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Natural Language Processing

6 Best Use Cases To Save Customers’ Hours Of Time Using NLP

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Natural Language Processing (NLP) is a part of ML Algorithms. It interprets & analyzes the words, sentences, and context of human searches and queries. As a subset of AI, it provides the answers through smart coded algorithms without human interventions.

Customers are always searching for the best services. And this is why many businesses have started investing massive capital into applied data science, ML, and AI technologies.

Business is heavily dependent on words to convey that customers search for using human languages. Therefore, NLP Solutions have carved out solid ways to enhance customers’ experiences.

Introduction

With growing technologies, hassle-free services look pretty innovative. But the truth is NLP has been part of our lives for years now. And customers from all across the world interact with NLP each day, without even realizing it.

According to the surveys, Gartner predicts that 45% of interaction with technologies would be conversions using smart devices. Most of them will be by voices, image searches, and others. Also, according to the research, it says that chatbots and automation can handle 85% of the customers’ communications.

Usage of Amazon Alexa, Google Home Assistant, Microsoft Cortana, and Apple Siri is rapidly growing these days. Over 66.4 million people who use smart devices are not using them to know about weather conditions anymore.

They started using it beyond that, from listening to the news to searching online, everything they can do is without typing.

Here are the SIX best use cases you can implement to provide the best customer experience. And save a lot of their time through ML algorithms by voice recognition and intelligent searching.

Intent Classifications To Understand Your Customers.

It consists of identifying goals or purposes that underline a text. They have the best applications in chatbots and also can drive more benefits in sales and customer support areas.

Through intent classification techniques, you can analyze customer interactions. Through emails, chats, or social media posts, you can know their intent. And spot whether they are ready to buy or not. It is the best and faster way to classify the leads and sort them into different categories.

Whenever there arises any issue, customers can raise their complaints. And you can solve them through customer support tickets through churn prevention and strategy to win them back.

Chatbots and Virtual Assistants Can Manage Business in Your Absence

Chatbots and virtual assistants give automatic replays with personalized messages. They can understand customers’ language and deliver appropriate responses through NLP. Using ML algorithms, predefined rules get coded for answering questions. Through which chatbots learn how to respond to any quest.

These smart virtual assistants can handle 80% of the routine queries that are more complicated questions. And the best part is they are available 24 × 7, can interact, and handle multiple customers at a time, even if in your absence.

Speech Recognition To Understand Human Languages

The demand for speech recognition is rising; more and more apps are starting to integrate voice search. They are an essential part of every business these days. Alexa, Siri, Cortana, and Google Assistant are providing the best user experience through smart devices.

Speech recognition technology uses NLP to translate the spoken languages into machine-readable. Through this, they interact with the customers directly and provide them what they are looking into for purchase and service intent.

You have already heard that voice search is rising. The prediction says that more than 37% of the search will take place without a screen by 2021. This smart technology can call, send emails, and translate into various other languages.

Urgency Detections To Leave a Positive Impact

Using NLP techniques, you can determine urgency in texts and train urgency detection models based on your criteria. It will help you to prioritize the most vital request and make sure they do not remain unchecked in the piles of unlisted complaints. Urgency detection makes you reply faster, leading to a positive impact on customer satisfaction.

Auto-Correct Suggestions To Keep You Error-Free

Customers are always in a hurry; typos are the most common mistakes to them. Customers fade up when they do not get that they have been looking for a purchase or services. There are high chances that they may end up taking more time or turn down making a purchase.

Therefore, auto-correction and suggestions play a vital role in displaying what customers are looking for services or purchases. Natural Language Processing helps in autocorrecting those typos and suggest them with actual terms. That enhances customer services.

Tools like Grammarly use NLP to give better suggestions and make writing more effective and polished. It can detect grammatical, spelling, and sentence structure errors.

Market Intelligence For Better Marketing

Marketers use NLP to learn about customers’ behavior and use these insights to create effective strategies. By analyzing search queries, sentiments, and intent in unstructured data can boost your market research and business opportunities.

Sentiment analysis helps you in narrowing down to identify the pain points and keep an eye on competitors and their approaches.

Conclusion

NLP has many exciting applications to save customers’ hours of time. Through huge unstructured data that include customer support, social media reviews, survey responses, and more. Companies get insights, and that helps them in better decision-making and automate tasks to provide better customer service.

The use cases show how NLP has the best and wide applications across industries. NLP technology is evolving, bringing new opportunities to the market. It maximizes productivity, streamlines operations, and yields productivity from routine processes.

Ram Tavva is a Senior Data Scientist and Alumnus of IIM- C (Indian Institute of Management - Kolkata) with over 25 years of professional experience Specialized in data science, artificial intelligence, and machine learning.

Ram has conducted myriad Project management and ITIL Process consulting engagements in various organizations. He’s performed maturity assessment, gap analysis and project management process definition and end to end implementation of project management best practices.