For example, many keyword-based search engines lack semantic understanding (that is, they cannot understand the meaning behind language) and have trouble finding relevant results if the search terms don’t perfectly match what’s in their system. When there’s no exact match, some systems return no results at all, frustrating users and potential customers.
What’s more, different people often describe the same products using different words. Some users make spelling mistakes or use language that’s too broad. The result is the same: unoptimized search terms that can’t be processed by a rudimentary search engine.
Many e-commerce storefronts also fail to make use of user data to offer personalized search options. For example, each shopper has their own search habits, purchase history, and browsing patterns that could help tailor search results. But without the ability to understand and leverage this data, online shops fall short of providing the customized experiences that shoppers really want.