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The ecommerce product finder should be placed in a place that is easily accessible and intuitive for the customer. This is most often located in the upper right corner or in the middle of the homepage. Ensure that the customer has no trouble finding the search engine by making it intuitive and usable.
A new era in product search is ahead of us, in fact we are already in it. Smart search is becoming a reality. Google is experimenting with innovative solutions, and users expect more and more precise results. Are you an online store owner? Your product search function leaves much to be desired? You can't afford it! It's time to change it.
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In an online store, the heart is the product search engine. It is the one that drives the customer to buy, enables him to find the items he is looking for, makes various suggestions. Nevertheless, it can also alienate, disappoint and drive the user to search in competing stores. Therefore, it is crucial that the search engine meet customers' expectations by adapting to their needs and remaining relevant. Users adapt quickly to smart solutions offered by industry leaders. If the search engine is outdated and the customer doesn't find the information he is looking for as quickly as he would like, we risk losing him to the competition.
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A standard search engine, in addition to a field for entering a keyword, may already include the ability to personalize the search at this stage.
Personalization can direct the user from here to the results that are in his field of interest, for example: we can give the opportunity to search in a specific category or main filters such as location in which we want to search the phrase / for example, real estate search engine.
A modern approach to the search engine theme is presented in the following view
We agree that this is an interesting design approach that may appeal. The innovation of the proposal may tempt ecommerce owners and UX/UI designers, the problem we see with this solution is that it departs from the typical ecommerce UX solutions that online store users are used to, which may cause problems with the user experience of this type of innovative search engine and generate potential losses.
An example of a successful solution is Answear's search engine, where the product search engine is located in the upper right corner. In addition, in the form of animated captions, the search engine suggests what you can type in.
After entering the password and clicking the magnifying glass icon, the user is shown an expanded panel with :
An online store should have a search engine that is great at dealing with typos and spelling errors. The number of users making these types of mistakes is significant, which is easy to see by analyzing Analytics statistics. The search engine should be able to adapt to popular mistakes, which is also supported by the habits of users using Google. Even with misspellings, the search engine should suggest corrected phrases or inform that it presents results for the correctly spelled phrase as well. This allows the user to continue searching with an error, if that is the user's intention.
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When designing or improving an online store's search engine, it is also worth focusing on product filtering and sorting functions. These functions prove to be extremely useful, especially when the store offers a wide assortment and manually searching all products would be very time-consuming. For example, on the Allegro platform, customers have access to various sorting options, such as relevance, price or popularity:
And the filtering function, located in a side panel on the page:
The auto-complete feature is a fairly obvious element, but unfortunately many online stores do not take advantage of this possibility. It is worth implementing it on your platform, as it significantly simplifies and speeds up the search process for customers. The Allegro portal makes great use of this feature:
Going further, you can implement the solution of dynamic prompts in specific categories already at the stage of entering a phrase
Prompt the user where to go to find interesting products or an issue at the phrase entry stage
Is your product search engine able to consider synonyms? Customers may use different terms to describe the item they are looking for, for example, a turtleneck may be referred to as a pullover and a phone as a smartphone. Check if your search engine can recognize synonyms. If it does, great! If not, it would be worthwhile for it to at least direct the customer to the right place, where content, suggestion or option of interest to the user will appear instead of the standard error. For example, when a customer searches for a laptop in an x-kom store, the search engine could already at this stage suggest to him what else he might be interested in:
Nowadays, the consumer expects personalized offers tailored to his preferences. When he is logged in, some platforms offer him products that are in line with his previous interests and fit his profile and needs. Examples of this approach can be found in services such as Amazon, Spotify and Tidal:
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A search engine you might be inspired by is the twitter search engine. When typing a phrase, twitter offers the option to navigate to tags or recent posts related to the keyword phrase you are typing.
The current common practice is to avoid giving the user blank results. Lack of suggestions for similar products can result in an unfavorable user experience and prompt the user to leave the site.
We can see this by analyzing the approach of two platforms, sklephp.co.uk and mediaexpert.co.uk, to taking care of user comfort.
Sometimes on large screens, the query input field can be hard to see. In addition, on mobile devices, the magnifying glass icon used for zooming is often hidden in a hamburger-type menu, which can negatively affect user convenience by increasing the user's workload. Ensure the visibility of the search engine on smaller screens, for example, by placing it under the logo in the form of a wide bar that is easy to click on.
Waiting a long time for results (more than 10 seconds) can be frustrating for users. To improve the experience, it is advisable to use a progress indicator that clearly indicates the time it takes to complete the search. Additionally, interesting animations can make the waiting time more enjoyable by distracting the user from the ongoing process. With this approach, users are sure to appreciate the efforts to improve the app's user experience.
For an extensive product range, there is a need to include additional search criteria.
