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Improving virtual agents with data-driven UX design

Gain the insight and clarity you need to stop guessing your way through automated conversations with customers.

Data is the key to eliminating the guesswork in conversational design and user experience. But it is not always easy to make sense of all the information, apply it correctly and use it to craft specific robust guidelines.

In this webinar Dr. Cameron Taylor, head of the boost.ai UX Research Program, will illustrate how to interpret data collected from automated conversations and apply it to making better design decisions for virtual agents and chatbots.

Key takeaways

In this 60-minute webinar you will learn how to make sense of data to design effective conversations for your virtual agent.

  • Learn why an evidence-based approach is necessary
  • Study examples of findings derived from real-life conversations
  • How to pull actionable insights from a set of data

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Speakers

Dr. Cameron Taylor
UX Research Lead, boost.ai

With a Ph.D. in Linguistics from the University of Cambridge, and a human approach in an industry often dominated by machine-first thinking, Cameron has been working closely with numerous research institutions to define what really happens when humans and machines engage in communication with each other.

In this webinar, Cameron will demonstrate how to filter out the noise and replace it with data-driven insight in order to make informed decisions when designing effective conversations for a virtual agent.

Clay Cardozo (host)
Head of Technology Partnerships, boost.ai

Clay works with partners throughout Europe on conversational AI initiatives to address the wide range of service challenges that their clients face.

Leveraging a background in financial services and UX design, he pursues a balance for service design in which the allocation of human and virtual resources allows each to focus on responsibilities to which they bring the most value.