“Text analytics can help organizations discover patterns in large unstructured data sets. Unstructured data, such as videos, photos, and audio accounts for at least 80% of your company’s data, a true blind spot for most businesses.”
Data scientists use advanced data science approaches to examine text. This textual data provides a better understanding of client attitudes toward certain topics or uncovers additional information.
Using this text analytics, you can turn free-form text into structured data for use in prediction models or uncover hidden patterns in your data. If you want, you can use text analysis to identify prospective customers who might be interested in cross-selling, forecast customer attitudes, and understand fraud-prevention behaviors.
Businesses understand the value of their raw text across all industries. As a result, with the help of data, they can reduce operational expenses, find previously unknown linkages, and get a better insight into the future trends.
Is it hard to comprehend that text accounts for 80% of all corporate data?
Online reviews, call center transcripts, consumer surveys, and other written documents are examples. This raw text data is a gold mine for understanding customer attitudes. Text mining and analytics transform these underutilized data sources into actionable information. However, each organization must have the expertise, infrastructure, and analytical perspective to implement this cutting-edge technology in their own way.
How is Text Analytics Used in Companies?
Companies can use NLP and untapped data sources in a number of ground-breaking ways.
Many businesses are already successfully employing text to drive their operations. In addition, text analytics can help you improve your procedures if you're transitioning from business intelligence reporting to data science.
Best Five Text Analytics Use Cases for Businesses
Companies and people, regardless of industry, desire to make better-informed business decisions based on trackable and measurable data.
Thanks to improvements in text analysis, companies can now mine the text for insights and improve their service or offering to thrive in their industry.
Read on to understand some of the text analytics use cases that could be applied in your company.
Voice of the Customer (VOC) to Extract Customer Opinion on a product
Companies employ VOC applications to determine what customers say about a product or service.
Emails, call center logs, surveys, and social media streams such as blogs, tweets, forum postings, newsfeeds, and so on are examples of data sources.
A telecommunications company, for example, might use voice of customer text analysis to look for complaints about their online services on Twitter.
It will give them an early warning when customers aren’t happy with the service's performance, so that they can act before the client calls to complain or publicly ask for the contract to be terminated.
Lead Generation through Social Media
A piece of social media information can be used to retain and get new clients. It is like the use of the VOC application.
For example, if a person tweets that they are interested in a particular product or service, text analytics can detect this and pass the information to a sales representative, who can then pursue the prospect and turn them into a customer.
Finding Out What Customers Value through Market Research
According to numerous statistics, consumers are interested in other people's thoughts and experiences. According to a study, at least 90% of humans are influenced by what they read.
Also, if the review is terrible, the sentiment is shared. In the last few years, several websites have been collecting reviews of local eateries, vacation spots, and, of course, commercial products.
If your company is thinking about going into a new market or looking into new product ideas, why not start by looking into online market research reviews
from real people?
Market research helps you know what features are important to customers when you start your marketing effort. It's critical to know which characteristics influence purchasing decisions and contribute to customer unhappiness.
Use Customer Complaints to Identify New Product Ideals
Understanding the consumer experience is critical, and internet reviews offer a dependable means to do it. Of course, when a consumer encounters problems, no one expects them to be happy, but it can be positive if the support is speedy and helpful.
Social media handles could be effectively used to understand the feedback and complaints of customers. Responding to them promptly makes the customers feel good. It also, gives an idea of the expectations of the customers and the new product ideals.
Analyzing the Customer Sentiments
Whether you're selling a handbag or consumer software on the App Store, text analytics may help you categorize reviews quickly. Unfortunately, a spreadsheet and hours of reading and categorizing reviews are generally required for the manual option. Aside from the discomfort of working long hours, we frequently find irregularities due to the physical nature of this labor. So why not create a data categorization
and scoring model that you can use to rerun the data daily, weekly, or monthly?
Companies now have many options to perform text analysis thanks to the rise and availability of unstructured text data. However, simply wanting to use text analytics and predictive analytics isn't enough. You need to first understand where you are as a company from an analytical point of view, and then you need to create a plan on how to embrace these new opportunities. Understanding where you are now can help you determine your next steps and protect you from taking on more than you can handle.
Frequently Asked Questions
How do companies use text analytics?
Text analytics is being used by businesses to analyze consumer comments, evaluate client interactions, assess claims, and uncover compliance concerns. Text analytics software based on natural language processing (NLP) can be used to quickly scan internal legal documents for words and phrases related to finance or fraud.
What can text analytics be used for?
Text analytics is used to gain deeper insights from unstructured text. For example, it can help you see a pattern or trend.
Can business intelligence be improved through text analytics?
Text analytics can help you understand trends, patterns, and actionable insights that you can apply to make data-driven decisions. It can be done by combining the findings of text analysis with business intelligence tools to put the numbers into easy-to-understand reports and images.