Conversational marketing is the latest buzzword in marketing. Everyone is familiar with Siri, Cortana, Alexa, and Google Voice Search. These are personal assistant apps that have learned enough human language and the relationships between words and terms to respond to most questions and commands we can give them.
The technology behind them is called natural language processing, and it involves algorithms that allow machines to learn words and identify patterns of words in common human language. NLP techniques also assume that, over time, machines get better at recognizing these patterns, and thus better at processing verbal requests and instructions
So, what does all of this have to do with marketing? A lot, actually.
Big Data Vs. Big Text
Big data is all the rage right now among marketers and for a good reason.
Big data analytics involves gathering information and data from the vast supply 'out there,' organizing it, and then presenting reports based upon human inquiry. In general, it allows businesses to see trends in human behaviors and make business decisions based upon those trends.
Big data is largely structured data. For example, if a lender wanted to come up with new loan products, he would gather data on current products, their popularity, and the types of loans that certain demographics have typically pursued. Based on this information, he would develop the new products.
Big text is largely what is called 'unstructured data.' It comes from social media posts, emails, customer service interactions, and product and service reviews – that 90% of the 'stuff' on the web that is not structured. Big globs of it are just out there, and it has been almost impossible for marketers to gather it all and make sense of it.
Enter Natural Language Processing
Suppose someone is searching for amazing vegan dinner recipes. As humans, we understand what they are looking for. The question is, can machines be taught to do the same?
Normal searches may yield results for dinner recipes, information about vegans, etc. But what we want machines to do is to understand the relationships among all of the words in the search phrase, so that the results bring precisely what is wanted. Can they do it? Yes, to a larger degree than you might think, and they are getting better at it all the time.
Natural language processing involves machines taking terms of a search phrase, combing through all of the unstructured data that is out there, finding the patterns where the words are used in a combination, and then generating results based on those combinations. If you are a company that offers a subscription to vegan recipes or even home delivery of vegan meals, you want that machine to spit out your website.
How Marketers Can 'Cash In'
Natural language processing is poised to become a multi-billion-dollar industry by 2020. It is a technology that virtually any business can use to save time and acquire the other resources they need to meet consumer demands and to market to those customers in a more targeted manner. One innovative paper writing service, for example, is using this volume of unstructured data to understand the biggest issues students are having with their written coursework assignments. As they gather the information, they are able to do two things: recruit and employ those writers who will meet these needs and develop marketing strategies based upon this big text data. Having the technology that provides this information quickly and without human effort is huge. It saves time, can reduce staff needs, and gives marketers data that is far more reliable than “hunches” or “gut feelings.”