> For the complete documentation index, see [llms.txt](https://docs.allthingsghl.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.allthingsghl.com/ai-prompts/highlevel/ghl-voice-ai-prompts/troubleshooting/misinterpreted-caller-intent.md). # Misinterpreted Caller Intent HighLevel (GHL) Voice AI Guide for Misinterpreted Caller Intent & Clarification **Objective** This guide provides ready-to-use, word-for-word prompts for GHL Voice AI to prevent misinterpreted caller intent and ensure AI asks clarifying questions instead of making incorrect assumptions. AI confirms user intent before proceeding Prevents AI from making incorrect assumptions Uses clarifying prompts to ensure accuracy Redirects unclear responses back to the correct conversation flow 1\. Understanding the Problem: Why AI Misinterprets Caller Intent What Causes AI to Misunderstand User Intent? AI assumes meaning instead of asking for clarification. AI misinterprets vague responses like “I don’t know” or “maybe.” AI reacts incorrectly to similar-sounding inputs (e.g., confusing “cancel my service” with “cancel my appointment”). Solution: Use clarification prompts before proceeding. Confirm intent before taking action (e.g., canceling, booking, charging). Provide options to let users refine their request. 2\. Step-by-Step AI Prompt Implementation for Clarifying User Intent Step 1: Asking for Clarification Instead of Assuming Objective: If a user provides an unclear or vague response, AI must clarify before acting. Copy-and-Paste Prompt (Clarifying Vague Responses): "Just to make sure I understand correctly, are you asking about \[Option A] or \[Option B]?" "Could you clarify that for me? Are you looking for help with \[Option A] or something else?" "I want to be sure I answer correctly—are you referring to \[Option A] or \[Option B]?" ✔ Real-Life Example: User: "I need to cancel." Bad AI Response (Incorrect Assumption): "Okay, I’ve canceled your subscription." Optimized AI Response (Clarifying Prompt): "Got it! Just to be sure, are you looking to cancel an appointment or your entire service?" Where to Use in GHL: Apply when users give one-word answers or unclear intent (e.g., “cancel,” “change it,” “help”). Step 2: Confirming User Intent Before Taking an Action Objective: If an action affects a user’s account, booking, or service, AI must confirm before proceeding. Copy-and-Paste Prompt (Confirming Before Acting): "Just to confirm, you want me to \[Action]? Please say ‘Yes’ to continue or ‘No’ to change it." "I want to make sure I get this right. Are you requesting \[Action]?" "Before I proceed, can you confirm that you’d like to \[Action]?" ✔ Real-Life Example: User: "I need to change my account." Bad AI Response (Incorrect Assumption): "I’ve updated your payment details." Optimized AI Response (Clarifying Prompt): "Got it! Just to confirm, are you updating your account details or making a change to your subscription?" Where to Use in GHL: Apply before making changes to a user’s account, payment, or services. Step 3: Handling Unclear Responses Gracefully Objective: If the user gives a confusing or mixed response, AI must ask for confirmation rather than proceeding blindly. Copy-and-Paste Prompt (Handling Unclear Responses): "I didn’t quite catch that. Are you asking about \[Option A] or \[Option B]?" "I heard you say \[User Input]. Just to confirm, do you mean \[Option A]?" "I want to make sure I get this right. Are you asking about \[Option A] or something else?" ✔ Real-Life Example: User: "I think I want to cancel, but I’m not sure." Bad AI Response (Incorrect Assumption): "Okay, I’ve canceled your account." Optimized AI Response (Clarifying Prompt): "I hear you. Are you saying you’d like to pause your service temporarily, or are you looking to cancel completely?" Where to Use in GHL: Apply when users give non-committal answers like “maybe,” “not sure,” or “I think so.” Step 4: Offering Alternative Options Instead of Assuming "No" Means "Goodbye" Objective: If the user says "No" or "I’m not sure," AI must offer alternatives instead of ending the conversation. Copy-and-Paste Prompt (Offering Alternative Options): "No problem! If you’re unsure, I can send you more information to review. Would that help?" "I totally understand! Some customers prefer to test it out first. Would you like to try a free trial before making a decision?" "I hear you! Would you like to speak with a representative instead?" ✔ Real-Life Example: User: "I don’t think this is right for me." Bad AI Response (Incorrect Assumption): "Okay, goodbye." Optimized AI Response (Clarifying Prompt with Alternative Option): "I understand! If you’d like, I can send over more details so you can review it before making a decision. Would that be helpful?" Where to Use in GHL: Apply when users hesitate or reject an offer instead of letting the conversation die. 3\. Full Example of an Optimized AI Conversation (With Clarification Prompts & Intent Confirmation) Scenario: AI Handling an Ambiguous User Request AI: "Hi, this is Sarah from \[Company Name]. How can I assist you today?" User: "I need to cancel." AI: "Got it! Just to be sure, are you looking to cancel an appointment or your entire service?" User: "Uh, I think I just need to reschedule my appointment." AI: "Understood! Would you like me to send you a text with available time slots?" User: "Yeah, that’d be great." AI: "Awesome! I just sent you a message with available times. Let me know if I can help with anything else!" Outcome: AI successfully clarified intent, prevented errors, and avoided making incorrect assumptions. 4\. Implementation Checklist for GHL Voice AI Agents Copy and paste clarification prompts into the GHL Voice AI response library. AI must ask for confirmation before taking an action that could affect a user’s account. Use clarification prompts for vague responses to prevent misinterpretation. Provide alternative options instead of assuming rejection means "end the call." Test AI interactions to identify common misinterpretations and refine responses. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. 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