Machine Learning Powered Contact Center Analytics with Contact Lens for Amazon Connect
Your contact center is the biggest touchpoint between you and your customers, and every engagement can provide your team with powerful insights. With Contact Lens for Amazon Connect, customer service supervisors can quickly and easily discover emerging themes and trends from customer conversations, directly in Amazon Connect. In this tech talk, we’ll show you how Contact Lens for Amazon Connect transcribes contact center calls to create a fully searchable archive, including sentiment analysis and silence detection to improve customer service agents’ performance. You’ll learn how to surface valuable customer insights from every conversation with integrated machine learning (ML) and artificial intelligence (AI), allowing you to deeply understand your customer conversations and take the appropriate actions without having to manually audit every contact.
Machine learning technologies are helping to transform the modern contact center from a cost center into a profit center. Organizations are deploying artificial intelligence (AI) and machine learning (ML) services to do things like create intelligent chatbots, intelligent voicebots, smart routing, real-time voice analytics with sentiment analysis, agent assist with next best action, and post-call analytics.
By enhancing the overall customer experience through your contact center, you can boost repurchase odds and improve long-term loyalty. AWS offers solutions for customers who want an end-to-end contact center solution, or those who want to build intelligence into their existing contact center.
*Explore how with little coding, you can analyze call and chat transcripts, customer and agent sentiment
*Learn to uncover potential risk and find and address the conversations where your attention is needed most
*Give your contact center supervisor the tools to draw powerful insights to help improve your agent’s and customer’s experience
***To learn more about the services featured in this talk, please visit:
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