Natural Language Processing offers great business benefits
Data in all its forms — especially that submitted by customers — is a valuable source of information. But, at the same time, many businesses lack the tools to analyze it correctly. Natural language processing offers a fast and efficient way to comb through social media posts, comment forms and chatbot streams to find what you customers really want.
Natural language processing (NLP) has been a technology that science and business have been hankering after for decades. Over years it has become more important as data became king, but it is a must-have today, as part of a collection of tools known as machine learning, as businesses start to drown in big data.
The arrival of NLP has been hastened by the need to understand what people type and say to the likes of chatbots, Siri, Google Home, Alexa and other talkative assistants. Companies relying on data in the cloud, customer support staff and other roles need to know what is happening as thousands or millions of conversations take place around them.
All that data is no good if the device or service doesn’t understand what a customer or prospect is asking for. Similarly, the business needs to spot trends in that data, and it can be hard to analyze unstructured data that much of this information is stored as.
Strong use cases for machine learning are based around checking your data is compliant for any legal regulations (such as GDPR in Europe), who has access to files while NLP gives greater insight into what is stored in the files.
The rise of NLP and AI
NLP gives a company the opportunity to scan messages, such as tweets, feedback forms, documents or files. Working either historically in batches or live, and look for key phrases or words that can help the company identify valuable trends or information, from the simple “our customers are asking for this product at this time of day” or feedback suggests our chatbot is not giving enough specific information.”
Large companies can hire data scientists to build apps that help crunch the data, but there are many cloud-based automation, machine learning and NLP tools that any company can access to help them leverage data and create actionable insights. And, if a company like Dunkin’ Donuts can use machine learning, we’re pretty sure yours can too.
Chatbots are a key, and rapidly growing, area where NLP can help the company build and operate a better bot. If a customer types something the bot isn’t expecting, NLP can scan the phrase for keywords and direct the conversation to something relevant. If that keeps happening, data builds up over time and the company can refine the chatbot to make sure customers have a better progress path.
Businesses can also benefit by automating processes using software such as Smart Processes Automation (SPA) from WorkFusion, with features including workflow analysis; helping a business streamline processes. Using cognitive AI-based processing SPA can automate judgment decision making around unstructured data, while a team of SMEs can provide quality control within a fast-moving business.
Beyond these use cases, AI, NLP and automation can help with translation tasks as businesses increasingly become global players, no matter how small they are. Recruitment and HR are another boom area for the technologies with resumes being sifted for key information or chatbots providing workers with holiday, sickness and other information on request to save the department having to find out that information.
The future of NLP for business
It is true that a business can probably work okay without using NLP at the current time. However, as data becomes even more critical to companies and the volume grows, it will soon be impossible for humans to keep track, and AI, NLP and other technologies will have to take over the work.
By getting on-board with NLP in your applications and processes now, you are setting your company up to be more efficient and prepared for this heavy data future.
