Unstructured data is a nightmare for almost every business. They form the backbone of data silos — the roadblocks to business process improvement and informed decision making. Unstructured data adds almost up to 80% of an enterprise’s data: that’s quite a lot of untapped value.
While data preparation techniques such as tokenization, stemming, and lemmatization can effectively help structure data, they fall short when facing the elephant in the room: big, real-time data. In today’s high-speed business environment, with 2.5 quintillion bytes of data produced by humans every day, businesses across the globe are banking on AI-driven solutions to process and analyse unstructured data in real time.
Natural Language Processing (NLP) is an AI-powered capability that enterprises can readily harness to extract valuable insights from untapped, unstructured data sources.
NLP is redefining enterprise solutions, helping streamline and automate business processes, increase productivity, and simplify mission-critical business operations. But has it yet been deployed at scale?
Although NLP is in its nascent stages, it is already making an incredible impact across industries. For instance, the finance industry is a complex landscape largely driven by data, mostly text-based. Finance professionals spend a considerable amount of time reading invoices, transaction reports, documents, websites, etc., to gain insights that can drive their decisions.
NLP techniques such as part of speech tagging and named entity recognition can turn the raw textual data of the financial documents into meaningful insights. From retail banking to investing and funding, NLP is becoming increasingly popular among traders, analysts, portfolio managers, and other stakeholders.
NLP helps process unstructured data at scale
The pandemic has shifted traditional business engagements to digital mediums in the new normal. More and more conversations and transactions are happening on the cloud. In the last two years alone, we’ve generated almost 90% of the world’s data — mostly unstructured.
Businesses across the globe are now exploring and implementing NLP technology to understand the data they create and procure. The mission to streamline and automate business processes is now dependent on how well one can dive into the surrounding ocean of data and fish out valuable insights.
According to Market Watch, the global Natural Language Processing (NLP) market size will reach USD 3 billion in 2028, growing at a CAGR of 20.9%.
Thanks to its machine translation and text and voice processing capabilities, NLP is facilitating analysis of unstructured data at scale helping extract large amounts of useful data from documents, emails, social media, internal systems, online reviews, and much more. And more importantly, it processes voluminous amounts of data faster than manual analysis, which typically takes weeks or months.
It’s true NLP is transforming the way we handle unstructured data, but did you know it is also turning the tables in how businesses engage with customers and employees?
NLP drives better conversations across industries
The success of any business lies in how well they communicate with their customers and stakeholders. Conversational AI technology has been a major disruptor in industry-wide communications, across dimensions. It combines natural language processing with software solutions such as chatbots and voice assistants to help users navigate seamlessly on a platform, find relevant products, and even clarify doubts in real time.
Intelligent customer engagement: Chatbots, powered by NLP, are now almost on all major consumer-facing platforms driving conversations round-the-clock. Chatbots can help businesses achieve up to 30% cost-saving from conversational AI solutions. These automated systems analyse and respond to customer queries in real time, freeing up employees’ time and enabling them to focus on more creative and cognitive tasks.
Better workplace collaboration: While NLP-based chatbots are becoming prevalent these days, users are becoming more accustomed to them and expect the same experience in the workplace. Enterprises are beginning to use natural language understanding (NLU) applications to improve information discovery and collaboration at the workplace.
The benefits of conversational AI can be felt for the longer term and will continue to boost the business value for organizations as NLP-driven solutions evolve with time and disrupt conventional business processes.
NLP helps analyze sentiments and improve business processes
Customers form different opinions about products and services as they engage with different brands. These opinions, which have an incredible impact on the market, often show up in online reviews and social media. NLP software can perform semantic and sentiment analysis on text from various sources to extract subjective qualities — attitudes, emotions, confusion, suspicion — to help you understand the language and mood of your customers.
Businesses, through NLP, will have a better understanding of market segmentation and can target customers directly while lessening customer churn. Enterprises can also expand their use of business intelligence (BI) solutions at the organizational level, with the help of NLP. It offers users an intuitive tool to find vital data, analyze trends, and make fact-based, data-driven decisions to improve business processes.
How have you adopted NLP to streamline and automate business processes?
In brief, natural language processing is becoming an integral part of modern businesses, helping stakeholders better understand customers and improve customer retention and satisfaction. It will continue to revolutionize businesses by streamlining and automating processes, enabling real-time, data-driven decision making and improving cost-efficiency.
How would you like to perform accurate analysis of data, gain actionable insights, streamline and automate business processes, and reduce costs for your business?