Natural language processing (NLP) combines the studies of data science, computer science, and linguistics to understand language much like humans do. It’s useful to businesses because it breaks down human language making it easier for machines to analyze automatically.
With no-code NLP-driven platforms like MonkeyLearn popping up NLP tools are becoming more accessible than ever, helping businesses automatically process huge quantities of text data, streamline their operations, reduce costs, improve customer satisfaction, and more.
Let’s take a closer look at why your business needs natural language processing.
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.
When performing repetitive (and frankly boring) tasks, like reading and analyzing 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.
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 analyze 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.
NLP tools allow you to automatically analyze 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.
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.
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.
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.
Natural language processing can be a huge help to any business, to save time and money, streamline and automate processes, and make real-time, data-driven decisions. And with easy-to-use and easy-to-implement SaaS tools, you no longer need a data science background to put NLP to work for you.
MonkeyLearn’s suite of powerful NLP tools can ensure you always get the most out of your text data.
December 11th, 2020