𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 is the most important tool of communication invented by human civilization. It is either spoken or written, consisting of the use of words in a structured and conventional way.Language helps us share our thoughts, and understand others.
𝐍𝐚𝐭𝐮𝐫𝐚𝐥 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠 is, a form of artificial intelligence, all about trying to analyze and understand either written or spoken language and the context that it’s being used in. The ultimate objective of NLP is to read, decipher, understand, and make sense of the human languages in a manner that is valuable.
Wikipedia defines NLP as “ a sub field of AI concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.”
𝐔𝐬𝐞𝐬 𝐨𝐟 𝐍𝐚𝐭𝐮𝐫𝐚𝐥 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠
Spell check is a form of NLP that everyone is used to by now. It’s unobtrusive, easy to use, and can reduce a lot of headaches for users.Not every user is going to take the time to compose a grammatically perfect sentence
Search autocomplete is another type of NLP that many people use on a daily basis and have almost come to expect when searching for something. This is thanks in large part to pioneers like Google, who have been using the feature in their search engine for years. The feature is just as helpful on company websites.
3. Chat Bots
Chatbots help meet customers’ request for personalization: by collecting user-relevant data they can address them individually and offer fully personalized experiences devoid of the stress of human-to-human communication. Moreover, chatbots increasingly find application in sales: they can target prospects, strike a conversation, schedule appointments and much more.
Facebook Messenger is one of the latest ways that businesses can connect to customers through social media. NLP makes it possible to extend the functionality of these bots so that they’re not simply advertising a product or service, but can actually interact with customers and provide a unique experience.
4. Social Media Monitoring
Knowing what customers are saying on social media about a brand can help businesses continue to offer a great product, service, or customer experience. NLP makes monitoring and responding to that feedback easy.
5. Descriptive Analytics
Accumulating reviews for products and services has many benefits. Reviews can increase confidence in potential buyers and they can even be used to activate seller ratings on Google Ads. However, there’s another benefit of reviews that you should be tapping into if you’re not already.
When it comes to adjusting sales and marketing strategy, sentiment analysis helps estimate how customers feel about your brand. This technology, also known as opinion mining, stems from social media analysis and is capable of analyzing news and blogs assigning a value to the text (negative, positive or neutral). A Switzerland-based company Sentifi uses natural language processing to find influencers and define its key brand advocates. Today’s NLP algorithms go as far as identifying emotions such as happy, annoyed, angry, sad. Needless to say, with precise tools like this marketers now have all it takes to develop actionable strategies and make informed decisions.
What other NLP and text mining use cases in business would you add here?