Have you thought about the business data sitting around unused? 

You may have different ways to work with structured data, but often the unstructured data goes unused because of the complexity involved in the process. Relying on responses and open-end comments don’t factor in your business goals. Besides, chances are you overlook opportunities, miss out on some valuable customer feedback, and fall behind in optimizing the customer experience. 

Don’t worry, text mining fixes this problem. Text mining helps businesses extract fruitful information that can be used by sieving through data collected from social media, customer support tickets, Vlogs, Voice Of Customer (VoE), Voice Of Customer (VoC), and other sources. 

When done at scale and integrated organization-wide, text mining leads to synergetic marketing strategies that eclipse client nurturing and brand reputation management. Besides, it’s also instrumental in identifying policy violations – return and warranty claims or cyberbullying on social forums. 

But, before we delve deep it’s important to understand the subtle difference between text analytics and text analysis. These terms are often thrown around so often that they are used interchangeably. 

This blog will shed light on this topic as well. But, first, let’s look at the real-world example of text mining. 

Real-World Example of Text Mining

There’s no doubt, businesses can gain a lot by using text mining solutions. Also, they can deliver valuable information and simultaneously act as a catalyst for business intelligence in every conceivable industry. 

A handful of applications of a text mining API in businesses are listed below. Let’s have a look!  

• Electronic Health Records

In the healthcare industry, text analytics help tremendously in patient management and engagement – right from analyzing patient history to their dosages and responses. 

Text mining also comes to the rescue in Psychiatry where patient notes have been used to predict precedents of some specific types of behaviors that need some particular treatments. A recent study published by the US National Library of Medicine shed light on how analyzing texts of EMR reports helped in the prediction of seclusion of patients along with the importance of text analysis in evidence-based clinical decision-making. 

2. Client Nurturing 

To analyze customer service tickets, call logs, client forums, surveys, social media platforms, emails, tweets, and news feeds, text mining is used. It provides businesses with better insights into what their customers are looking for and which areas need to be reworked. 

To analyze the collected through videos, comments, and posts, it uses Video Content Analysis and Audio Analysis. 

3. Reputation Management 

Companies and brands need to maintain a public image, especially in today’s culture. 

Text mining allows you to understand the captured data from social media listening and Voice of Customer programs by analyzing tweets, comments, news articles, and other feedback that mention anything related to it. Companies can uphold the status of their reputation in real-time by taking measures to thwart the crisis.

4. Cyberbullying and Threat Detections 

Text mining helps in ensuring that community standards are followed in the comments and tweets on your social channels. Besides, keywords can be categorized as red flags and the text analysis engine will choose them, including synonyms or misspelled words that sometimes dodge the engine. 

Video and audio files can also be analyzed simultaneously because the engine transcribes the files from speech to text and processes them for threat and policy violation detection. 

5. Search Engine Optimization

Nowadays, search engines put text mining to use to identify spam and filler content in content marketing websites. The engine can identify several contexts, intent, and variations and mark an email as spam, or even it can penalize a company website that has been trying to increase its search engine ranking by keyword stuffing and other techniques. 

A company’s own search engine can be optimized and powered with a text analytics API. it provides you an organization-wide capability to semantically search all the documents. 

6. Social Media Listening 

Listening to your customer base through comments on social media brings a lot of benefits to the organization. This outlines the fact that with social media listening, there is much more you can learn about your customer which might survey won’t be able to offer. 

Not to forget the power of social media, companies like Mcdonald’s, Wendys, Netflix, and even Microsoft have had hilarious and witty social media exchanges with their customers, while they use this data to improve their existing user interface and customer experience. 

7. Finding Patterns in Data

A crucial aspect in medical treatments and clinical trials, real estate planning and new product development, finding patterns in data historically and presently. 

Imbibing the feature of text analytics enables companies to study the patterns in data for diverse domains like events affecting oil prices, consumer behavior, weather forecasting and many more. Patterns and trends are crucial to formulating new policies for security and surveillance as well as for traffic regulations to address congestion problems on high-frequency routes. 

8. Return and Warranty

Undoubtedly, text analysis is important to understand a company’s data. 

As data is received from hundreds of dealer service professionals, spread across locations with warranty claims and returns. A good text mining tool can read and categorize data even if it has misspellings, shorthand, acronyms, or any other inconsistency and analyzes them for reference and corrective measures. 

9. Surveys and Reviews 

Whether it’s the reviews on social media or emails, or market research surveys, a smart text analytics API can easily identify and categorize the topics and themes, all thanks to its machine-learning training. 

 Open-ended questions having verbose and cryptic answers in surveys can lead to inaccurate analysis if done manually because of human error and bias. Here, a text analytics solution uses techniques like NLP and aspect-based sentiment analysis to ensure that different aspects and themes present in a single review are taken into account. 

Finally

Introducing text mining apps and software have the potential to make it easy for you to steer your business in the right direction. No matter where your customer chooses to share their thoughts, brands can understand the meaning behind their words. 

So, make the most of your company’s data with the right text analytics API and achieve the competitive edge that will take you through 2022 and beyond.