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Joshua Loo
Business problem:
Currently, AI Agent does not have the capability to process voice notes from messages. This limits platform users from handling situations where contacts prefer speaking rather than typing. Many users rely on voice messages for convenience, cultural reasons, or to describe complex issues faster. Without the ability to process voice notes, agents must manually listen, interpret, and respond, leading to slower resolution times and missed automation opportunities.
Desired outcome:
Allow AI to process voice notes from incoming messages and generate contextual responses. Specific use cases:
  • Transcribe voice notes into text and provide relevant answers.
  • Understand spoken product queries and suggest matching items.
  • Diagnose issues described verbally and respond based on knowledge sources.
  • Process voice messages containing order details, complaints, or instructions.
Use case (Capture, Convert, Retain):
This feature spans multiple phases:
Capture:
Engage users who prefer voice over text, lowering friction and making it easier to interact with the business.
Convert:
Use voice-based queries for faster product discovery, order placement, and upselling.
Retain:
Reduce effort for customers by removing the need to type, while ensuring quick and accurate responses that build trust and loyalty.