As conversational AI becomes a primary interface for product discovery and customer engagement, marketing leaders face a new imperative: integrating chat-based signals into their personalization stack. For enterprises running Adobe Experience Cloud, this means treating conversational data, utterances, tone, vernacular and intent as first-class inputs into Real-Time CDP and Journey Optimizer. This article outlines how to architect that integration, with code-level examples and architecture. Step 1: Capture Conversational Signals as Real-Time Events Conversational platforms like ChatGPT generate rich signals like phrasing, tone, dialect, urgency and emotional cues. These must be streamed into Adobe RTCDP as XDM-compatible events. Example: Ingesting a conversational utterance const event = { _experience: { decisioning: { conversation: { utterance: "I need something quick for the kids", intent: "meal recommendation", tone: "c...