Onsite search in e-commerce – How shop customers find what they are looking for

Standard search with important basic functions

Standard searches vary greatly in sophistication depending on the shop system, but usually offer essential basic functions such as full-text search and simple filters.Efficient and user-oriented functions such as error tolerance, autosuggest, or the ability to weight search results yourself are usually missing. But this is exactly what shop operators expect from an onsite search: a high-quality search function and many search functionalities.

Standard searches also reach their limits when it comes to implementing individual shop requirements. These can include, for example, the mapping of business-specific processes or the adaptation of the search to the shop's own product data model.⁶

As a shop operator, you need to weigh up whether the advantages (no additional costs and no additional integration effort) outweigh the disadvantages (usually inefficient). However, especially for smaller shopsandbeginners, an onsite search of the shop system is a good option so that a search can be offered in the online shop at all. But at the latest when the search function has to be customized due to individual requirements, there is no way around an intelligent onsite search.

Greater satisfaction when using intelligent search

Only 10% of shop operators who use the standard search function of their shop system are "very satisfied." Already 60% of shop operators rely on additional modules from third-party providers. These providers show a significantly higher level of satisfaction: at 52%, providers who use an additional module or intelligent search instead of the standard search function are the most satisfied.⁷

The high level of satisfaction among shop operators using intelligent search shows that optimizing onsite search is worthwhile and that its potential should be exploited. We will now take a closer look at the important features that intelligent onsite search should include.

Thesaurus for taking language usage into account

Every shop customer searches differently. This depends on their level of knowledge, but also on geographical or demographic differences and personal preferences. The search algorithm must therefore be able to cope with different terms and spellings and understand the search input. This starts with singular and plural differences, but also affects the recognition of synonyms (e.g., socks = stockings). To avoid problems here, the thesaurus can help. This function can be used to set synonyms or alternative terms, for example.

Error tolerance to avoid zero-hit pages

Even the most attentive user makes typos sometimes.Error-tolerant searchhas therefore long been a must in e-commerce. It recognizes errors (e.g., careless mistakes and incorrect spellings) in the search entry and suggests alternative search terms to the customer that they might have meant with their incorrect entry. This prevents shop customers from landing on a zero-hit page.

For example , if a customer enters "black shirt ironing" in the ETERNA online shop, they will not be directed to a zero-results page despite several spelling errors, but will instead be shown the desired products.

Example of error tolerance in the onsite search function of the ETERNA online shop (source: screenshot from eterna.de)

Semantics for search term combinations with properties

When customers search for a specific product, their search query may include various aspects that the product should have (e.g., black long-sleeved T-shirt). In this case,semantic searchensures that your onsite search also understands thecontext of a search queryinstead of just paying attention to the exact wording. Semantics thus enables search term combinations with properties.

Autosuggest for displaying product suggestions

Autocomplete generatessuitable suggestionsfor previously entered letter combinations as soon as the search term is entered directly below the search bar, making it a welcome aid for many online shoppers. This helps to avoid spelling mistakes and improves usability. By also displaying preview images directly, shop customers get a good idea of the products in the range and can navigate more quickly to the desired product detail page.

If a customer searches for water glasses in the Fackelmann online shop and starts typing the term into the search field, matching suggestions are displayed directly below the search bar. In addition to search suggestions, shop customers can also view products with preview images and additional information such as the respective price.

Example of the autosuggest function for onsite search in the Fackelmann online shop (source: screenshot from fackelmann.de)

Result management for manual configuration options

Despite intelligent algorithms, it is sometimes desirable to make manual adjustments to search results, e.g., to support specific marketing campaigns. These can be implementedusing results management. For example, this allows you to change the order, weighting, and prioritization of certain products in the search results, or to remove them altogether.

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Link Finder for implementing content commerce

Not every user searches exclusively for products and categories in online shops. Instead, site search is often used to find useful content. There is also a function for this, called Link Finder, which can be used to easily find the imprint, terms and conditions, blog articles, etc. This can be particularly helpful in the B2B sector, where many products require explanation and further content is therefore welcome.

In the Villeroy & Boch online shop, customers can find numerous products as well as useful care instructions for various products.

Example of finding content using the onsite search function in the Villeroy & Boch online shop (source: screenshot from villeroy-boch.de)

Faceted navigation and sorting function for narrowing down and sorting results

After Search Navigation includes the sorting and filter functions of the onsite search. Dynamic facet filters narrowdown the search results according to specific criteria. Examples of facet filters are filtering by color, size, and brand. Once the filter has been applied, only those products that match the selected characteristics are displayed.
The sorting function, on the other hand, only rearranges the search results according to specific criteria such as price, offer, and release date. Both functions give the searcher a quicker overview of the products that match their search query.

Shop customers browsing the A-Z Gartenhaus online shop can use various after-search navigation options for their product research. On the product overview pages, they will find a faceted navigation feature that allows them to narrow down products according to specific criteria with just a few clicks. Shop customers have access to many different filters, some of which are visual. Customers can also use the sorting function to reorder products (e.g., by popularity or rating).

Example of sorting and filter functions for onsite search in the online shop of A-Z Gartenhaus (source: screenshot from gartenhaus-gmbh.de)

Would you like to learn more about the intelligent search function and see how it works in practice? Then take a look at our short explanatory video!

In addition to all the features presented, it is important to customize the onsite search for your online shop. This is because every shop has different requirements based on its products, their descriptions, and its customers and their search behavior, which can be implemented through an intelligent onsite search.