When we talk about applications for natural language processing (NLP), the use cases that generally come up focus on Voice of the Customer (VoC) and Customer Experience Management (CEM). And fair enough: Plenty of the activity around and investment in NLP has been in this space. The NLP-powered customer experience platform Medallia was just purchased by a private equity firm for $6.4 billion. The AI-backed customer feedback platform Clarabridge was recently bought by Qualtrics for $1.1 billion. There’s no doubt when it comes to VoC and CEM, NLP is a winning solution.
But text analytics delivers benefits outside the VoC and CEM spaces, and savvy brands have been quietly leveraging it to their advantage. Let’s explore a few of the lesser-known NLP applications that are transforming organizational processes and bottom lines.
Trend Hunting and Demand Prediction in Hospitality
Being slow to catch on to a trend can mean missed profits – and a missed opportunity to be first to market. In the food and beverage industry, certain ingredients can become a hot topic overnight, with demand surpassing supply. Bars, restaurants, hotels, and stores that are slow to hit on the trend may struggle to keep an ingredient in stock, have problems anticipating future order sizes, or miss an opportunity to incorporate an on-trend ingredient in their menu. This can impact brand perceptions, customer experiences, budgeting, and staff satisfaction.
Client Application: Our company worked with a business that advises hospitality brands on market trends and strategies to create a taxonomy of the different ingredients used by a large swathe of brands in this vertical. Then we used NLP to identify “hot” ingredients, where they were being used, and in what quantities. Restaurants and hospitality brands can now pay attention to trending ingredient information and order more of it.
Compendia Review in Medical Affairs
Medical compendia are a list of approved and preferred drugs for different illnesses and are used by insurance companies and doctors when recommending treatments. However, compendia are incredibly complex and ever-changing, with specific drugs moving up and down the list based on new research, new side effects, pricing, and new competitors. Pharmaceutical companies spend enormous amounts of money developing drugs, and becoming less or more preferred for a specific treatment type can have a bottom-line impact of hundreds of millions. But compendia review has historically been done manually, which risks changes being spotted too slowly or not at all.
Client Application: We worked with a pharmaceutical company to build a simple but powerful tool that alerts users to changes in compendia and shows the specific language that has changed – something that delivers enormous business value.
Email Routing in Financial Services
In the financial services industry, huge trading volumes can happen in a split second, and keeping your eye on the ball is vital. But if a feed or platform used to inform decision-making goes down or is scheduled for maintenance, overflowing inboxes can be burdened with additional pings, warnings, and alerts. NLP can parse, categorize, and route these emails to the correct recipients – keeping inboxes clear of clutter so that employees can focus on high-value tasks. Given that the average worker spends 28% of the day reading and answering emails, this sort of solution can significantly impact worker productivity and availability – especially when combined with NLP workflows built for sales and trading.
Robotic Process Automation (RPA) in Professional Services
Robotic process automation uses NLP to automate repetitive business tasks, typically those involving data processing or routing, to free workers to focus on more valuable, rewarding tasks. Examples of tasks that are ripe for automation include moving data from a form into a database, categorizing support tickets, parsing PDFs or scanned images. One common application uses RPA to scan invoices and trigger a payment from accounts payable – leading to faster billing cycles and revenue collection. With employees spending an average of 3 hours a day on repetitive tasks, NLP-powered RPA reduces organizational and billing inefficiencies, while being highly accurate.
Building Supply Chain Resiliency in Manufacturing
Most manufacturing companies use internal data to monitor the supply and demand of materials, putting their supply chain at risk in the event of an unforeseen external event, something we’ve seen the impact of during COVID-19. Shutdowns, labor shortages, transportation delays, and swings in supply and demand can all wreak havoc on supply chains, resulting in shortages and lost profits. Take the printing industry, which has seen unprecedented local demand along with a considerable shift in publication schedules and is struggling to keep up with orders, creating a “paper jam” that has industry professionals warning that consumers begin their Christmas book shopping as early as August. By incorporating NLP into their supply chain processes, manufacturers can improve responsiveness, adaptability, and resilience. Shipment document analysis, supplier compliance monitoring, demand analysis, and real-time analysis of external events such as natural disasters, power outages, shutdowns, or political crises are all areas in which NLP can deliver results – and help keep supply chains moving.
… and More to Come
VoC and customer experience are absolutely the key drivers in the NLP space at the moment. But as organizations become aware of the possibilities of AI and automation as a way to solve process inefficiencies and strategic “unknowns,” NLP is becoming an invaluable option for quickly and efficiently identifying trends and critical events, automating busywork, simplifying processes, and helping humans focus on the work that matters.