How to Choose the Best E-Commerce Self-Learning Site Search?

On-site search function was found to be the most used tool for finding products as it was perceived as a much faster choice than category navigation. While the majority of users look up for their products through site search, it doesn’t make sense not to have a robust site search that delivers optimum results.

Choosing the right e-commerce on-site search often comes as a daunting task as it is very easy to fall victim to tempting features that may not boost conversions. Even worse, you may end up getting site search features that you will never use. Hence, it is necessary to ensure you are equipped with an intuitive site search, which not only drives your store performance, but also converts more users.

In order to help you decide what you need and what may be the best choice for your store, we have listed 5 critical features of the site search that will certainly drive conversions.

5 Important Characteristics of Self-Learning Site Search Tool

#1 Show relevant search results

We, humans, often tend to search products using our own words. The terms we search sometimes don’t match the actual product name. For instance, terms like hoodie and sweatshirt are often used interchangeably, and site search that is not efficient enough may not show results for the sweatshirts, when the user enters hoodie. Wizzy site search solves this issue by providing the same results for synonymous search terms. Meaning, you will be able to find the same products you are looking for even though if you use a different word.

#2 Allow users to narrow down results with search filters

Imagine you have thousands of products in your e-commerce store and your site search is all optimized to show relevant results. However, you will still need an additional filter program that narrows down the results. For example, if you are looking for a white shirt, your search may show 900 results, which is quite a big number to go through. Instead, allow your users to narrow down the searches by filtering through particular size, price, and patterns, and locate the most suitable products.

#3 Provide personalized recommendations

If you want to speed up the shopping process and close the deal as soon as your user visits the site, personalized product recommendation is the way to go. Use Wizzy: intelligent on-site search to monitor your users search behavior and purchase history, and use these insights to identify products, and offer personalized recommendations even before they hit the search bar. Providing personalized product recommendations have also proven to boost customer loyalty.

#4 Natural language processing ability

Since the ultimate goal of the site search is to help your users find what they are looking for, NLP plays a key role here. For instance, if your user searches ‘red and black shoes for the evening party’, the site search that is powered by NLP will show relevant results. Only an NLP-enabled e-commerce site search tool can understand conversational searches, so when you are evaluating site search providers, make sure you search those terms to see if the tool retrieves relevant results.

#5 Complete the search phrases with smart autocomplete

Autocomplete is one of the key features of a site search that uses Machine Learning to identify search patterns. With smart autocomplete, you can suggest products or categories based on what your users have entered, and allow them to quickly find the products they are looking for. For instance, if you type ‘mobile’, the site search should automatically suggests phrases like ‘mobile phones’, ‘mobile cases’, ‘mobile charger’ and so on. According to a study, e-commerce sites with smart autocomplete are likely to convert six times more customers than sites that don’t.


These are some of the essential features that every site search should have. If you wish to enhance your site search experience, integrate Wizzy’s smart site search in your website and enjoy all the features mentioned above to deliver a flawless shopping experience.

Wizzy in a Nutshell

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