Currently in Flowbuilder, when a customer clicks a Quick Reply button, the response is received as text rather than being classified as an interactive message.
Because of this, it is not possible to easily distinguish between:
  • customers selecting a structured quick reply option.
  • customers sending a free-text message.
This creates challenges when configuring AI triggers or fallback flows, as teams must manually exclude each quick reply keyword individually. This becomes difficult to maintain when:
  • there are many quick reply options.
  • flows are frequently updated.
  • multiple chatbot journeys exist.
  • teams want scalable logic for AI fallback behavior.
For example, when using AI agents alongside structured chatbot flows, teams may want AI to only trigger when a customer sends a free-text message that is not part of predefined quick reply journeys.
Currently this requires manually listing all quick reply texts in condition nodes, or implementing complex label logic.
Both approaches add operational overhead and increase risk of logic breaking when flows change.