One of the most popular purchases today is the Amazon Echo, a smart speaker that listens to requests from people and answers them as desired. A quick survey of its reviews shows that users have found it useful for tasks as wide ranging as playing random songs, ordering shavers from Amazon and finding out when the next season of The Handmaid’s Tale will premiere on Hulu.
Another daily-life tool that millions of people around the world can’t live without is Google Translate. It’s the free translation service from Google that allows users to submit voice commands. There is no doubt that both Google Translate and the Amazon Echo have proven useful and popular.Â
But the true credit goes to natural language processing, the artificial intelligence software that makes their services possible in the first place.
What is natural language processing?
In the simplest of explanations, natural language processing is a technical process that enables machines to communicate with humans by understanding their speech. It involves the receipt of raw data (voice commands or text commands) that is then processed through various processes (such as parsing, tags, word arrangement, etc.). The machine then offers a response as required.Â
Natural language processing has been in development since the 1950s. Its processes have become advanced enough to get useful today. Google Translate and the Echo are just the tip; other NLP examples include voice assistants such as Microsoft’s Cortana and Apple’s Siri, live assistants such as chatbots and more.Â
There are many natural language processing examples which are being incorporated by major big data industries as part of their AI-forward goals. Everyday businesses have taken advantage of it too, especially in their customer service operations. Still, many business owners haven’t.Â
Below, we explore why a business should use natural language processing in its operations.
It enables flexibility in decision making
Natural language processors can analyze reports, documents and (current and past) news reports on behalf of the business to determine hard-to-predict parameters such as customer interest, market changes and even suitability for a job.Â
The latter is achieved by finding if an applicant used specific terms in their resume. With such real-time analytics, business owners become better equipped to make decisions or change them whenever necessary and ahead of competitors.Â
It is a very effective way of understanding customer’s sentiments about the business
Any business with a handle on its marketing strategy will want to know what its customers are thinking about it. Unfortunately, most businesses can only access basic data such as location, age and salary. Natural language processing makes understanding customer sentiments a lot easier. In fact, there is no better tool for understanding customers better.Â
So, how NLP technology works? It works by capturing text from customer service chats and voice recordings and analyzing each word and phrase used. Considerations for how it was spoken are also affected. This process helps identify user sentiment toward the business, whether positive or not. Businesses can then build their marketing strategies around that.Â
It helps with market expansion
NLP is a big help for businesses trying to expand their territories. The process almost always involves dealing with customers that speak different languages or English with different accents and nuances.Â
With NLP, the language barrier is demolished. Businesses can employ NLP-powered translators and customer care chatbots to understand their customer requests better and respond better.
It helps businesses provide better, faster customer service
The average customer wants to be listened to and have their problem solved in as little time as possible. That’s ideal for customer service. Many businesses employ natural language processing for this exact task because it has proven to be very useful.Â
Chat-bots, the popular robot customer service agents that –regardless of the time of day – answer questions on service websites, Facebook Messenger, Slack groups and Skype channels, are the best example of NLP in customer service.Â
Translation is another example; businesses employ translation during customer care calls for non-English speaking customers. Many major companies record customer query sessions for purposes of understanding customers better using NLP.
It simplifies communication throughout the business/organization
Many businesses have already taken advantage of natural language processing in achieving efficiency in their operations. This effect is best seen by Human Resource departments, many of whom now employ bots to answer employee queries on issues such as insurance and paid time off.Â
Employees can make these requests at any hour of the day, unlike with actual HR officers. The latter also applies bots to job applicant resumes to weed out candidates that don’t fit a required mold.Â
It makes tasks faster
The average business owner or employee spends hours every day researching by hand, whether it’s the numbers regarding recent sales or the day’s industry news. Natural language processing makes business tasks a lot faster to complete.Â
A simple voice request can provide the day’s top news, latest stock figures, information about an employee, or quarterly sales figures for unique product Z in under a minute. Any business looking to optimize its tasks for more efficiency should employ NLP.
To take advantage of a growing movementÂ
There is no denying that artificial intelligence is the next big thing. Facets of AI, such as natural language processing, are already boring their roots in almost every aspect of daily business operation.Â
If no other reason is enticing enough, businesses should incorporate natural language processing for the sole purpose of not being left behind when AI takes off. Still, natural language processing has already proven its worth for businesses as regards customer service and competition analysis, so it makes practical sense to make use of it.
Conclusion
Natural language processing is already proving to be the next big thing for businesses everywhere, along with machine learning, big data and other major aspects of artificial intelligence. The businesses that have already incorporated this technology have reported successful results, especially with customer service. For business owners still unsure of how useful natural language processing can be to their business, the ways above are just some of the few.
______________________________________________________
Interesting related article: “What is Artificial Intelligence?“