How NLP Can Change Your Business
Discover how Natural Language Processing can help your business, and how NLP is already helping businesses in various industries.
How many times have you used Google Translate to find the meaning of a word or phrase in another language? Odds are it's been more than once.
But what about your business? How often do companies use translator services, natural language processing (NLP), or other tools to analyze an international customer's online interaction? More often than you think.
Natural language processing (NLP) is one of the most important technologies businesses can use to understand and respond to their customers' needs, wants, and expectations across any global market, regardless of language boundaries.
Used by Google and Bing for web search, NLP powers Siri on our iPhones, Amazon's Kindle feature that automatically updates your e-books, and Twitter's real-time search engine.
NLP is also at the forefront of powering the next generation of software that will be able to conduct complex conversations with users, such as Microsoft's Cortana virtual digital assistant or IBM Watson computer.
With this technology, companies like Google can now translate foreign web pages for English speakers by monitoring how other non-English language websites interact with English ones.
For example, if someone searches on Bing in English for a foreign film title using certain keywords, NLP can detect which non-English websites use those same words and then translate the page into English so that searchers can find it easily.
The most significant NLP application for businesses comes from developing countries. Countries with rapidly growing populations are becoming the biggest opportunity for companies who plan to enter those markets.
Companies must find a way to communicate directly with customers across all cultures and languages. According to the US Census Bureau, just 10% of the world population speaks English as their native language, which means that 90% don't have access to information through that language alone.
Meanwhile, Google has been investing in NLP technologies since 2002, when founder Sergey Brin decided that Google needed a better way to organize its growing number of foreign pages. Today, Google's former head of geo services, Craig Nevill-Manning, leads the company's machine translation research and product development.
In addition to simply translating foreign web pages into English, companies use NLP for specific purposes such as "pre-emptive customer outreach" or live chat support while customers are still browsing a site. This allows service reps to answer questions before they're even asked. For example, HSBC Bank uses its investment in NLP technologies for this specific purpose.
IBM is another great example of a company investing heavily in NLP technology. IBM's Watson computer first came into the public spotlight when it won on Jeopardy against two former champions. Since then, IBM has been using the technology to analyze more data than humans ever could and derive meaning from that information. For instance, Watson is being tested by major retailers like Walmart, Kroger's Foods Co . , Sam's Club, Home Depot, Target Corp., Safeway Inc., and The Fresh Market.
How You Can Use NLP Today
Although you might not have access to an artificially intelligent computer like IBM Watson anytime soon, there are ways you can use NLP today and see immediate benefits.
1) Use Skype's self-service tools for instant customer support. If your company targets international customers, they might be more inclined to look for a local business offering live chat support rather than one that only uses email. For example, using Skype is one of the best ways to target Spanish speakers in Latin America because many of them prefer the messaging platform over Facebook or Google+ Hangouts.
2) Start communicating with customers on social media networks. The same way we search online now includes looking at specific social media posts about certain topics and companies. Take advantage of this information and monitor what customers say about your brand across different social media platforms like Twitter, Facebook, and Instagram so you can engage them with the right messages.
3) Implement a chatbot or virtual assistant to help customers find information. In addition to customer service, many companies are now using NLP technology in different ways. For example, you can use IBM Watson's Bluemix platform to create a "virtual agent" that combines natural language processing and speech recognition into one interface. You can then give it access to your company's knowledge base so customers can ask questions and receive answers from an online chat window rather than calling a call center.
There are some ethical issues you should consider before investing in NLP for your company.
For instance, companies will need to invest in strong security measures to detect "suspicious language" or words that suggest criminal intent. For example, if a customer were to use the term "explosives" instead of "batteries," it might raise concern for an online shopper who lives in an area where someone buying explosives could attract suspicion from the authorities.
For now, companies are struggling between having too much data to handle and not enough good information to make sense of it all. Using NLP technologies well helps businesses adapt to changing global markets and makes customers feel more valued because they have access to information they need quickly and easily.
How It Stacks Up Against Humans
Right now, the algorithms powering NLP don't understand contextual information as well as humans do. For example, it would be difficult for a computer to differentiate between "I'm looking forward to seeing you" and "I can't wait to see you." Although computers understand language in a certain way, they're still missing this particular human expression and emotional element.
However, we might not have to worry about computers becoming too clever for our own good because understanding context depends on what industry you're working in. Take weather forecasting as an example - meteorologists use natural language processing (NLP) technology because it helps them figure out which areas will receive heavy rain better than human forecasters.
