AWS Partner Network (APN) Blog
Tag: Call Center
Transforming Customer Experience and Boosting Retention with AI-Powered Contact Centers
Today’s global marketplace relies heavily on contact centers for streamlining, maintaining, and maximizing customer service and sales at scale. Explore the role of machine learning solutions in transforming contact centers and the key aspects of Quantiphi’s contact center intelligence (CCI) solution built on AWS. Learn how it helped a U.S.-based consumer healthcare organization address contact center challenges by using custom artificial intelligence and ML techniques.
Intelligent Case Management Using Amazon Connect and Amazon Kinesis Data Streams
There is a flurry of contact center solutions being brought to market, but enterprise customers often find these solutions time-consuming, cost-intensive, and difficult to implement. Learn how to integrate an Amazon Connect instance with Salesforce Service Cloud to automatically create a case in Salesforce using REST APIs and Amazon Kinesis Data Streams. This allows you to proactively handles call drops occurring for customers when they dial into a contact center solution.
Intelligent Call Routing Using Amazon Fraud Detector and Amazon Connect
Amazon Fraud Detector is a fully managed service that makes it easy to identify potentially fraudulent online activities, such as online payment fraud and the creation of fake accounts. Learn how APN Premier Consulting Partner TCS has been integrating Amazon Fraud Detector to detect spam calls and route them efficiently using Amazon Connect. Used together, these AWS services can distinguish your genuine customers from spam or fraudulent callers.
Unlocking the Value of Your Contact Center Data with TrueVoice Speech Analytics from Deloitte
Voice data represents a rich and relatively untapped source of information that can help organizations gaining precious insights into their customers and operations. By leveraging a number of AWS services, Deloitte’s speech analytics solution, TrueVoice, can process voice data at scale, apply machine learning models to extract valuable information for this unstructured data, and continuously refine and enrich such models, tailoring them to specific industries and business needs.