MAY 2018CIOAPPLICATIONS.COM8In the light of your experience what are the technological trends and challenges you've witnessed in the Virtual Assistance and chat-bots space?After a year of huge overhype, bots are finally starting to find their place in the care ecosystem. Clients that moved fast, broke stuff, and learned lessons about what works and what doesn't are the best positioned to drive value from the initiative. Fence sitters who didn't invest last year are finally starting to show some interest. On the platform side, bot providers are finally starting to put their functionality where their marketing is - meaning the promises they made to win business are starting to manifest in some more mature functionality. This is particularly true for bot building platforms which allow business users to configure and assemble bots without relying solely on developers.New business models are starting to emerge including pay per performance models that shift the accountability from (mostly internal) IT groups to external chatbot partners. This creates the right incentive model and should drive better agility and focus on continuous improvement/optimization.And finally, while there is some slight differentiation in the evolution of underlying technology - AI/NLU/Dialog Management - there isn't one clear winner. Even if Watson continues to outpace the competition for mindshare.What in your opinion is the right strategy for enterprises to leverage chat-bots? What should be the points of considerations, the dos and don'ts?If brands haven't already started talking about where a chat-bot might fit in their overall strategy, they ought to get moving. There are many things to work through - including who ultimately owns bot strategy. The answer today isn't clear with some marketing teams driving, some customer care teams and some IT teams trying to satisfy all parties. Assuming brands have a natural place for a bot to interact (many don't!), like live chat, Messaging, in-app, or increasingly through voice enabled interaction, a great first step would be to define a base set of use cases that lend themselves to automation. Bots do well today for highly transactional customer interactions. Pick a small set of those across the end to end (acquisition to retention) customer relationship and validate those against your existing internal architecture. From there, it's develop fast, test, measure and optimize for evermore. If your bot is performing well against one use case, look for the next best one and repeat the process.Don't:· Try and boil the ocean in the beginning· Work in a bubble - a bot is a collective endeavor, much like your website or your social media program· Oversell the capability or the promise of a human-less future to the organization until you've had a chance to meaningfully test in production and understand the economicsAccuracy is theKey Driver of a Good Chatbot ExperienceGORDON WHITE, GENERAL MANAGER AMERICAS, TSC IN MY VIEW
< Page 7 | Page 9 >