Bots can augment human interaction, create greater business efficiencies, and remove friction from customer interactions.
It’s also a market that’s attracting impressive investment dollars, with 180 bot companies raising $24 billion in funding to date. Industry leaders from IBM to Facebook are making big efforts to take advantage of this trend, spending significant resources encouraging developers to create new bots that enable more personalized customer interactions. In March of 2016, Cisco announced the Spark Innovation Fund, a $150 million investment in bots and developers who want to make new products for Cisco endpoints in offices around the world.
Some of the most obvious uses for bots revolve around communication, customer service, and ecommerce. Chatbots are at the center of the way people communicate today, with over 2.5 billion people worldwide using a messaging platform like WhatsApp, Facebook Messenger, or Telegram. Twitter recently rolled out a bot-like feature within its DM service to enable brands to interact more frequently with customers, with the goal of ultimately improving the customer experience. Facebook is testing a service to enable users to make payments on Facebook Messenger that are facilitated via the use of bots built on its platform. Gaming companies are using bots to help ward off trolls that might interfere with the natural progression of the game.
All this is happening while we create almost unfathomable amounts of data — data that is expected to reach 35 zettabytes by 2020. So how can companies outside ecommerce take advantage of bots to automate these new data sets and deliver smarter, faster analytics access in the process? Let’s take a look:
The concept of human to machine interaction via natural language processing can drive immediate analytics responses, rather than waiting on human analysis…
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