How to Optimize the Search Box of Your Ecommerce Site 

When assessing the success of a website, one should first understand what it is that it offers. Ecommerce sites are generally classified based on two parameters: the types of products sold and the nature of participants. Understanding the differences between e-commerce sites and physical stores can provide important insights into brand business models. For businesses that maintain physical inventories, logistical issues may become a problem. However, businesses that offer a completely digital product experience shouldn’t have this problem. 

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Search query 

The way you phrase your search query can make or break the user experience on your eCommerce site. While most eCommerce search solutions don’t use synonyms or autocorrect, they can still help your users avoid mistakes. For example, autocorrect query suggestions can help users type in more relevant terms and avoid bounces. If a customer types in “knee pads” in error, machine learning will suggest related products. Such functionality improves your customer experience and ensures that your shoppers find what they’re looking for. 

Search engine 

There are many options for eCommerce search engines, but there are some specific features that you need to know. It is important to understand your business strategy, as well as your current IT infrastructure. You can deploy a cloud-based search engine such as Algolia. This analytics-based solution is user-friendly and fast, with support for most major eCommerce platforms. It is also highly secure, with as-you-type filters and customizable features. It offers free and paid plans, depending on your product count and business goals. 

Search box 

Having a good search box on your eCommerce site is vital in helping shoppers find the product they are looking for. It’s one of the most important revenue drivers for an eCommerce site, yet many retailers fail to optimize the functionality and design of this component. Below are some tips for a better search box: 

NLP-enabled search 

Natural language processing (NLP) algorithms can improve the search experience for your eCommerce site by understanding your users’ intent. By analyzing their search queries, you can set up synonyms and optimize your vocabulary. One example of a smart search engine for eCommerce sites is Searchanise. It offers instant, typo-resistant search suggestions , and customizable product filters. This kind of search engine can improve your customer experience and increase conversion rates. 

Customer experience 

The eCommerce customer experience is the entire journey your customers take when they buy from you. From the moment they first visit your website, you must make sure your sales experience is seamless. From the product selection process to the cross-sell and up-sell offers, to the processing of their purchase, your site must make the customer’s experience as smooth as possible. Having a smooth shopping experience is vital to ensuring that your customers return to your site and become repeat customers.