Text Classification: What are the Must-Use Techniques of Machine Learning


With so much data at our fingertips, managing it all has become too much for humans to manage efficiently. Businesses are processing more text than ever before and while some of this data might need skilled professionals, much of this information is done with computers. That’s where machine learning comes in. 

Over the past few years, machine learning become an incredibly popular technology for companies to leverage. The automation of these processes saves time and processes data much faster as a result. 

Machine learning has contributed incredibly to the business market with Netflix as an example, saving over $1 billion using this technology for personalization and content recommendations.

Text classification and the use of machine learning have incredible benefits that will only improve business processes. In this guide, you’ll understand the basics of text classification, how it works and a number of worthwhile techniques to use when it comes to machine learning.

With data being a goldmine for any business in the digital age, technology like machine learning is revolutionizing business industries across the board.

Defining text classification

What does text classification mean? Text classification is a technique within machine learning that help to structure, organize and categorize any kind of text. The technique assigned predefined categories to open-ended text.

Text classification is a natural language processing application that is used across the web whether it be for documents, files, and more.

How does text classification work

Text classification is used in a variety of different ways. The most popular is sentiment analysis. Let’s look at the different examples of machine learning text classification offers for those that use it.

Sentiment Analysis

As mentioned, sentiment analysis is used as a classifier to understand a positive or negative text on any given subject.

This is used in a variety of business tasks which include social media monitoring and what’s being said about the brand to detecting customer pain points. This information is found through survey responses and feedback forms, identifying what a customer did or didn’t like about a product or service.

It is also used in market research for helping analyze and find gaps in the market for the brand’s benefit. 

Customer Feedback

Using machine learning and AI is useful when it comes to creating more actionable analytics for customer feedback. According to Marketing Charts, it found the market industry could be transformed substantially by AI, including the task of finding insight into customer feedback data.

From sorting through survey responses and product reviews, text classification helps detect trends and themes quickly. It’s a task that if done manually by a human, would end up being a very time-consuming process.

Customer Support

Support teams work hard to provide the best experience for your customers. As we move into an era of customer-centric experiences for growth in business, the use of text classification for customer support is effective.

Tagging common questions, tracking unresolved queries, and assigning urgency to support tickets can all be done through machine learning. What may have taken hours for support teams to be done manually is done in seconds via computer.

This helps support those teams who are able to then prioritize working on cases that need their help first and foremost.

Fraud & Online Abuse

Keeping your platforms and customer spaces free from profanity and fraudulent attempts is important. Text classification offers its support by being able to filter out signs of fraud and abuse on the web. 

From bullying on social networks to spread fraudulent content in the comments section of your blog. Machine learning tools use text classification to track and monitor any specific topics and language used that are deemed abusive and help remove them.


Language detection is another format of text classification that’s used in a variety of work tasks. These include:

  • Filtering incoming messages from languages that aren’t desired
  • Send support tickets to the right team members
  • Categorize and sort documents based on the language used
  • Detect the language of customer feedback

The ability to detect language helps expand the business beyond just its native language. It widens the horizons of potential a business has when interacting with users from all parts of the world.

Four must-use techniques for machine learning

Now you know how text classification works, how do you adapt this machine learning to your business? There are a number of effective techniques that implement the use of text classification. Here are just four of those must-use techniques for machine learning that are worth exploring this year. 

1. Assess ad performance to make more informed decisions

Ads are an important part of marketing the business and getting the right ad sets to ensure your budgets are used effectively.

The use of text classification and machine learning is beneficial when it comes to ad performance. A machine learning tool that uses the past performance data of ads to create campaigns where budgets will be better well spent.

Based on the previous data, text classification pinpoints where ads performed well so that new ads are provided with the right budgets. As a result, this helps improve conversion rates and maximize ROI for your marketing funds available.

Machine learning goes several steps further than the average human does when it comes to improving ad performance. It seeks out correlations between ad sets and performance in general. As a result, it is leveraged to make your own media team smarter when it comes to marketing skills and advertising talents.

2. Analyze documents to check for accuracy

Paperwork and the admin workload often trigger a universal groan of disapproval. A lot of delays are caused by paperwork, especially when there are multiple collaborators on the document.

A machine learning tool using text classification helps to check documents to ensure accuracy in what’s been filled out and what’s still missing. It is helpful for many of those who’ve been given the unfortunate task of managing this admin.

3. Categorize support tickets

Dealing with a multitude of support tickets every day is challenging for even the most organized of customer support teams. Sometimes the volume of tickets is simply too difficult to manage and monitor. That’s where machine learning technology has the upper advantage.

Implementing text classification to request predefined categories helps determine which tickets need to be answered first and foremost.

It keeps your staff working efficiently instead of having to trawl through the oldest of tickets before working backward.

4. Prioritize business emails

Business emails come into the inbox daily in their hundreds and not all of them are relevant. In order to help your internal operations, there are plenty of machine learning tools that help to organize business emails a little more efficiently. 

By labeling communications correctly, these emails can be categorized to express their intention. The user who owns the email inbox is then able to successfully organize their inbox, forwarding to the relevant department as well as marking its importance, hitting the snooze button, or sending it to spam.

The importance of text classification

Text classification offers plenty of benefits as do many of the techniques utilized within machine learning technology. With this being said, here are a few advantages worth noting should you consider making the most of AI and machine learning for your business this year.


Everyone has the same 24 hours in a day and for a business, it’s often not enough. To improve company efficiency nowadays, extra hands are needed. Digital hands to be exact.

Humans only work so fast and even by hiring more staff, the output potential isn’t the same as utilizing the power of computers. The use of text classification and machine-learning technology is cheaper than hiring more staff to do it all manually.

Offers real-time analysis

When it comes to machine learning, companies get access to real-time analytics that help in reactive situations and scenarios where the outcome isn’t guaranteed.

Machine learning with text classification helps to gather user insights in real-time which helps take the next steps accurately.

Accuracy in results

It’s important that few mistakes are made as a business and while humans are trained to a certain extent, human error occurs.

Machine learning tools don’t make these mistakes, in fact, they generate outcomes and answers that humans would never have come to in some cases.

A refined strategy for business

Text classification is a great way of helping improve your company strategy and to improve on the engagement of your campaigns. With everything that machine learning technology provides, it certainly helps provide more accuracy in everything you do within business operations.

Make full use of text classification as a machine-learning technique for business

As a highly popular machine-learning technique, text classification is a must-use for any business in this digital age. Make sure to make use of text classification for your business in 2023.

Natalie Redman for ROI4CIO

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