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ContactEngine is Now Part of NICE: Re-inventing Proactive Conversational AI Together

Insights: Whitepaper
Proactive and Reactive: Symbiotic sides of the same AI coin

Introduction

Artificial Intelligence (AI) as a phrase is bandied about to refer to any number of
technologies currently in use. And it’s not that this is wrong per se, but it's like referring
to rustic Italian cuisine and molecular gastronomy simply as “food”. The world would
be a poorer place without either, but they serve entirely separate purposes for the
palate.

According to Gartner, “By 2025, proactive (outbound) customer engagement
interactions will outnumber reactive (inbound) customer engagement interactions.”
The distinction being made here is the AI as its designed for use in the reactive realm
(think chatbots) vs. the use case of proactive engagement. While the core technology
that underlies both may be similar, and both have specific use cases, it is true that
proactive engagement is a more focused utilization.

If you’ve ever attempted to play the game twenty questions, you’ve had an inkling of
what a chatbot is attempting to do, i.e., asking a series of questions of an individual
in an effort to get at an answer. Except in the case of chatbots, you’re usually playing
the game with an irate customer in a negative frame of mind. Proactive engagement
on the other hand is reaching out to the person with a clear objective, ideally before
they have a chance to become irritable. So, when we’re trying to compare Chatbots to
Proactive Conversational AI, as is the case in so many instances, context is king... 

Content

  • Introduction
  • Definitions and Hierarchy
  • Differentiation between proactive and reactive technologies
  • Market Players
  • Conclusion

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Improving customer engagement to ensure right-first-time delivery and repair through proactive conversation

Automotive

Managing and improving customer conversations across complex networks of manufacturers, dealers and customers

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