Amazon Connect Customer now supports information extraction, which automatically captures key data from voice and chat interactions, reducing manual data capture and improving agent and supervisor productivity. Information extraction captures verbatim values like account numbers, reservation IDs, and product names, as well as derived insights inferred from the conversation such as reason for contact, resolution provided, and next steps promised.
You define conversational analytics rules for what to extract and when. Extraction operates on raw contact content before redaction, so you can capture specific data points while still redacting sensitive values from recordings and transcripts. Agents see extracted values during After Contact Work, supervisors use them to search and review contacts, and developers access them programmatically through APIs, Kinesis Data Streams, and S3 output files. You can also feed extracted values directly into rule actions like email notifications, task creation, and case creation, turning unstructured conversations into automated experiences. For example, a travel company can automatically extract “Hotel Name,” “Reservation ID,” and “Reason for call” from interactions, then populate outbound emails and create follow-up tasks, eliminating manual data entry and reducing handle time.
To learn more, see Information extraction in the Amazon Connect Customer Administrator Guide, or visit the Amazon Connect Customer website. For a complete list of conversational analytics capabilities available by AWS Region, refer to Availability of Connect Customer features by Region.
Categories: marketing:marchitecture/contact-center,general:products/amazon-connect
Source: Amazon Web Services
