In e-commerce, search functionality is at the heart of a successful customer experience.

In e-commerce, search functionality is at the heart of a successful customer experience.

The customer expects the search functionality of an online store to operate at the same level as search engines. Indeed, search is a crucial part of the customer experience, which at best can increase sales and at worst can be a barrier to purchasing and even damage one's image.


Implementing a product search function from an online store's selection is a successful combination of customer-centric design, psychological insight, content understanding, and data utilization.

Continuous improvement of search is both a competitive advantage and a key factor in the customer experience. Not all search fields are Google, nor do they always have the foresight and accuracy brought by artificial intelligence. Enriching search data is ongoing work influenced by the movements of competitors and the search behaviour of customers. 

Beware of misuse. The search terms used by customers are important for enhancing and developing your search data. However, never display the searches or inputs made by users directly on the site. Displaying users' searches directly on the site allows for misuse, and raw input does not serve the customer in the best possible way. 

Instead, offer identified related search terms and suggestions where content is genuinely available. It's also worth remembering that customers apply the same criteria to search features for both international search engines and small online shops.

Therefore, the basic level of the search can be considered to extend the search to product features, and not just rely on precise product names. As the service develops, elements such as data utilization and harnessing artificial intelligence for beneficial use also come into play.

Utilize synonyms in search

A successful search starts from the user experience. What is a synonym for trainers or winter tyres? Or can misspelled words be recognized?

The search must recognize synonyms, colloquial language, and common terms. For example, in the automotive world, a potential buyer might be just as likely to be buying a Merc or a Beemer as a Mercedes-Benz or BMW. It is important for an online store to recognize all these and offer the customer a similar range regardless of the spelling of the search term.

Categorize results. Grouping products helps clarify the search view and results. A high volume of results is not always the best.

Personalize search results

A key component of a good customer experience is the feeling of personal service. In an online store, this is an increasingly important part and element that customers are increasingly expecting from their service experience.

Identify your customer's needs and search history. Personalized search results for users are something more customers now expect without explicitly asking for them. For example, in a clothing store's product search, it's important that a customer looking for men's sneakers does not receive gumboots or stilettos in their search results.

Utilize campaigns and seasons. It's worth considering the influence of seasonal changes in search results, as well as various campaigns. 

Influence product sales volumes. Search results can, if necessary, boost sales and reduce waste. Offer customers products based on demand!

Utilize artificial intelligence and machine learning in search

The era of artificial intelligence and machine learning is strongly becoming a part of the search features of online stores. At this stage, leveraging these will undoubtedly benefit your position and represents a guaranteed competitive advantage.

Utilize images in search results. The harnessing of artificial intelligence allows for the recognition of product image content and matching it with the user's search. This way, the customer can describe the product they need without knowing the exact name of the product.

Anticipate search terms and offer alternatives. As mentioned at the beginning, the customer expects to receive similar service in their search results whether they are using an international search engine or an online store. Utilizing machine learning allows for the anticipation of the search terms used, making search usage more pleasant and easier for the customer. "You might also like these" search results are always a better alternative than no search results at all.

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Crasman Ltd

28 Feb 2023