Why Chatbots Are the Future of Big Data
- by 7wData
Facebook launched the Messenger Platform Almost exactly a year ago, Facebook launched the Messenger Platform , allowing developers to create their own chatbots. For many people that was the first time they had even heard of chatbots, but Facebook and others now proclaimed them as 'the next big thing', conversational assistants that would revolutionize how businesses communicate with their customers. But where are chatbots now? Do they still have a role to play? Here is how they are set to transform enterprise, and why they are the future of big data.
chatbots are the new appsgrowing use of messenger apps In the wake of Facebook's announcement, many have repeated the mantra ' chatbots are the new apps ' (a claim made by Microsoft's CEO Satya Nadella in March 2016). But despite solid statistics identifying the slowdown of the app market, the growing use of messenger apps , and the fact that there are already tens of thousands of Messenger bots out there, the revolution that was promised is yet to arrive. I mean, how often do you use a chatbot instead of an app?
The problem is that chatbots have yet to find their place in the world. Many are gimmicky, or simply provide the same functionality as an existing app with a different interface. This is a bad design approach to start with, and the truth is that for some tasks a graphical user interface is actually more intuitive anyway. The idea that chatbots will replace apps is a good headline, but it's unhelpful- to increase adoption rates developers have to create chatbots that do things apps can't, or at least concentrate on use cases that suit their conversational nature. Â Â Â
chatbots in banking So where does that leave chatbots? Just as apps didn't replace websites, successful chatbots won't be built primarily to replace apps, but for the tasks to which they are best-suited. For example, the strength of a conversational assistant is its ability to replicate a human, so it is the human interactions between business and customer that they will replace. In fact, we are already seeing this in the growing use of chatbots in banking . The way chatbots can answer queries allows them to give the impression that a bank really knows their customer, restoring the 'personal touch' that has been lost in recent years. The same is true for other industries - it is in the areas of customer service, product selection advice (think expert recommendations about fashion, travel etc.) and customer relationship management that chatbots can currently provide real value.
NPL platforms A successful chatbot involves a large amount of data exchange between business and customer. However, due to the nature of those interactions, the information provided by humans is complex, unstructured text. So how is that data analyzed to be sure that queries are responded to correctly? It is recent developments in natural language processing (NLP) that are making it possible. Just a few years ago it was seen as a fringe technology with frustratingly low accuracy, but big strides have brought it to the mainstream. Ready-made NPL platforms from the likes of IBM, Microsoft and Google are available to developers, ensuring that any chatbot can take advantage of them.
What is important for enterprise to consider is that the power of natural language processing can be leveraged not just to improve the functionality of a chatbot, but to further analyze the data being exchanged. That unstructured text is a potential goldmine of information, that (as long as data privacy issues are addressed) should be fully utilized.
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