Pressing, searching, and hunting for information is a thing of the past. Until recently, employees across industries had to scroll search engines, wait on co-worker responses, and scan through company memos and files just to find the answer to a simple question using NLQA.
Specific machine learning and artificial intelligence techniques allow workers to proactively understand their information with the help of natural language question answering (NLQA). NLQA understands spoken or written verbiage to provide on-the-spot question answering. Subsets of NLQA, like natural language processing (NLP) and natural language understanding (NLU), have the ability to extract tone and intent behind all sorts of text. Using such techniques, NLQA provides relevant solutions and answers in context directly to the employees’ workflow.
So, what business use cases are organizations enhancing with NLQA, and what makes the technology so beneficial that all companies should get involved?
NLQA Business Cases
Departments involved in customer support are significant beneficiaries of NLQA across industries. Waiting on hold or delayed support tickets are becoming obsolete by having NLQA in an organization’s toolkit. Many answers to specific questions can be automated in the form of chatbots or support for customer service representatives.
The chatbot’s goal is to understand what the customer needs and point them in the right direction to fulfilling that need. However, chatbots must be trained based on data already within a company and freshly compiled data – documents, files, customer and company data, previous chatlogs, whitepapers, and more. Understanding the context of this data allows chatbots to generate answers based on the customer’s concern and support future clients with similar problems. The process is called case deflection because it solves the case before any human involvement.
If the chatbot is not utilized or happens to be unhelpful, a human customer service representative will step in. However, they may not know the answer off the top of their head. Here, NLQA can act as a shoulder to lean on. Staff can copy and paste a question so the system can provide a relevant answer using the same data a chatbot would use. In many cases, the system will comprehend the question and proactively provide an answer to be passed along to the client automatically.
This process applies to many different departments, as information is the workforce’s greatest asset. Maintenance teams can receive exact instructions on how to fix a piece of equipment with a simple search, or legal teams can gather details about a contract question or an upcoming court case.
The Countless Benefits of NLQA
Efficiency and innovation drive successful business operations across the globe. Being slowed down is bad for employee morale and timelines on tasks or projects. No one wants to feel helpless! NLQA assists in preventing slowdowns and beyond, completely eliminating the need to wait or exhaustively hunt for knowledge.
Existing information should be accessible in all parts of the business. If it exists, why not? New employees can also count on NLQA to help them get up to speed on unique company processes and standards – decreasing the cost of onboarding and training time.
Should You Be Looking into NLQA for Your Business?
Productive meetings to key in on which departments and functional areas would benefit the most to quick information access and question answering is an excellent starting point. Focusing on a single use case can help determine the long-term benefits of NLQA and Insight Engines as a whole. Insight Engines help companies understand their data and seamlessly integrate it into existing workflows. A test run with the technology can help provide insight into what other areas NLQA can support.