Why autosuggest is an important part of ecommerce search engine

What does autosuggest mean and why is this feature so important?

Autosuggest (also known as Type Ahead) refers to the suggestion functionof ecommerce search engine. As you type in your search terms, matching words and products from various areas (e.g., product, category, content, etc.) are automatically displayed in a preview window below the search field. The more of the word or search term combination is typed, the more accurate the suggestions displayed in the preview window become. As you type, asearch algorithm searches the product catalog in a few milliseconds and adjusts the list of suggestions. Autosuggest is important because it greatly helps users navigate the online shop.

Similar to brick-and-mortar retail, when a customer enters a store, they look around and orient themselves based on the product categories on display to find their way to the desired product. Auto-suggest search is an important feature that enables the same experience in online stores.

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How autosuggest search works

The basis for autosuggest search is the:

• Product catalog. Specific attributes from the feed are indexed and weighted. This makes the autosuggest feature incredibly fast. The labeling is based on empirical values, but can be changed at any time. The product catalog is searched via a
• Search algorithm that scans the indexed components of the product catalog in a few milliseconds and displays the final result in the preview window. The criteria used by the search algorithm are discussed with the shop operator in advance. For an optimized suggestion, the following factors play a role:
• The click and purchase behavior of online shoppers plays a role. The search algorithm accesses a knowledge base and first displays the suggestion in the preview window that has the higher click and purchase behavior. For example, if running shoes with similar spellings (e.g., Adidas and Asics) are searched for, the search algorithm checks how many products of each brand are available in the range and which is more popular with online shoppers. This is then displayed. It is also possible to display a personalized product suggestion based on the individual customer, e.g., sports shoes for women if the online shopper is recognized as a woman. In each individual case, it must be checked which solution makes the most sense for the online shop. An integrated tracking code is required to retrieve the information, which stores anonymized data about the online shopper in the knowledge base.

By clicking on the Autosuggest preview window, online shoppers are taken directly to the product detail page, arelevant results list, or a content article related to their search query. This makes it easy to quickly find the desired item or further information.

Example of autosuggest at Tableware24

When the term "best" is entered in the Tableware24 online shop, a preview window with suggestions opens after the first letter is typed. Various products are displayed on the right-hand side, which immediately lead to the product detail page. On the left-hand side of the preview window, matching suggestions (e.g., category and product type) for the search term are displayed. Here, you can navigate directly to the results list for "cutlery" or "cutlery set." You are then taken back to the product detail page.

Autosuggest function of the Tableware24 online shop for the search term "best" (source: screenshot from tableware24.com)

When the term "vase" is entered into the ecommerce search engine, Tableware24 displays products, content, and search suggestions. A selection of different vases appears on the right-hand side. These can be selected based on the click and purchase behavior of the respective online shopper, for example. The left-hand side refers to content as well as various brands. The online shopper has the option of clicking on "vases" to learn more about them and access various brand results lists. This means that content posts and brands can also be integrated into the ecommerce search engine. It is also possible to place content posts in the autosuggest preview window with text and a preview image, as well as to forward directly to the content post.

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Autosuggest function of the Tableware24 online shop for the search term "vas" (source: screenshot from tableware24.com)

Conclusion: Autosuggest offers comprehensive service

Autosuggest is an essential part of ecommerce search engine and offers online shoppers a comprehensive service as soon as they start typing their search term: assistance with orientation and navigation to the appropriate product detail page. To ensure that autosuggest works properly, it is important to tailor it to the online shop. The product catalog must be labeled, weighted, and the search algorithm configured. The integration of click and purchase behavior also ensures a fine-tuning to display a sorted preselection to the online shopper. Autosuggest thus helps to prevent bounce rates in the shop and increase conversion. The autosuggest function is therefore an important part of ecommerce search engine.

Discover how Gartenhaus increases the click-through rate on product overview pages by 4.23%:

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