What Is Autosuggest and Why Is It So Important?
Autosuggest (also known as typeahead) is a function of the intelligent search that proposes suggestions to the user. Corresponding words and products from various areas (i. e., product, category, content, etc.) are automatically displayed in a preview window below the search field. Consequently, as more of the word or search word combination is written out, increasingly precise suggestions can be displayed in the preview window. As the user types, the product catalogue is searched in milliseconds using a search algorithm, and the suggestion list is displayed. Hence, autosuggest is an important feature as it greatly contributes to the user orientation in the online shop.
Consider for example a costumer entering a local store. They will look around and orient themselves by using the goods displayed to find their way to their desired product. In an online shop, the autosuggest search meets an equivalent purpose.
How Does Autosuggest Work
The basis for an autosuggest search is the:
- Product catalogue. Certain attributes from the feed are indexed and weighted. In this way, autosuggest can work incredibly fast. Labels are decided based on empirical values, but they can be changed at any time. The product catalogue is searched via a
- Search algorithm, which runs through the indexed items of the product catalogue in a matter of milliseconds and issues the final result in the preview window. The criteria used for the search algorithm is discussed in advance with the store owner. For an optimised suggestion, the
- Click-and-buy behaviour of online shoppers plays a role. The search algorithm accesses a knowledge base and initially displays the suggestion in the preview window, demonstrating the most likely click-and-buy behaviour. For example, if the search is for running shoes with similar spellings (i.e., Adidas and Asics), the search algorithm finds how many products from the respective brands are in their range, and which is most popular for online shoppers. This is then output for the customer. It is also possible to issue a personalised product suggestion, which is based on the individual customer, i. e., sports shoes for women, if the online shopper is recognised as a woman. In certain cases, it is necessary to check which solution makes most sense for the online store. An integrated tracking code, which stores anonymous data on the online shopper in the knowledge base, is required to retrieve information.
By clicking on the autosuggest preview window, the online shopper is directed straight to the product details page, a corresponding results list or to a content piece related to the search request. This means that the desired item or additional information can be found quickly.
Do you have an autosuggest search in your online shop that automatically adds search terms and allows the online shopper to be redirected directly to product detail pages, results lists or content articles? What experiences have you had with this? Tell us about it!
Autosuggest Example at Tableware24
If the term “best” is entered in the online shop of Tableware24, a preview window with suggestions opens after the first letter. Various products are displayed on the right-hand side, which immediately lead to the product detail page. On the left side of the preview window, the matching suggestions (e.g. category and product type) for the search term are displayed. Here you can navigate directly to the list of results for “Besteck” (cutlery) or “Besteck-Set” (cutlery set). The path then leads back to the product detail page.