For example, on dodrukarki.co.uk this functionality is correlated with automatic sorting and filtering, which are activated when a query is entered.
Presenting the number of available search results allows the user to decide whether he or she wants to take the time to review the results. You may want to further narrow your search criteria to get more precise results.
The use of a separate scroll area inside the automatic suggestions box is not a favorable solution and should be avoided to avoid too many items and hinder user interaction.
It is incorrect to use a text field that is too short, as users can still enter long queries, but only part of the text will be visible. This will make it difficult to edit and view full queries. It is recommended that the text field accommodate at least 27 characters to handle 90% of queries.
According to the study, 84% of online stores fail to tailor search results to subjective categories such as "cheap," "high quality" or "beautiful."
It is important to monitor such phrases and queries appearing in the store's analytics, and then tag products accordingly based on the keywords.
Modern search engines, such as Google, are based on advanced search algorithms using machine learning technology. Machine learning is a field of science that is part of artificial intelligence (AI). Its main goal is the practical application of an automated system that can improve itself with the help of collected information, without the need for further programming.
Machine learning-based e-commerce search engines combine keywords with a variety of data, such as click-through rates, conversions, customer reviews, advertising inventory and margins. Each search contributes to improving the relevance of the results, and this process of system improvement takes place with thousands of searches each day.
Search result optimization, image recognition, data analysis as part of a marketing strategy (advertising campaigns, retargeting, newsletters), data analysis to support the sales process (product sales history, cross selling), voice search, chatbots, virtual advisors and automated customer service - bringing more context to phrases typed into an online store's search engine is aimed at increasing conversions. Today, the field of modern technology, including artificial intelligence, is becoming more and more common. We can expect to see the developed use of behavioral psychology in machine learning technology soon as well. In the context of improving search engines, there will certainly be innovations. Although not widely used at present, it is worth being aware of the changes in the virtual world that will develop in this fascinating field.
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Let's start with an important insight from the article titled "Mental Models For Search Are Getting Firmer." It addresses the key expectations of online store users and the placement of the search engine on the online store.
According to research conducted by Nielsen Norman Group, the design of the search field should address customers' mental models. In the context of search, these models are mainly shaped by popular search engines such as Google and Yahoo.
The components of a search engine have become conventionalized, and as a standard it should include:
Although there are some departures from this convention (such as replacing the bar with a magnifying glass icon), it is still the most common, understandable, acceptable, desirable and well-liked form.
Search fields usually:
Additionally:
Unfortunately, e-commerce customers are very demanding, and the list of their expectations is even longer.
Search engines should additionally provide:
Achieving this effect depends largely on the color scheme of the strip.
The easiest recognition of the search field can be achieved by using:
While there has been a noticeable recent trend toward a more subtle, transparent look for the search field, from the perspective of ease of identification, such a move seems debatable.
It is worth remembering that the search engine in an online store plays a key role for the customer and should be easily accessible.
Choosing the right search engine for your online store can be a challenge, given the variety of tools available on the market. The features, flexibility and billing model vary considerably, so it is crucial to find the option that best meets the needs of your e-store.
Remember that a key element of search engine optimization for an online store is carefully created product descriptions. This well-thought-out content also affects your site's positioning on Google.
When creating product descriptions, it is worth paying attention to:
It is also important to give product descriptions the right structure, use precise naming rules and assign appropriate labels. This is all to improve search engine performance and increase the visibility of your online store.
The search engine is a key element of customer navigation in an online store. It enables products to be found quickly and efficiently, increasing customer satisfaction and conversion.
Personalizing results based on a customer's search history helps deliver more tailored suggestions, increasing the chances of closing the deal.
Semantic search is based on understanding the meaning of phrases and context, resulting in more precise and intuitive results compared to traditional keyword-based methods.
Empty results can lead to frustrated customers and discouraged purchases. Therefore, it is important to avoid situations where lack of results can discourage users.
Yes, modern search engines often use artificial intelligence, including machine learning, to refine search results and deliver a more personalized shopping experience.
For mobile users, the search box should be easily accessible, properly configured for a touch interface, and provide an intuitive experience regardless of screen size.
Yes, features such as voice search and data analytics can significantly improve the customer experience by providing more advanced and intuitive search tools.
Developments in technology, such as artificial intelligence, machine learning and data analytics, promise to introduce more advanced features, increasing the effectiveness of search and personalizing results.
Search engine with option to remember recently searched or popular products.
A search engine that suggests dynamic retrieved prompts depending on the letters typed.
Search by zip code to narrow results to a particular area.
An example of a search engine showing tags when searching for a product and the ability to go to a complete list of searches in the form of a subpage - CTA 'show more'.
Search engine showing results from several categories: news, categories, most popular
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