Fuzzy search is a type of search algorithm that allows for imprecise matching of search terms, in contrast to exact or strict matching. It is particularly useful in ecommerce, where users may have trouble spelling or describing a product accurately.
Fuzzy search takes into account variations in spelling, word order, and even synonyms or related terms, to return a list of results that match the user's intent as closely as possible. This can greatly improve the user experience by reducing frustration and increasing the chances of finding what they are looking for.
One use case for fuzzy search in ecommerce is product search. For example, let's say a user is searching for a particular type of footwear, but they are unsure of the exact spelling or terminology. They might search for "sneekers" instead of "sneakers", or use a more general term like "running shoes". Without fuzzy search, the system might not be able to find any matches for these search terms and return no results. Fuzzy search can also be used to provide auto-suggestions for search terms as the user types and personalized product recommendations based on the user's search history and browsing behavior.