Ship a 48‑Hour Returns & Exchanges AI Agent for Shopify + WhatsApp (MCP + OpenTelemetry)

Editor checklist

  • Scan competitor trends and holiday returns data to validate demand.
  • Define success metrics, risks, and guardrails for a CX agent.
  • Design an MCP + OpenTelemetry reference architecture.
  • Implement a Shopify returns flow using returnProcess.
  • Ship a WhatsApp utility‑only conversation design that complies with 2025 rules.
  • Instrument evals and SLOs; plan rollout and handoffs.

Why a returns agent, and why now?

Holiday sales set records again, but returns balloon right after Cyber Week. Salesforce reported $1.2T in global online sales in 2024 with a 28% jump in return rates, projecting $133B in returned goods; AI and agents influenced 19% of online orders. That’s margin pressure—and opportunity to win loyalty with faster, clearer returns. citeturn6search0turn6news12

NRF/HAPPY Returns data pegs U.S. returns near $890B in 2024 and forecasts ~16% of 2025 retail sales being returned, with e‑commerce return rates around 19%. If your CX team dreads December tickets, you’re not alone. citeturn6search6turn6search3

Across the ecosystem, agents are professionalizing fast: Microsoft unveiled Agent 365 to govern fleets of bots, and investors just backed Wonderful with $100M to put AI agents at the front lines of support. Your returns flow is a perfect place to deploy a governed, measurable agent that creates value in days—not months. citeturn0news12turn0search1

What you’ll build in 48 hours

A WhatsApp‑native returns and exchanges agent that:

  • Verifies order identity and eligibility.
  • Offers refunds or exchanges based on policy and inventory.
  • Executes Shopify’s returnProcess mutation and sends confirmation updates.
  • Escalates gracefully to a human with full trace context.

We’ll keep it portable by using MCP for tool access and OpenTelemetry for tracing, so it slots into your control plane and avoids lock‑in. citeturn3news17turn3news18

Architecture at a glance

  • Agent host: Your preferred runtime (e.g., OpenAI AgentKit, internal agent service). Use MCP clients to reach tools. citeturn0search0
  • MCP servers: Shopify Admin GraphQL, order DB, policy service, shipping/RMA labels.
  • Messaging: WhatsApp Cloud API with utility templates (no U.S. marketing templates allowed as of Apr 1, 2025). citeturn5search3
  • Observability: OpenTelemetry Gen‑AI semantic conventions for spans, events, metrics. citeturn4search0turn4search2turn4search3

Day 1: Foundations (6–8 hours)

  1. Define success: Target first‑response under 3s, resolution under 5 minutes, and SLOs that matter (success rate, handoff rate, cost/ticket).
  2. WhatsApp setup: Create utility templates only (order lookup, return label, exchange confirmation). U.S. marketing templates are paused; utility templates sent inside an open customer service window are free under 2025 pricing updates—design your flow to get the customer to message first (via email/SMS prompts or order pages). citeturn5search6turn10view0
  3. Shopify access: Enable Admin GraphQL API 2025‑07 and test returnProcess for refunds and exchanges; migrate away from deprecated returnRefund. citeturn7search3turn7search5
  4. Policy as data: Encode return windows, exceptions (final sale), fraud flags, and exchange logic as a JSON policy that the agent reads.
  5. Telemetry: Instrument spans: intent_detectorder_lookupeligibility_evalreturn_processnotify_customer. Use gen_ai.* attributes for inputs/outputs and gen_ai.client.token.usage metrics. citeturn4search0turn4search3

Day 2: Ship the flow (8–10 hours)

  1. Intent + verification (WhatsApp): ask for one identifier (email or phone) and last 4 digits of order number. Minimize PII exposure; mask inputs in logs.
  2. Eligibility + options: Use order data and policy to propose refund or exchange with clear deltas (restocking fee, shipping). For apparel, default to exchange to reduce loss.
  3. Execute in Shopify: Call returnProcess with selected line items; include issueRefund details or create exchange line items. Handle and log ReturnUserError. citeturn7search3
  4. Notify (WhatsApp utility template): send confirmation and RMA/label. Keep copy transactional to remain compliant. citeturn5search2
  5. Observability + handoff: If confidence or eligibility < 0.7, route to human with the trace URL; record handoff_reason.
  6. Evals: Create a 20‑case suite (damaged item, wrong size, window expired, high‑value electronics) and run nightly. If using AgentKit, leverage its “Evals for Agents” primitives. citeturn0search0

Conversation design that saves money

  • Open the 24‑hour window for free utility replies: Nudge customers to DM you from order pages/emails to initiate. Then your utility templates (status, labels) are free within that window under new per‑message pricing. citeturn10view0
  • Avoid U.S. marketing templates: As of April 1, 2025, they won’t deliver to +1 numbers. Keep returns flows strictly transactional. citeturn5search3

Sample: Shopify returnProcess (refund)

{
  "returnId": "gid://shopify/Return/945000961",
  "returnLineItems": [{"id": "gid://shopify/ReturnLineItem/677614678", "quantity": 1}],
  "financialTransfer": {
    "issueRefund": {
      "orderTransactions": [{
        "transactionAmount": {"amount": 25.99, "currencyCode": "USD"},
        "parentId": "gid://shopify/OrderTransaction/239853124"
      }]
    }
  },
  "notifyCustomer": true
}

See Shopify’s docs for full payloads, errors, and exchange flows. citeturn7search3

Governance and safety

  • Control plane: Register the agent, tools, and policies; enforce least‑privilege tool permissions; monitor for injection/tool abuse. If you’re new to this, start with our 7‑day control plane.
  • Red‑team before scale: Simulate prompt injection, return‑policy bypass, and PII exposure; we published a 48‑hour checklist for support agents. citeturn0news13 Guide
  • Telemetry: Adopt the Gen‑AI semantic conventions so traces are portable across vendors and correlate cleanly with CX metrics. citeturn4search0

Measuring impact (starter SLOs)

  • Return/exchange resolution rate ≥ 90% without human handoff.
  • Median TTFT ≤ 3s; TPOT (time to process outcome) ≤ 4m.
  • Cost per ticket down 25–40% with smart routing; see our FinOps playbook.

What’s next

Add upsell logic to exchanges outside the U.S. (where allowed), connect store credit issuance, and expand to returns kiosks or QR codes. Keep an eye on Windows/enterprise MCP support and governance products like Agent 365 as you scale your agent fleet. citeturn3news18turn0news12

Internal links


CTA: Want this done for you? HireNinja can deploy this returns agent (MCP + OpenTelemetry) for your store in 48 hours—governed, observable, and ready for holiday scale. Book a consult.

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