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Deflection – Voice Integration with Deflection Capability to WhatsApp Chat with User Intervention

"Our customers contact us through the Voice channel, with Lynn voice integration via phone calls. An automated flow in Lynn checks for executive availability in Genesys Cloud voice queues. If availability is not found, an option to contact via chat through WhatsApp is offered, implementing a proactive scheduling service on this channel. Redirected interactions will retain session self-service history and can also deploy cognitive capabilities in this flow. For example, if our client inquires: 'I want to speak with an Operator', the corresponding intention is detected. Immediately, Lynn checks availability in the voice queues. If no availability is found, a menu is displayed stating, 'Currently, we don't have executives available to handle your request via phone: (Option) Wait in Queue (Option) WhatsApp Assistance'. If the WhatsApp option is chosen, their attention will be scheduled to a Chat queue associated with that service."

Status: Active.

Complexity: Advanced.

Category: Omnichannelity

Use Case Description

  • Usability: Application of voice deflection strategy towards WhatsApp channel associated with the number provided in a phone call, incorporating cognitive functions while conserving interaction history between channels.

  • Expected Outcome: Reduce dropouts in queues by diverting voice interactions to a chat channel, minimizing waiting anxiety in queues by engaging a channel (WhatsApp) for message transactions with longer typical response times (Social Network), making the most of asynchronous chat queue resources.

Resolution Method for Use Case

Solution Description

  1. Prior subscription and connection of target channels, a self-service flow with proactive capabilities is structured in Lynn's designer, able to manage mixed deflections on voice and chat queues conditioned to the originating channel associated with the conversation.

  2. Upon detecting the cognitive intention associated with transferring the conversation to human management, queue availability is verified, integrating deflection capacity to chat channels in chat queues (Can be asynchronous queues).

LYNN Components Involved

  • Messaging Gateway.
  • Voice Gateway.
  • Cognitive Module.
  • Proactive Module.
  • Channels Sandbox (for testing).

External Components Involved

  • Chat engine with voice and chat management capabilities.
  • External channel subscriptions.
  • Cognitive engine.

Estimated Hours: 196 hours, referenced if executed by a Certified Lynn Core Developer (LCCD) personnel.

Additional Documentation:

Resource Center Documentation

External Documentation

  • Channel Policies