You search for a product. You find the product. You buy it. Or maybe you don’t buy anything at all – if the shop search fails you. Many shoppers lose their interest in buying anything after encountering poor or no search results in an online shop. A shop search can cause the same level of frustration as the unfriendly or little informed staff in a local store. Who would still want to shop there? So what differentiates a good search experience from a bad one? How do you stimulate a customer’s shopping mood instead of spoiling it? Setting error tolerances, offering filter options, and displaying alternatives can already make a big difference. What you should pay attention to and how unleash your full potential when you optimize your shop search.

Why Is Your Product Search So Important?

When visiting an online shop, 43 percent of users immediately use the search function instead of clicking through various categories. This shows how relevant the product search in online shops really is. Already in 2013 a study showed that the conversion rate for users immediately using the onsite search is significantly higher than the overall average: 4.63% compared to 2.77%.

And that is only natural. When customers use the search function in an online shop, they have a specific need to buy. They either already have a certain product in mind or at least know in which direction it should go. A person who is just browsing, on the other hand, may not want to buy anything at all – depending on his or her mood. In addition, those who find the desired products while searching, may stay on the site longer and find other items as well, for example, if other matching products are suggested.

Beyond the actual purchase, the search function also provides valuable insights into what your customers are looking for. Which brands or products are searched for particularly often? Are some of them perhaps not yet part of your assortment? Then it might be time to change that.

What Your Search Function Should Be Capable of

When it comes to configuring the search function in your online shop, it may help to take a look at big eCommerce players as well as successful competitors in your own industry. Many users have gotten used to their product search and expect a similarly convenient and good experience from you. Here’s what you should look out for…

Easy to find

Shoppers expect to find the search function at the top of the page of an online shop, either in the middle or on the right. A magnifier icon makes it universally recognizable. If an empty text field is already visible, this can provide even more visibility and encourage searches.

Visible on every page

Anyone who wants to search from a product or category page should not be forced to click back to the home page. So these pages should also have a search box.

Typo tolerance

One misspelled letter already gets you no results? That can have a direct impact on your sales. The search function should still be able to find and offer the right products.

Recognize synonyms and customer language

Not everyone searches with exactly the terms that are defined as a default in your online shop. In particular, when it comes to products with more technical terms, customer language can be quite different in everyday life. The search should therefore also deliver good results for synonyms and simpler terms.

Making suggestions

Autosuggest and autocomplete guide users in the right direction. Autosuggest recommends suitable products, categories, or brands directly as the user is typing. Autocomplete fills in the search query with various possibilities of how it might continue. For example, if you type in “winter”, “winter jacket”, “winter coat”, or “winter shoes” will be displayed and you can immediately choose the right one.

Provide filter options right away

If the search function immediately recognizes from which category the search query originates, it can immediately offer suitable matches that narrow down the search. The user can then select among these and doesn’t have to filter on the results page.

Stop words for more accurate results

It makes sense to generally exclude certain terms from the search that have no relevance to the search – so-called stop words. This makes the search faster and more accurate. For example, in a shop with only one brand, users may still search for the brand name and thus receive very broad results. The name can then be defined as a stop word to make the suggestions more precise.

Do Not Send Customers to a Dead End

Few things are more frustrating when shopping online than empty search results pages. The probability that customers will leave the shop in such a case is high. Those who offer search tips, on the other hand, can at least prevent this to some extent. Such tips can point to typo clues or more specific search queries. Online shops can also display related products or categories. Perhaps customers will be inspired to buy another product after all.

Configure Your eCommerce Search Based on Data

Shop managers often feel the need to define possible results for search queries. Better than a manual approach, however, is a data-driven one, where gut feeling plays no role. Relying entirely on data provides users with a better experience. For example, the Elasticsearch search engine is a powerful tool for searching high-quality product data for the right criteria. Certain aspects can be configured manually, like which attributes of the product data should be searched or how they are prioritized and weighted.

More than just product results

It might be that not only single products match a search query. A user could, for example, also search for a brand or even a specific influencer with whom the company collaborates. If you use a headless system with powerful and well-configured APIs, you can display a customized results page for each search that contains more than just products. Matching brands and categories can also be displayed, as well as other content, perhaps from an influencer or inspirational stories.

In addition to conventional search results pages, filtered product pages can also be made available via an API. If users search for “red Levi’s T-shirt,” for example, they are taken to a category page for T-shirts. This is already filtered for by the color red and the brand Levi’s. The filters can then be further customized to include blue or green t-shirts or other brands in the results.

Something for Everyone: Search Personalization

Personalization ensures that visitors receive more relevant results. This often enhances the probability that they will make a purchase. For example, to display personalized results, previous search queries (on the current or a previous visit) can be included. For logged-in customers, who have already placed several orders, the API request of a new search can then immediately feature the preferred brands. The algorithm of Elasticsearch or a comparable tool then adapts to show more products from these brands in the results. This means the experience can always be precisely tailored. And this can strengthen customer loyalty.