Why Natural Language Processing is Essential for Your Business Chatbot

While chatbots help users accomplish tasks quickly every day, most businesses still struggle to reach the ideal. A chatbot that provides an experience indistinguishable from interacting with a human being. Despite this reality, the technology that enables accurate, humanlike response isn’t science fiction. It exists right now. What’s the secret to boosting a chatbot’s accuracy and intelligence? NLP (Natural Language Processing), a deep learning technology that empowers bots to analyze user input and generate a response, much like a human. This technology is deeply important for any customer-facing bot. First, let’s break down what it is and what it has to offer.

What is Natural Language Processing?

Before NLP, chatbots would commonly use an on-rails structure or rudimentary machine learning and rule matching to connect a query to a pre-written response. NLP, meanwhile, can take any user query and identify entities and sentiment, generating its own responses in a truly intelligent way.

There are more than a few major benefits to powering your bot with NLP. First, the technology understands semantics and structure of text, allowing you to make sense of vase amounts of unstructured data. Second, MLP is capable of understanding morphemes across different languages for better accessibility. With the ability to learn slang and understand abbreviations just like a human, NLP makes bots more lifelike and easier to use with fewer errors. Finally, because NLP understands user intent, it shifts search away from a focus on keywords and towards meaning.

NLP is important to businesses because it provides an immeasurably better user experience across applications: chatbots, voice-enabled applications and devices, social media listening and more. NLP helps in any situation where you need to understand what a customer is saying with better clarity and accuracy.

How NLP Can Help Your Business

Customer Service

One of the sectors that can best benefit from NLP is customer service. Customer service chatbots powered by NLP can answer both open and closed questions. The difference between “Has my package been delivered yet?” and “When I can expect my package?”.  This makes the bot more accurate and intuitive, because the user can express their problem in their own words. With sentiment analysis, NLP allows customer service bots to prioritize extremely dissatisfied or angry responses, or automatically pass those users along to a human agent.

Both these benefits save a business significant time and money. More accurate bots that are better equipped to handle simple tasks ease agents’ workload, allowing them to focus solely on more complex tasks. And when a human agent is necessary to solve a problem, better routing afforded by NLP ensures the customer need only state their problem once. Overall, these benefits translate to a better customer service experience, which in turn leads to better sales and greater customer loyalty. Because customer service is the new competitive battleground, NLP gives businesses a much-needed competitive edge.

Market Research and Social Listening

Natural language processing can greatly enhance your business social listening strategy. NLP allows for summarization of vast amounts of unstructured content. This means you can quickly identify the main idea and meaning behind user queries and comments. By scanning for trends using chatbot analytics and NLP, you discover what’s important to your customers and discover operational risks. You also tap into how users feel about your brand. NLP lets you easily identify what customers are happy or unhappy with. So, you can quickly make things right by better anticipating and acting on their expectations.

Entertainment

Many entertainment franchises have turned to chatbots to promote their products, films and games. Whether they’re chatting with Kim Kardashian to learn about her game or helping the Power Rangers film’s Alpha 5, users hope to engage in the world of the franchise by being walked through various scenarios. Realism, then, is key. A bot that fails to understand users breaks immersion and tarnishes the brand experience. NLP eases bot confusion and provides a more entertaining, realistic experience, offering a better return on investment in your promotional entertainment bot.

Notable Platforms to Power Your Bot with Natural Language Processing

Microsoft Language Understanding Intelligence Service (LUIS)

LUIS is a versatile NLP solution that’s easy for less experienced users to pick up. This is because it offers pre-built applications that adapt to user queries. After users have spent some time talking to your chatbot, LUIS will identify queries that it wants you to label for better accuracy. In addition to training existing language models, you can even develop your own. A part of Microsoft’s Cognitive Services, LUIS offers deep integration with the Microsoft Bot Framework, which connects to bots on a variety of platforms.

Wit.ai

A popular Natural Language Processing solution, Wit.ai powers chatbots, mobile apps, internet of things devices and wearables. It translates words into actions by identifying entities and overall intent behind user queries. This is another service that’s easier for novices or small teams. The Wit community offers a ton of existing commands, so you can get started quickly. Of course, you can generate your own custom commands, too.

Google Natural Language API

If you’ve ever interacted with Google Assistant, you’re aware of what Google Natural Language API is capable of. It powers the prominent mobile assistant by parsing intent, sentiment analysis and entity identification across a variety of languages. In addition to letting you develop your own language models, the service classifies content with relationship graphs to help you better make sense of what people are saying. With these insights, you can better take action to improve your bot’s responses.

Watson Conversation Service

Tap into the power of the infamous IBM Watson to power your chatbot. This service offers the typical bells and whistles for training and labeling language models, but it goes one step further. It lets you simulate conversations. This is valuable for bot testing and iteration, letting you test on-the-fly how your bot responds to different queries. Watson Conversation Service integrates into other Watson applications, like Watson Alchemy Language and Natural Language Classifier.

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