7 power uses of Natural Language Processing

7 power uses of Natural Language Processing is profiled by BTW Media because published evidence links it to internet infrastructure, governance, operational dependencies, or market visibility.

• Natural Language Processing (NLP) stands as a testament to the ever-evolving synergy between human language and machine intelligence.
• In a world where information inundates us from all directions, NLP serves as a beacon of comprehension, enabling machines to decipher, interpret, and generate human language.
• NLP bridges the gap between human language and computer algorithms, empowering machines to comprehend and interact with textual data.

Natural Language Processing (NLP) integrates principles from data science, computer science, and linguistics to comprehend language in a manner akin to human understanding. Its application holds significant value for businesses by dissecting human language, thereby facilitating automated analysis by machines.

The emergence of no-code NLP platforms, exemplified by tools like MonkeyLearn, has democratised access to NLP capabilities. These platforms enable businesses to effortlessly process vast volumes of text data, leading to operational efficiency, cost reduction, enhanced customer satisfaction, and myriad other benefits.

Let’s delve deeper into the compelling reasons why your business should embrace natural language processing.

Also read: What are the mechanics behind conversational AI?

1. Perform large-scale analysis

NLP technology allows for text analysis at scale on all manner of documents, internal systems, emails, social media data, online reviews, and more. Process huge amounts of data in just seconds or minutes, that would take days or weeks of manual analysis.

Furthermore, NLP tools can scale up or down immediately to meet your needs, so you have as much or as little computational power as you need.

2. Get a more objective and accurate analysis

When performing repetitive (and frankly boring) tasks, like reading and analysing open-ended survey responses and other text data, humans are prone to mistakes or may have inherent biases that can skew the results.

NLP-powered tools can be trained to the language and criteria of your business, often in just a few steps. So, once you have them up and running, they perform much more accurately than humans ever could. And you can tweak and continue to train your models as the marketplace or language of your business evolves.

Also read: The difference between Conversational AI and GenAI

3. Streamline processes and reduce costs

NLP tools work at whatever scale you need, 24/7, in real time.

You’d need at least a couple of employees working full-time to accomplish manual data analysis but with NLP SaaS tools, you can keep staff to a minimum. When you connect NLP tools to your data, you’ll be able to analyse your customer feedback on the go, so you’ll know right away when customers are having problems with your product or service.

Automate ticket tagging and routing with NLP tools like MonkeyLearn to streamline processes and free your agents from repetitive tasks. And remain on top of emerging trends just as they arise.

4. Improve customer satisfaction

NLP tools allow you to automatically analyse and sort customer service tickets by topic, intent, urgency, sentiment, etc., and route them directly to the proper department or employee, so you never leave a customer in the cold.

MonkeyLearn integrations with CRM systems, like Zendesk, Freshdesk, Service Cloud, and HelpScout are a great help to automatically manage, route, even respond to customer support tickets. And performing NLP analysis on customer satisfaction surveys can help you quickly discover how happy customers are at every stage of their journey.

5. Better understand your market

Natural language processing is having a huge impact on marketing. When you put NLP to work to understand the language of your customer base, you’ll have a better understanding of market segmentation, be better equipped to target your customers directly, and decrease customer churn.

6. Empower your employees

With all the human hours you’ll save by automating processes and using data analysis to its full potential, your employees will be able to focus on what matters: their actual jobs. Furthermore, when you remove tedious, repetitive tasks, your employees will have less boredom, fatigue, and increased focus.

7. Get real, actionable insights

The unstructured data of open-ended survey responses and online reviews and comments requires an extra level of analysis – you have to break down the text so it can be understood by machines. But AI-guided NLP tools can make it easy.

No more guesswork or simple, cursory analyses. Natural language processing allows you to really dig into unstructured text for data-driven, real-world, immediately actionable insights.