💬 AI-powered WhatsApp customer support for Shopify brands with LLM agents

⚡ 1,274 views · 💬 Support Chatbots

Description

🚀 AI-Powered WhatsApp Customer Support for Shopify Brands

This n8n template builds a WhatsApp support copilot that answers order status and product availability from Shopify using LLM “agents,” then replies to the customer in WhatsApp or routes to human support.

Use cases

• “Where is my order?” → live status + tracking link
• “What are your best-selling T-shirts?” → in-stock sizes & variants
• Greetings / small talk → welcome message
• Anything unclear → handoff to support channel

Good to know

• WhatsApp Business conversations are billed by Meta/Twilio/Exotel; plan accordingly.
• Shopify Admin API has rate limits (leaky bucket) --- stagger requests.
• LLM usage incurs token costs; cap max tokens and enable caching where possible.
• Avoid sending PII to the model; only pass minimal order/product fields.

How it works

1. WhatsApp Trigger
   Receives an incoming message (e.g., “Where is my order?”).

2. Get Customer from Shopify → Customer Details → Normalize Input
   Looks up the customer by phone, formats the query (lower-case, emoji & punctuation normalization).

3. Switch (intent router)
   Classifies into welcome, orderStatusQuery, productQuery, or supportQuery.

4. Welcome path
   Welcome message → polite greeting → (noop placeholder).

5. Order status path (Orders Agent)

   • Orders Agent (LLM + Memory) interprets the user request and extracts needed fields.
   • Get Customer Orders (HTTP to Shopify) fetches the user’s latest order(s).
   • Structured Output Parser cleans the agent’s output into a strict schema.
   • Send Order Status (WhatsApp message) returns status, ETA, and tracking link.

6. Products path (Products Agent)

   • Products Agent (LLM + Memory) turns the ask into a product query.
   • Get Products from Shopify (HTTP) pulls best sellers / inventory & sizes.
   • Structured Output Parser formats name, price, sizes, stock.
   • Send Products message (WhatsApp) sends a tidy, human-readable reply

7. Support path Send a message to support posts the transcript/context to your agent/helpdesk channel and informs the user a human will respond

How to use

• Replace the manual/WhatsApp trigger with your live WhatsApp number/webhook.
• Set env vars/credentials: Shopify domain + Admin API token, WhatsApp provider keys, LLM key (OpenAI/OpenRouter), and (optionally) your support channel webhook.
• Edit message templates for tone, add your brand name, and localize if needed.
• Test with samples: “Where is my order?”, “Show best sellers”, “Hi”.

Requirements

• WhatsApp Business API (Meta/Twilio/Exotel)
• Shopify store + Admin API access
• LLM provider (OpenAI/OpenRouter etc.)
• Slack webhook for human handoff

Prerequisites

• Active WhatsApp Business Account connected via API provider (Meta, Twilio, or Exotel).
• Shopify Admin API credentials (API key, secret, store domain).
• Slack OAuth app or webhook for human support escalation.
• API key for your LLM provider (OpenAI, OpenRouter, etc.).

Customising this workflow

• Add intents: returns/exchanges, COD confirmation, address changes.
• Enrich product replies with images, price ranges, and “Buy” deep links.
• Add multilingual support by detecting locale and templating responses.
• Log all interactions to a DB/Sheet for analytics and quality review.
• Guardrails: confidence thresholds → fallback to support; redact PII; retry on API errors.

🔗 Nodes Used

HTTP Request, Slack, WhatsApp Business Cloud, AI Agent, OpenAI Chat Model, Simple Memory

📥 Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup