> ## Documentation Index > Fetch the complete documentation index at: https://docs.subverseai.com/llms.txt > Use this file to discover all available pages before exploring further. # Schedule Callback Node > Schedule automated follow-up calls with customers ## Overview The Schedule Callback Node allows you to schedule follow-up calls with customers, passing additional context from previous interactions. This enables intelligent, context-aware callbacks based on workflow logic. ## Use Cases * **Unresolved Issues**: Schedule callbacks for issues that couldn't be resolved immediately * **Customer Requests**: Honor customer requests to be called back at specific times * **Follow-up Campaigns**: Automated follow-ups after initial contact * **Dropped Calls**: Reconnect with customers after unexpected disconnections * **Appointment Reminders**: Schedule reminder calls before appointments * **Payment Follow-ups**: Call customers about pending payments * **Survey Callbacks**: Schedule calls to collect feedback * **Lead Nurturing**: Follow up with leads at optimal times ## Inputs ### **Greetings\_message** Greeting message the voice agent will say to the customer. **Purpose:** * Overrides the [initial prompt](/agents/agent-configurations#agent-settings) defined for the agent * Provides context-specific greeting * Can be AI-generated or manually written **Behavior:** * Can be linked from a previous block (e.g., AI-generated greeting) * Can be manually written in the node * Data linkage overrides written text **Example:** ``` Hello John, this is a follow-up call regarding your support ticket #12345. We have an update on your issue. ``` **AI-Generated Example:** ``` Link from AI Query Agent output that generates: "Hi Jane, I'm calling back as you requested. I have the information about the Premium Plan pricing you asked about." ``` ### **Conversation\_context** Pass previous conversation context to the voice agent. **Purpose:** * Provide continuity between calls * Give agent full context of previous interactions * Enable personalized conversations **What to Include:** * Previous call transcript * Customer history * Issue details * Relevant notes **Example:** ``` Previous Call Summary: - Customer called about order delay - Order #ORD-12345 was stuck in shipping - Promised to investigate and call back - Customer prefers morning calls Customer Details: - Name: John Doe - Premium customer since 2023 - Previous issues: 0 ``` ### **Scheduled\_Time** (Required) Set the exact time for the callback. **Format:** ISO 8601 date format `YYYY-MM-DDTHH:MM:SSZ` **Examples:** * `2025-12-10T10:00:00Z` - December 10, 2025 at 10:00 AM UTC * `2025-12-11T15:30:00Z` - December 11, 2025 at 3:30 PM UTC **Tips:** * Always use future timestamps * Consider customer timezone * Respect business hours * Account for working hour constraints ### **Bot\_Number** (Required) Phone number to be used to call the customer. **Configuration:** * Can be linked from a previous block * Can be selected from dropdown * Data linkage overrides dropdown selection **Format:** +\[country code]\[number] **Example:** `+91xxxxxxxxxx` ### **Use\_Case** (Required) Voice agent that will handle the callback. **Configuration:** * Can be linked from a previous block * Can be selected from dropdown * Data linkage overrides dropdown selection **Example:** `customer_support`, `sales_follow_up` ### **Customer\_Number** (Required) Customer's phone number to call. **Format:** +\[country code]\[number] **Example:** `+91xxxxxxxxxx` ### **Customer\_Details** Customer information in JSON format. **Purpose:** * Personalize the callback * Provide agent with customer context * Include relevant data for the conversation **Example:** ```json theme={null} { "name": "John Doe", "email": "john@example.com", "ticket_id": "TKT-12345", "issue": "Order delay", "order_id": "ORD-789" } ``` ### **Agent\_Options** Override default agent settings for this callback. **Use Cases:** * Change language for specific customers * Use different voice * Modify initial prompt * Adjust call settings **Example:** ```json theme={null} { "language": "hi-IN", "voice": "Riya", "max_duration": 300 } ``` ### **No\_Of\_Retries** Number of retry attempts if the callback fails. **Recommended:** 2-3 retries **Example:** `2` ### **Retries\_After\_In\_Hrs** Time interval between retry attempts (in hours). **Recommended:** 1-2 hours **Example:** `1` ### **Start\_Working\_Hour** Start of business hours in 24-hour format (HH:MM). **Purpose:** * Ensure calls only during business hours * Respect customer preferences * Avoid early morning calls **Example:** `09:00` ### **End\_Working\_Hour** End of business hours in 24-hour format (HH:MM). **Purpose:** * Prevent late evening calls * Comply with regulations * Respect customer time **Example:** `18:00` ### **Timezone** Timezone for working hours calculation. **Default:** Asia/Kolkata **Examples:** * `America/New_York` * `Europe/London` * `Asia/Tokyo` ## Outputs ### **Callback\_scheduled** Confirms if the callback was successfully scheduled. **Values:** * `True`: Callback successfully scheduled * `False`: Scheduling failed **Usage:** * Connect to conditional logic * Trigger error handling * Log for monitoring * Send notifications ## Configuration Examples ### Example 1: Simple Callback ``` Greetings_message: "Hello, this is a follow-up call from SubVerse." Scheduled_Time: 2025-12-10T14:00:00Z Bot_Number: +91xxxxxxxxxx Use_Case: customer_support Customer_Number: +91xxxxxxxxxx ``` ### Example 2: Context-Aware Callback ``` Greetings_message: "Hi John, I'm calling back about your order #12345." Conversation_context: "Previous call: Customer reported order delay. Promised to check with shipping and call back." Scheduled_Time: 2025-12-10T10:00:00Z Bot_Number: +91xxxxxxxxxx Use_Case: order_support Customer_Number: +91xxxxxxxxxx Customer_Details: { "name": "John Doe", "order_id": "ORD-12345", "issue": "Shipping delay" } ``` ### Example 3: Scheduled with Retries ``` Greetings_message: "Hello, this is a reminder about your payment." Scheduled_Time: 2025-12-10T11:00:00Z Bot_Number: +91xxxxxxxxxx Use_Case: payment_reminder Customer_Number: +91xxxxxxxxxx No_Of_Retries: 2 Retries_After_In_Hrs: 2 Start_Working_Hour: 09:00 End_Working_Hour: 18:00 Timezone: Asia/Kolkata ``` ### Example 4: AI-Generated Callback ``` Greetings_message: [Linked from AI Query Agent] Conversation_context: [Linked from previous call transcript] Scheduled_Time: [Calculated by AI based on customer preference] Bot_Number: +91xxxxxxxxxx Use_Case: sales_follow_up Customer_Number: +91xxxxxxxxxx Customer_Details: [Linked from CRM data] ``` ## Workflow Integration ### Common Patterns **Pattern 1: Post-Call Callback** ``` Incoming Call Node ↓ AI Query Agent (analyze if callback needed) ↓ Schedule Callback Node (if needed) ``` **Pattern 2: Dropped Call Recovery** ``` Voice Agent Node ↓ Smart Filter (check if call duration < 30 seconds) ↓ Schedule Callback Node (immediate callback in 5 minutes) ``` **Pattern 3: Time-Based Follow-up** ``` Voice Agent Node ↓ AI Query Agent (determine follow-up timing) ↓ Schedule Callback Node (schedule based on AI decision) ``` **Pattern 4: Multi-Step Campaign** ``` Upload Data Node ↓ Voice Agent Node (initial call) ↓ AI Query Agent (analyze outcome) ↓ Schedule Callback Node (if not converted) ``` ## Best Practices ### Timing * **Customer Preference**: Honor requested callback times * **Business Hours**: Always use working hour constraints * **Timezone Awareness**: Consider customer location * **Spacing**: Don't schedule too many callbacks close together ### Context * **Full History**: Include complete previous interaction context * **Relevant Details**: Only include information needed for the call * **Clear Summary**: Provide concise context summary * **Update Regularly**: Ensure context is current ### Personalization * **Use Names**: Include customer name in greeting * **Reference History**: Mention previous interactions * **Specific Purpose**: Clearly state reason for callback * **Custom Greetings**: Tailor message to situation ### Retry Strategy * **Reasonable Attempts**: 2-3 retries is usually sufficient * **Appropriate Spacing**: 1-2 hours between retries * **Time Limits**: Don't retry beyond same day * **Alternative Contact**: Consider other channels after failed retries ## Monitoring ### Track Callback Performance **Metrics to Monitor:** * **Schedule Success Rate**: Percentage of successfully scheduled callbacks * **Connection Rate**: Callbacks that successfully connected * **Completion Rate**: Callbacks that achieved their objective * **Retry Effectiveness**: Success rate of retry attempts ### Analyze Patterns **Look For:** * **Optimal Timing**: When callbacks are most successful * **Context Impact**: How context affects outcomes * **Retry Patterns**: Which retries succeed * **Failure Reasons**: Why callbacks fail ## Troubleshooting ### Callback Not Scheduling **Possible Causes:** * Invalid Scheduled\_Time format * Time in the past * Missing required fields **Solutions:** * Use ISO 8601 format * Ensure future timestamp * Verify all required inputs ### Callback Not Connecting **Possible Causes:** * Invalid phone number * Customer unavailable * Network issues **Solutions:** * Validate phone number format * Set appropriate retry logic * Check telephony integration ### Wrong Timing **Possible Causes:** * Timezone mismatch * Working hours not set * Incorrect time calculation **Solutions:** * Verify timezone setting * Set Start/End Working Hours * Double-check time calculations ## Next Steps Configure outbound calling Intelligent callback decisions Send callback confirmations Monitor callback performance Link the Greetings\_message and Conversation\_context from AI Query Agent to create intelligent, context-aware callbacks. Always respect customer preferences for callback timing. Unsolicited calls at inconvenient times can harm customer relationships.