AWS announced Contact Lens for Amazon Connect, a set of capabilities for Amazon Connect enabled by machine learning (ML) that gives contact center supervisors and analysts the ability to understand the content, sentiment, and trends of their customer conversations to identify crucial customer feedback and improve customer experience.
It shows how positive or negative the interaction was , who spoke for what amount of time etc. Supervisors can also access recording of the call used for the analysis and there is an option to remove sensitive data like user name and location to protect customers.
The Contact Lens can also let us filter the calls based on various factors like sentiments or number of times a words was used , call duration , call id etc . Sentiments are analysed between -5 to +5 where -5 means very unhappy and +5 means extremely happy.
Contact Lens for Amazon Connect produces an output file in customers’ S3 bucket that contains metadata (such as transcriptions, sentiment, categorization labels, talk speed, and interruptions). Organizations can leverage this data in various existing systems and do not need to invest in new tooling. For example, you can use this data in a Business Intelligence tool, like Amazon QuickSight or Tableau, along with your CRM data to gain insights into customer engagements. Your data science teams can also use this data to create custom machine learning models with Amazon SageMaker.
As you saw it is pretty is easy to integrate a basic Contact Lens on AWS. Now you can try out and get all the analysis for your Contact center. If you are looking to implement this from us just reply to us or contact us and we would be all help.