--- title: "AI customer support in Gorgias: workflows for ecommerce helpdesks" excerpt: "Gorgias is the ecommerce-native helpdesk that integrates with Shopify, BigCommerce, and Magento. AI agents augment order-question triage, returns intent classification, and customer-LTV-aware response through Gorgias REST API. The workflow that compounds: agent reads order context, drafts reply, agent confirms, the rationale persists." author: mei category: Playbooks date: "2026-05-30" --- AI customer support inside Gorgias works because the helpdesk already has the order context attached to every ticket. Shopify and BigCommerce data flows in natively. The AI layer (Gorgias Automate, plus outside models like ChatGPT or Claude called through the Gorgias REST API) reads that context, classifies intent, drafts the reply, and routes anything ambiguous to a human. You keep Gorgias as the system of record. You add an interpretation layer on top. See the [pillar guide on running support with AI](/blog/how-to-run-customer-support-with-ai) for the broader pattern. ## The workflow that actually compounds **1. Pull order context at ticket creation.** Gorgias auto-attaches Shopify order data to tickets when the customer email matches. For BigCommerce stores, the same integration runs through the Gorgias REST API. Confirm the order, fulfillment status, and tracking are visible in the sidebar before the agent or the model touches the reply. **2. Classify intent with Gorgias Automate or an external model.** Gorgias Automate ships with intent detection trained on ecommerce tickets: "where is my order," "return request," "exchange," "cancel order," "discount request." For anything custom, call ChatGPT or Claude through a webhook and write the predicted intent back as a Gorgias tag. The tag drives routing rules. **3. Draft the reply against the order, not the ticket.** This is the part most teams get wrong. The model should read the Shopify order: items, fulfillment carrier, last scan, return policy window. Then draft. A WISMO ticket answered against the order takes two seconds; the same ticket answered against the ticket body alone forces a follow-up. The [ticket triage primer](/blog/ai-ticket-triage) covers the classification side in more depth. **4. Human confirms, then sends.** Auto-send is a trap for ecommerce. LTV-aware replies (free reshipment for a VIP, store credit for a first-time buyer) require judgment. The agent reviews the draft, edits if needed, and sends from inside Gorgias. **5. Log the rationale somewhere durable.** Why the agent gave store credit instead of a refund. Why this ticket got escalated. This is the part Gorgias does not hold well. ## Worked example: a return on a $340 Shopify order Customer emails about a damaged jacket. Gorgias attaches the order. Gorgias Automate tags it `return-damaged`. ChatGPT, called through the REST API, drafts: "We're sorry, here's a prepaid label, refund issues on receipt." The agent checks: customer is a repeat buyer, three prior orders, no return history. The agent upgrades the offer to a replacement plus a discount code and sends. The interpretation (why this customer got the upgrade) needs to survive past the ticket close. See [ecommerce refund workflows](/blog/ecommerce-refund-workflows) for the policy side. ## The persistent-state pain Gorgias closes the ticket. The order context, the model's draft, the agent's override, and the reason for the override all live in three different places: Gorgias macros, the model's logs, a Slack thread. Next month, when a similar customer writes in, none of that interpretation is reachable. One way to solve this is a workspace like Dock that holds the rows the agent interprets around the ticket: `gorgias_ticket_id` as a pointer, then columns for intent, draft, override reason, LTV bucket, and outcome. Gorgias stays the system of record. Dock holds the interpretation. The [Dock for customer support overview](/blog/dock-for-customer-support) shows the table shape, and [Dock Shopify order pipelines](/blog/dock-shopify-order-pipelines) covers the order side. Identity matters here: agent actions need to attribute correctly, which the [agent identity lifecycle](/blog/agent-identity-lifecycle) post walks through. ## Why this matters Ecommerce returns hit 17.6% of online sales in 2023, roughly $247 billion ([NRF 2023 Consumer Returns report](https://nrf.com/research/2023-consumer-returns-retail-industry)). Every percentage point of resolution-without-escalation is margin. The teams that win are the ones whose model gets smarter at *their* policies, not just at English. Read the [pillar guide on AI customer support](/blog/how-to-run-customer-support-with-ai) for the full workflow. ## FAQ **Q: Does Gorgias have a native AI feature?** Yes. Gorgias Automate handles intent detection, auto-responses for common WISMO and order-status tickets, and order-aware macros. For custom logic, use the [Gorgias REST API](https://developers.gorgias.com/reference/introduction) to call ChatGPT, Claude, or your own model. **Q: Can I use ChatGPT inside Gorgias without Gorgias Automate?** Yes. Subscribe to the ticket-created webhook, send the payload to ChatGPT, write the draft back as a private note via the REST API. Many Shopify and BigCommerce stores run this exact pattern. **Q: Should AI auto-send replies in Gorgias?** For high-confidence WISMO with no refund implication, sometimes. For anything touching money, returns, or VIP customers, no. Auto-send fails badly on LTV-aware decisions. **Q: Where should the model's reasoning live?** Not in the ticket body. Gorgias tags are too flat. Use a separate workspace keyed by `gorgias_ticket_id` so the rationale, the override, and the outcome stay queryable next quarter.