments. 

Rick Sunzeri serves as the Director of Enterprise Accounts at ClearSale and is an experienced sales professional with a background in SaaS and complex network solutions. Rick specializes in enterprise-class sales with experience selling business applications to senior business and technology executives. Follow on LinkedInFacebookInstagramTwitter @ClearSaleUS, or visit  

Photo by Marten Newhall on Unsplash

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