While the future of NLP technology is bright, we still have a lot to learn about how it can help us better understand the world around us.
Use Cases in Different Industries
Admittedly, it's easy to see the benefits of NLP for customer service and support. Even small companies can launch virtual assistants that automate answers and provide customers with answers and suggestions before they ask a question. However, NLP is not just for B2C companies. Here are some examples of how businesses in different industries use natural language processing:
The US Department of Justice's National Institute of Justice (NIJ) has invested $8 million into research projects such as "NLP4Law," which focuses on developing algorithms that can automatically mine legal texts to understand the implications of cases to predict judicial decisions. This technology could potentially save thousands — if not millions — of lives by speeding up criminal investigations and placing violent offenders in jail.
One of the biggest challenges in healthcare is making information more accessible to medical professionals to give patients the right treatments at the right time. Researchers can build systems that understand natural language expressions and identify symptoms or illnesses mentioned in patient records using NLP. Once this data has been organized, it can be used for epidemic prevention, early diagnosis, drug discovery research, and more.
Airplanes are already taking flight with autopilot technology that can navigate routes based on GPS signals alone. As self-driving cars become increasingly prevalent, your car will also receive many features powered by NLP. A number of autonomous vehicle prototypes utilize "natural speech interfaces" where drivers talk to their cars just like they would with a friend or family member. Plus, safety features such as automatic braking and pedestrian recognition will help reduce the number of accidents on the road.
PR & Marketing
PR and marketing professionals use NLP to quickly sort through large amounts of information to identify the right journalists or bloggers for a particular story. This is especially important when dealing with companies that need to communicate with press members on high-priority issues. By using this technology, businesses can save time, resources, and money by putting their message in front of the right people at the right time.
Banking has become more automated than ever before. For example, Citigroup uses NLP to help identify credit card fraud by flagging communications that might be associated with illegal activity. According to the company's associate SVP of global digital solutions, Carl W. Liebert, they can "defeat cyber criminals who are constantly creating new ways of engaging in fraudulent activity" through their combination of advanced analytics and machine learning technology. Plus, banks can use real-time data tracking tools to offer customers personalized service without relying on support representatives or call centers.
Marketers have always used focus groups and surveys as a way to assess consumer demand for products. However, it can take time and significant resources to put these studies together — and even more to clean up and analyze the results. Now, marketers and researchers can use NLP and machine learning tools to quickly scan through millions of pieces of text-based data, making it easier than ever to make more informed decisions that benefit their businesses.
The Future of Natural Languages Processing: As Good As Humans?
Many businesses are starting to see the value in working with NLP-powered tools, but there are still some limitations. For example, because these platforms rely on data sets that have been manually defined by humans, they're limited in scope and lack the flexibility to identify new trends or patterns without explicit training.
As a result, many believe it's only a matter of time before NLP approaches human performance levels. According to research conducted by University College London professors Andrea Vedaldi and Karen Looney, if technology keeps developing at its current rate, NLP will match human capabilities within five years.
If you want your business to stay ahead of the curve - now is the perfect time to begin investing in advanced analytics solutions powered by natural language processing.
How to Prepare For Natural Language Processing
Many businesses make the mistake of waiting too long to work with NLP-powered tools because they believe these solutions are inaccessible or too expensive. However, there is a wide range of options available that can help companies at all levels.
For example, many organizations are integrating NLP into existing applications like email marketing systems and CRM hubs. This enables users to access information without opening up new software or learning an entirely new system. Plus, it's relatively easy for developers within any organization to get started since there are so many publicly available resources.
Once you've taken the first step, do your research before choosing a provider so you can find one that offers high-quality services at a reasonable cost. Remember, you don't have to go with a large enterprise-level firm to get the attention and support you need.
NLP has several applications for social good across different industries. People may wonder why natural language processing research matters if it is not directly related to helping them improve their day-to-day lives. But there's no denying its effects will have meaningful impacts on how we live, work and play now and in the future.
Furthermore, the social sector will benefit enormously from this technology as it continues to develop. For example, NLP can be used to help banks and financial institutions support children in need by identifying patterns of speech that might indicate abuse or neglect. It can also help medical professionals detect disease faster than ever by scanning large amounts of data for unusual phrases or words related to specific conditions.
Whether you're currently investing time and resources into NLP research or considering the possibilities for your organization, there is no doubt about it: natural language processing is changing the way we live, work and play. When done correctly, these systems can provide businesses with unparalleled insights about their customers, helping them make smarter decisions that benefit everyone involved.