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Quick Summary / TL;DR

Social commerce sellers on Facebook and Instagram frequently struggle with high inquiry volumes regarding product prices, stock availability, and delivery charges. Connecting your product catalog database directly to an AI messaging interface enables instant, accurate responses grounded in real inventory data, while preserving human staff escalation for custom orders.

The Challenge: High Message Volumes & Delayed Responses

E-commerce sellers who publish product listings on social media receive constant customer DMs asking repetitive questions: "Is this color in stock?", "What is the price?", or "How much is delivery to Chittagong?".

When staff members answer these manually, response delays accumulate during peak evening shopping hours, leading prospective buyers to purchase from competitors who reply immediately.

Implementation Blueprint: 5-Phase Catalog Chatbot Workflow

Phase 1: Catalog & Database Structuring

Structure your product inventory in a structured database (e.g., Supabase or Google Sheets) with unique SKUs, stock counts, size/color variants, and exact pricing.

Phase 2: Meta Webhook Integration

Connect Meta Messenger API endpoints to receive real-time message events from prospective buyers on your Facebook Page.

Phase 3: AI Retrieval & Function Calling

Use OpenAI function calling to interpret user intent (e.g., "Do you have size L in black?"), query your database for exact SKU stock, and draft an accurate reply.

Phase 4: Order Detail Confirmation

Collect buyer delivery address, contact phone number, and payment preferences, formatting the order details for admin confirmation.

Phase 5: Human Staff Escalation

Provide an instant handoff option when buyers ask for custom discounts, wholesale orders, or technical support, notifying sales representatives instantly.

Technical Limitations & Boundary Safeguards

To maintain reliability, chatbot implementations must enforce strict operational constraints:

No Hallucinated Pricing: The AI model must strictly retrieve prices from database records, rather than guessing costs.
Stock Sync Frequency: Inventory stock counts must sync in real time to prevent accepting orders for out-of-stock items.
Rate Limit Buffering: Implement queue buffering to handle sudden spikes in message volume during promotional campaigns.

Where DigiRib May Support Implementation

Building a reliable inventory-connected chatbot requires front-end integration, database setup, and secure API routing. DigiRib offers custom-scoped development (including Product 1 modules) to connect your product inventory to messaging channels safely.

Explore Automation Services → Contact DigiRib →

Primary References

• Meta Messenger Platform API: Webhook Events & Send API Guidelines.
• OpenAI API Documentation: Function Calling & Structured Data Retrieval.

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