Saturday, February 4, 2023

Five Ways Natural Language Processing (NLP) Creates Enormous Value for E-Commerce Businesses

By Prangya Pandab - August 22, 2022 4 Mins Read

NLP is becoming increasingly important for online businesses due to the actionable insights it offers. These insights enable businesses to make decisions that result in tangible outcomes. By automating numerous processes, it fosters growth and boosts business efficiency.

Businesses deal with a massive volume of text and speech data every day. How can they organize this data and choose a course of action? Natural Language Processing (NLP) is the solution. In many fields, data science solutions have made a significant impact. NLP-based technologies can break down the text into its constituent parts to comprehend the context and the intent. Using the NLP results, the machine can then choose which command to carry out.

Machine learning and Natural Language Processing have the potential to provide tremendous value to the e-commerce industry in several ways.

User Intent

The enhancement of the purchasing experience for consumers is one of the key objectives of online businesses. This includes product discovery, which needs the most work because it helps buyers find the products. Customers, on the other hand, are difficult to impress. Even though the search queries are initially vague, most buyers expect that the search engines will fully comprehend their shopping intent.

Also Read: Leverage Automation to Boost Employee Experience

Recognizing and examining the needs and behavior of their customers is crucial for e-commerce companies. Natural Language Processing enables machines to quickly identify the phrases and words people typically use when looking for a certain item. Users that connect with the system through a search engine can customize their searches with its assistance.

Intelligent Product Recommendations 

Typically, product recommendations are keyword-based. One will only get what they type in as a result. On the other hand, NLP has a wider range of considerations, including context and historical search data. These elements can contribute to more targeted search results.

By directing them toward the right products, it also helps the retailers keep the customers interested. Businesses will see a decrease in site abandonment and an increase in sales if they display products that meet their customers’ needs. Users occasionally tend to become lost among thousands of products. With NLP, users won’t feel overwhelmed and will find browsing through products and items to be less of a hassle. Users will have a lot better and more enjoyable experience as a result.

Also Read: Three Digital Transformation Projects CIOs Should Place a High Priority On

Search Based on Semantics

Longer search phrases, typos, and even synonyms can all be examined using semantic search. This is so because semantic search utilizes Machine Learning and Natural Language Processing. It gains knowledge on consumer behavior and purchasing habits. Based on it, it presents that customer with relevant products. The products will be re-ranked by semantic search, placing the best options at the top of the list. In this manner, the customer will remain interested and is likely to stay on the website longer.

Additionally, semantic search can examine past searches and predict what the users type. Customers can locate what they want more quickly thanks to the auto-completion provided by semantic search.

Customer Support

Most businesses are now leveraging chatbots. It has become a crucial asset in their customer service team. Enterprises are witnessing an increase in sales as a result of using chatbots. Additionally, it contributes to their customers’ overall positive experience.

These chatbots are accessible around-the-clock. Chatbots can respond to queries immediately, preventing the consumer from having to wait for hours and becoming impatient. They can manage several requests concurrently and still respond to each one.

Sentiment Analysis

E-commerce monitors social media platforms, user surveys, and product reviews for feedback on their products. However, it falls short of what NLP can do in terms of data gathering. Implementing NLP tools can help handle massive amounts of text data from emails, blogs, and other online postings. It avoids bias and recognizes even the smallest alterations in customer behaviour.

It can look for phrases and words that can be used to analyze consumer feedback on a particular product. NLP can recognize and classify emotions as neutral, negative, or positive. Businesses can better grasp what the market requires by studying customer sentiment. They can enhance their offerings and provide a more targeted experience in this way. They can also anticipate market trends and outperform their competition.

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AUTHOR

Prangya Pandab

Prangya Pandab is an Associate Editor with OnDot Media. She is a seasoned journalist with almost seven years of experience in the business news sector. Before joining ODM, she was a journalist with CNBC-TV18 for four years. She also had a brief stint with an infrastructure finance company working for their communications and branding vertical.

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