Example Pega data utilization by an IVR
When a customer calls into a business’s IVR, the contact is identified, and then the IVR verifies the customer. Once the customer is successfully verified, the customer’s context is set, a service interaction is created, and the IVR requests a set of recommendations. The IVR is responsible for translating text-to-speech (TTS) for the recommended inquiry responses and service case offer. When the customer accepts the service case, the case is then created by the IVR, and it receives step-by-step text-based case flow prompts to walk the customer through the case. The IVR is responsible for translating the customer’s spoken response from speech-to-text (STT) so that the Pega Natural Language Processing (NLP) capability can interpret the customer’s answer to a prompt. When the service case is complete, the customer receives a confirmation and can either hang-up or select another option.
A transcript of the customer’s interaction with the IVR is saved post-call. In addition, Pega Customer Service starts a collection of data for two reports that measure how many incoming customer calls are being offered a case and customer acceptance rates for the case types offered.
The following diagram illustrates an example integration of Pega Customer Service with Connect IVR, Lex bot, and Lambda components of the Amazon Connect IVR.
Pega Customer Service provides contact identification, customer context set-up, personalized recommendations, and service case execution to an IVR system by leveraging an Interactive Voice Response with Intelligent Virtual Assistant (IVR-IVA) channel. The IVR-IVA channel provides a secure integration point between the IVR and Pega Customer Service, so that those two systems can communicate using an open public set of IVR-IVA APIs. The IVR-IVA channel leverages the Pega NLP capability for entity detection of customer responses during service case execution. After the call ends, a transcript of the call is saved in the Pega Customer Service interaction history.
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