Babel

The Secret Behind Natural Language Processing (NLP) In Retail Industry

Artificial Intelligence has comprehensively changed the traditional lifestyle. Its effects are being felt in every domain. An important subdiscipline of AI (Artificial Intelligence) is Natural Language Processing (NLP). Even as people were accepting the inclusion of AI into their lives, advancements in NLP have yet again taken mankind by surprise. NLP empowers systems to comprehend and derive meaningful information from natural language. Natural language exists in the form of text and audio. Let’s have a look at how Natural Language Processing can revolutionize the Retail Industry.  

Recognizing and Analyzing Text

There are tons of pages of text available on the Internet or any website. It would not be possible for any person to go through & understand all this data. Reading each line and deriving meaning out of it, would be too cumbersome.

NLP can come to rescue, by extracting meaningful information out of it. It can process the essential keywords. It can then apprehend the hidden meaning behind those excerpts. Retailers can use this cognizance to improve their product offerings and brand visibility. They can opt for ways which please the customers and make them stick to the brand longer. NLP can also help find the essence of the text and semantically analyze this filtered information. Thus, helping streamline the whole business process of improving Retail product offerings. 

Sentiment Analysis

These days customers have the facility of providing feedback for the products. They want the companies to provide products based on their feedbacks and comments. Whether they like the product or not should be conveyed to the top personnel of the company.

Their views and opinions matter to a great extent for the company. Their sentiments need to be considered. But how to do such impossible tasks? Well, they may seem impossible for humans, they do not trouble machines. Using NLP, we can dive into the feelings and opinions of customers. The results can then be fed into Machine Learning models. The models can be built based on certain algorithms. These models can be used to further categorize the sentiments and feedbacks of customers. The results can be incorporated towards increasing the brand visibility.  

In-Store Virtual Assistants 

Robots or Virtual Assistants can be employed at stores to interact with the customers. This ensures that customers get all the queries answered effectively and efficiently.

Miscommunication or misbehavior can be eliminated when we have machines interacting with customers. Unambiguous & repeated communication can be done with customers without any fatigue. Customers get the impression that the Store is highly modernized to have such mechatronic tools. All this adds up significantly towards making the business an immense SUCCESS 

Chatbots, a necessity

Chatbots have become a must-have feature on any website. Gone are the days when people engaged with Customer Care Executives to find a solution. These days everything has become automated.

Things work out at lightning-fast speed. Hence it becomes extremely crucial to implement such functionalities on websites. Chatbots utilize NLP to understand the needs and desires of customers. Customers can clarify their doubts with chatbots which answer the queries in real-time.  

Personalized Advertisements

Targeted advertisements help in attracting more visitors towards your business. Every Internet user has his/her digital footprint.

NLP can analyze and understand the brands and products that a user likes. Thereafter, he can be targeted with advertisements of only those brands and products. Imagine yourself wanting to read your favorite novel, when suddenly you see an online store selling the same novel. Instinctively you would want to become a potential buyer. Targeted advertisements ensure that people are shown only those advertisements which are meaningful to them.  

Recommendation System

By gaining so much information about existing and potential customers, recommendation systems can be modelled for filtering. Such systems may involve content-based filtering or collaborative filtering or could be a hybrid of the two.

They learn the shopping patterns of customers. Based on these patterns, customers could be shown products related to their previous purchases or complementing items. They can also be shown the products which other similar users have bought. Customers shed their hesitation when they find that other users have already tested the products. Hence, the brand value and trustworthiness increases, resulting in higher conversions.  

Cost Savings

With NLP automating the workflow, and doing most of the manual work, there can be significant cost savings. The workforce can be guided towards only what’s necessary. Labor costs, operational costs and others can be reduced.

  • Spending once on technology can save recurring costs in future. Any changes needed can easily be done on the technical systems. NLP can thus enhance the retail business manifold 

 
 

To make businesses resilient and ready for the upcoming challenges, it becomes indispensable to intertwine them with emerging technologies. NLP is one such technology which can help the retail business flourish in the long run. 

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