Provide accurate suggestions with Autocomplete by leveraging your users' search queries and data.
With Algolia’s autocomplete functionality, users generate new, relevant autocomplete predictions with every keystroke. Our autocomplete feature lets them stop typing in the search field, and from the dropdown, select what they’re seeking, with the result being a better, more interactive search process and user experience.
Autocomplete suggestions help searchers by offering longer queries below the text box based on what they start typing as a partial query. People who use autocomplete get suggestions that are more precise. That precision, in turn, produces more-accurate results so the searcher can more efficiently select the web page, content, or products they’re seeking.
With autocomplete search, you reduce the number of keystrokes needed for on-the-go users to enter in their iOS or Android mobile devices. Less time typing and trying to avoid typos in a user interface on a mini screen means more time finding the right results. As an online retailer or informational site, you can increase engagement and optimize your user experience with stellar, fast mobile search.
You can always show your users popular searches. One step better: leverage search history. With Algolia Personalization, you can provide an individual level of relevance on the autocomplete list of suggestions shown to each user based on their expressed interests, gleaned from their previous search terms and enrichment data.
Query Suggestions works with multiple autocomplete data sources in order to always provide the best auto-suggest queries to your users.
To help users access the information, content, or products they need fast, Query Suggestions analyzes your indices, including the attributes for filtering and faceting, so you can provide search suggestions for the right content category (and never point to a no-results page).
Suggested queries are generated and ranked based on what your users search for and how they use the autocomplete function to refine their searches. This data is updated daily. And when you combine use of auto-suggest with our Personalization product, suggestions are further refined based on each user’s affinities and profile.
You can pull in Google Analytics or use your other external analytics tool of choice to further refine your auto-suggest feature to meet user needs, giving them the quality of autofill results they’d get from doing an Amazon or Google search.
You can fine-tune Query Suggestions for your key use-case scenarios.
You can use rules to boost specific suggestions in your autocomplete search feature, such as for trending items on your e-commerce sites. Another option: displaying banners in rich autocomplete for specific keywords or contexts. Plus, you can create synonyms to give users the best autocomplete options with related keywords, even if they enter search terms that aren’t in your catalog in the search box.
You can ban any keywords that you don’t want appearing in suggested user queries. Query Suggestions also takes this a step further and ignores multiple repeated similar queries from the same IP address.
Take charge of your granular query-suggestion settings, including which attributes to show in users’ text search suggestions, the minimum number of characters required in the text field for a suggestion to be surfaced, and more.
Hear how Kiabi transformed their omnichannel strategy to achieve a 15% increase in click-through rates, while effortlessly halving their “no result” rates.
Just like the Spice Girls knew what their fans really, really wanted, Algolia’s Ben Bulpett explains how Algolia's personalization capabilities can add that special 'spice' to your customer experience
In today’s digital landscape, the footwear industry is undergoing a transformative evolution. Modern consumers now expect a seamless, interconnected, and personalized shopping experience.
Query Suggestions, or Autocomplete, are only suggestions of better queries. For instance, if a user starts entering the snippet “smartphone,” they would be invited to choose a more precise query such as smartphone apple or smartphone iphone xs. With a more finely tuned query like that, their odds of retrieving the right search autocomplete results would increase.
Yes, you can combine different suggestions types, such as for products, categories, brands, articles, and blog posts, on a single autocomplete menu. You can even display multiple sections of results generated by searching different indexes or searching for facet possible values.
The Query Suggestions builder normalizes and completes suggestions to remove suggestions that are duplicated, similar, or have a prefix.
You can also customize a set of configurable constraints that disqualifies search terms from your suggestion index. If a suggestion matches any of these criteria, it’s not included as a search term:
Top searches from the Analytics API are aggregated, but the builder goes further. Here’s a good example: if tablets, Tabl, Tablets and tablet are top searches in your source index, the builder would narrow the specification to the term with the most searches.
It’s also a good idea to correctly designate the language, as well as remove irrelevant and inappropriate searches by configuring the banned expressions.
The builder rebuilds the index once every 24 hours, or whenever you change and save its configuration. Query Suggestions takes into account data items in the last 30 days, and the index is based on a sliding window of the most recent analytics data. When calculating suggestion popularity, searches made earlier in the 30-day period don’t count less than those made more recently.