Autosuggest A search feature that surfaces relevant products, categories, and query suggestions as the user types, before they finish writing. Definition Definition Autocomplete finishes the word someone is typing. Autosuggest goes further: it proposes products, categories, and search terms the person hasn't typed yet, based on what their partial input probably means. The difference matters more than it sounds. If someone types "run," autocomplete would try to finish that string: "running," "runner." Autosuggest looks at the same input and returns things like "running shoes," "running shorts," and a "Running" category link, even though none of those share the exact letters typed after "run." One completes a string. The other guesses intent. In practice, most search boxes blend the two into a single dropdown: a few text-based completions at the top, then product suggestions with images and prices, then category or brand links, all updating with each keystroke. The line between "autocomplete" and "autosuggest" gets blurry in the UI, but the mechanisms behind them are different. Autocomplete is mostly a string-matching problem (which indexed terms share this prefix). Autosuggest pulls in ranking signals like popularity, past purchase data, and current stock to decide which products and categories are worth surfacing, not just which ones technically match. What it's used for What it's used for Autosuggest catches shoppers before they've fully formed a search. A lot of people type two or three characters, see something relevant, and click it rather than finishing their original thought. That shortcut matters at scale: it cuts down on how many searches ever reach the "zero results" page, since a suggestion clicked from the dropdown is guaranteed to lead somewhere with products, unlike a freely typed query that might not match anything in the catalog. It also surfaces things a shopper didn't know to look for. Someone typing "trail" might be thinking about hiking, but autosuggest showing "trail running shoes" as a product suggestion can redirect them toward a category with more relevant options they wouldn't have searched for by name. How Doofinder applies it Doofinder combines autocomplete and autosuggest into one results layer that opens as the user types. That layer can include text suggestions, product cards with image and price, and category links, all pulled from the same live catalog index. Which of these appear, and in what order, is configurable per store, so a store with a narrow catalog can lean more on product suggestions, while one with broad categories can prioritize category links instead. The suggestions are ranked using signals like search popularity and click history, so the products or terms that actually convert well for other shoppers get priority over ones that just technically match the typed characters. Example Case study Example A pet supply store notices that a large share of searches for "leash" return decent results, but a smaller group of shoppers type "walk" and get nothing useful, since no product is named "walk." With autosuggest active, someone typing "walk" now sees suggested products like leashes, harnesses, and reflective collars, along with a "Dog Walking Gear" category link, none of which contain the word "walk" in the product name. Searches starting with "walk" that previously led to a dead end now convert at a similar rate to searches with clear product-name matches, since the shopper is being routed to relevant products based on what they meant, not just what they typed. References Sources https://doofinder.com/en/blog/autocomplete-in-search-engine