Is Natural Language Search a Must for Ecommerce or Not?

Natural language search is a search using conversational language rather than keywords. It allows users to use full sentences as if they are having a conversation with another human being. The technology that helps computers to process such search queries is called natural language processing (NLP) and is based on artificial intelligence. An example of a natural language search query could be "how to choose the best camera?":

First attempts to create search engines supporting natural language search date back to the 90s. In 1993 the START Natural Language Question Answering System was developed. It allowed users to search an encyclopedia using natural language search queries.

In 1996 Ask Jeeves was launched. It was an NLP search engine that made it possible for users to get answers to their questions in conversational language. The logic behind these two projects was rather straightforward: at that time, it was considered that computers need to be adapted to human behavior.

But soon, Google launched a keyword search engine which left competitors far behind thanks to the high relevance of search results. With the growing popularity of the Google search engine, people became more accustomed to keyword search. And soon the issue of adapting computers to human behavior was off the agenda because it was people who adapted to the computers. So, the users have formed a certain behavior pattern to search with the keywords and continue to follow this pattern until now, when shopping online.

Another rise of interest in natural language search happened with the development of voice assistants (Siri, Alexa, and others), as users most often use conversational language when talking to them. But communication patterns of people with voice assistants are not relevant for ecommerce because voice assistants are mostly used for various commands: asking for music (70%), weather forecast (64%), asking fun questions (53%), etc. Of course, voice assistants can be used for ecommerce shopping, but people rarely use them for online searches, ordering items, and making payments.

However, natural language has found its implementation in modern-day ecommerce. Let's see where it is used.

Voice search allows customers to search products without typing simply by using voice commands. Here a natural language search finds its implementation, as people use conversational language when searching with voice. However, voice search is a controversial feature, as some researchers predict it to be highly promising for ecommerce. In contrast, others argue that people are not using it intensively, and there's no chance the situation will change soon.

Ecommerce chatbots are virtual assistants that can process customers' questions and commands to complete users' purchases, offer product recommendations, or provide customer support. And, of course, they use artificial intelligence and natural language processing to keep up the meaningful conversation with the customers.

Let's wrap up everything covered in the previous part of the article to see if natural language search is a must for your business.

Chatbots and voice search can't function without natural language processing because people perceive them as communication partners and tend to use conversational language. But even if you use a chatbot or a voice search, you do not need to worry about natural language processing because it should be the concern of the developers of these apps.

As for ecommerce site search, users tend to follow different patterns: search for products using the keywords and then narrow down their search results with the filters. For example, customers will hardly enter a query "sneakers under 100$". They will likely search for "sneakers" and then use filters to narrow down search results to sneakers for less than 100$.

To sum up, it is quite possible that your ecommerce store does not need a natural language search engine at the moment. Maybe the trends will change in the future, but now it is hard to predict it.

Even though you most likely do not need a search engine processing natural language, it is possible to use the idea behind the NLP to boost the customer experience on your website. Let us share some tips and ideas on what you can do.

Invest some time in analyzing users' search queries to get helpful business development insights and understand your customers better. This also helps to expose the language they use when searching your website. The following tips will show you how to use this knowledge to maximum benefit.

After you've analyzed customers' search inputs, it's a good idea to use the language they use in the content of your website: in the product names, filters, descriptions, etc. Big brands also listen to their customers' speech, for example, Walmart. The picture below shows customers referring to medical uniforms as "scrubs" in reviews:

And this is precisely the product filter name when shopping for clothes at Walmart.

Customers may use different words to describe one and the same product: "sport pants", "running trousers", "yoga leggings", and so on. And only search engines with the support of synonyms will be able to handle all these variants and return product results instead of "no results page". You can use the data from the analysis of users' search inputs to add synonyms to your library and therefore provide a better search experience to your customers.

The result of implementing these tips will be better customer experiences and higher customer satisfaction. And, naturally, happy customers are the converting customers.

• In the early days of the Internet, people thought that computers needed to be adapted to human behavior, and for this reason, several natural language search engines were created

• However, with the success of Google, it became clear that users easily got used to keyword search, and the support of conversational search was no longer seen a must

• Natural language search found its implementation in chatbots and voice search as people use conversational language when interacting with them

• Ecommerce customers most frequently follow the behavior patterns set by Google and use keywords search when shopping online

• It is possible to use the idea behind the NLP to enhance the customer experience on ecommerce websites by analyzing users' search inputs and using the received knowledge to set up synonyms and optimize the vocabulary used for the product descriptions, names, filters, etc.

To get tools for analyzing users' search inputs and building a synonym library, install Searchanise, a smart search engine for Shopify, Magento, WooCommerce, BigCommerce, and CS-Cart. Apart from search analytics and synonyms, Searchanise provides instant typo-resistant search suggestions and customizable product filters to help you create an ultimate search experience for your customers.