Monitor social media to learn how users feel about an industry, product, brand, and more. NLP can look for trigger words, such as “great,” and give a company insight into how its audience responds to it. Of course, this is where sarcasm can make NLP difficult — “Oh, well that’s just great,” for example — but social media monitoring and overall sentiment analysis of emails, forums, chats, reviews, and other data can help a company act on what customers need.
Chat and Messaging
When users interact with NLP technology through messaging systems, they can often perform tasks, have customer service issues fixed without needing a representative, or find information they need. Chat bots, automated text messages, Facebook Messenger, and other tools are available for companies to keep in touch with and help customers on the go.
Companies can enlist natural language processing to do their market research for them. NLP tech can scour “text, infographics and images in news articles, reports, SEC filings and company websites” and more to collect data, then process it to find important news and insights into competitors, industries, and markets. This information helps companies make better data-based decisions.
With market research, sentiment analysis, and customer intent analysis, companies can learn new audiences to target with their advertising. Vik Bogdanov writes, “NLP software helps broaden the range of channels for ad placement, helping companies spend their ad budgets more effectively and target potential clients.”
The hoops a candidate has to jump through in order to submit an application to a company can be frustrating. When it’s too complicated, even the brightest candidates will give up. A simplified application process can help companies recruit better talent. Human resources departments can rely on tools that use NLP to help them sort through resumes and applications more effectively. Instead of looking for a specific term, for example, NLP can judge resumes based on similar words and phrases.
Natural language processing empowers companies.
Some instances of NLP have been around for years. For most users, seeing a squiggly red line under a word is just a part of life. As data continues to proliferate and NLP is used more often, it will improve and affect more consumers in a positive way. Someday, that may mean that Siri and Alexa will understand Scottish accents. Or, in a broader sense, it will better help customers help themselves with automated services that free agents to help those customers who need the human touch.
No matter how it improves, NLP is a tool that businesses must use to stay competitive. It helps employees and customers alike, and its advances mean it will likely someday be just as important as the now ubiquitous email.
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