The Importance of NLP Technology in E-commerce Businesses

The global natural language processing market was valued at approximately $11,898.35 billion in 2019 and is expected to reach $13,823.51 billion by 2020, growing at a Compound Annual Growth Rate (CAGR) of 16.52 percent to hit $29,787.47 billion by 2025.

NLP has been a buzzword in e-commerce industry for the past few years. NLP stands for natural language processing, and it’s an artificial intelligence technology that enables computers to understand human languages.

NLP allows users to communicate with computers using voice commands or text messages rather than relying on graphical interfaces like mobile apps or websites.

NPL can be used by e-commerce businesses to increase customer satisfaction levels, improve conversion rates, and reduce costs associated with the customer acquisition process.

In this article we will talk about NPL, its importance in e-commerce business, how you can adopt NPL technology in your e-commerce business for better result?

Table of Contents

What is NLP ?

NLP is an acronym for natural language processing. NLP is a subset of AI (artificial intelligence) that enables computers to understand human languages.

It allows users to communicate with computers using voice commands or text messages rather than relying on graphical interfaces like mobile apps or websites.

NLP can be used by e-commerce businesses to increase customer satisfaction levels, improve conversion rates, and reduce costs associated with the customer acquisition process.

How can you adopt NPL technology in your e-commerce business ?

There are several ways in which you can adopt NPL technology in your e-commerce business. One way is to use NPL-enabled chatbots to handle customer queries and complaints.

NPL-enabled chatbots can answer customer queries on your e-commerce website, and handle complaints without the need for human intervention.

NPL also allows you to personalize communication with customers by analyzing their purchase history.

NLP is already being used in various industries like finance, banking etc., so there’s no reason why it cannot be adopted by e-commerce businesses as well.

NPL is an amazing technology that offers lots of benefits to e-commerce businesses, so it’s worth looking into.

Customer Review Analysis

NLP can be used to analyse customer feedback and reviews to find out what customers liked or didn’t like about your product or service.

By using topic modelling or latent semantic analysis. This technique can be used to analyse customer feedback and reviews to find out what customers liked or didn’t like about your product or service.

After collecting the customer reviews from your products, we will undergo topic modelling to find the main topics in the reviews.

We will also use latent semantic analysis to find the keywords that are associated with each topic.

This information can then be used to improve your product or service based on customer feedback.

This is just one example of how NLP can be used in e-commerce businesses.

NPL offers many other benefits that can help you improve your business operations and increase customer satisfaction levels.

So if you’re looking for a way to improve your e-commerce business, NLP is definitely worth considering.

Voice search

When prospective customers search for certain words or phrases on Google, you may already be an SEO master at applying best practices to your website content in order to achieve a high ranking. Voice search optimization simply takes the verbal aspect of that approach one step further.

You’re optimizing your landing pages to show (verbally) when a potential customer does a voice search.

Once you’ve finished, it means that the device being utilized by the consumer can read out loud your webpages.

If you have an online store that sells items, then you may use voice search to allow your consumers to find those items without having to type anything in manually.

If you’re already using a voice assistant like as Apple’s Siri or Amazon’s Alexa, the ecommerce queries function in essentially the same way.

The user’s voice is compared to thousands of others’ voices, and Google’s AI software determines if the voice matches any of those recorded.

If it does not match, this technology will generate a list of options based on possible matches from previous searches or databases.

People make errors when they conduct a manual search by entering keywords.

Perhaps someone mistyped the name of a brand or product in their search queries.

When this occurs, the AI in the search engine normally recognizes the mistake and offers recommendations based on what it believes the user intended to say.

Contextual Search Engine

The NLP technology can also be used to create a contextual search engine which provides results based on the context of the user’s question rather than just matching keywords.

For example, searching for “best headphones under $100” will return different results from “I want to buy best headphones under $100”.

In this case NPL can help by providing the results for “headphones” and “under $100” together.

Contextual Search is a type of search that makes use of the web’s many contexts to find relevant results for the same queries.

On a rainy or sunny day, a query might provide varied outcomes. From winter to summer, or even from morning to night, a search engine results page layout may vary.

Recommendation System

Recommendation systems are based on artificial intelligence algorithms. User data, such as likes, hobbies, choices, and preferences, is accessible to AI.

Artificial intelligence algorithms utilize past information such as as users’ likes, interests, choices, and preferences to provide recommendations for them.

The recommendation system, in essence, determines or predicts the preferences and ratings of any product or items relevant to each customer’s selection.

These are utilized in nearly every industry to suggest a product, films, goods, songs, and videos to customers based on their prior purchase data.

The procedure analyzes past behaviors in order to provide simple recommendations.