About Us

Returns triage reduces refund abuse

A marketplace used rule‑based and AI triage for returns and fraud, expediting legit requests and reducing abuse.

Contents

  1. Objectives & KPIs
  2. Solution architecture
  3. Implementation
  4. Results
  5. Governance & security
  6. Lessons learned
Request a similar project

Objectives & KPIs

  • Automate initial triage for returns and fraud signals.
  • Reduce manual review and accelerate legit refunds.
  • Maintain clear audit trail and thresholds.

−35%

Refund abuse

−40%

Manual review load

+20%

Legit case speed

24/7

Automated triage

Solution architecture

Flows score risk, request evidence, approve simple cases, and escalate ambiguous ones to an analyst queue.

Order/Returns → Risk signals
Rules + LLM → Score & decide
Approve/Request more info/Escalate
Audit → Case log & metrics

We applied prompt guardrails, PII filtering, and rate limits. Clear escalation and analytics were embedded from day one.

Key integrations

  • WooCommerce/Shopify
  • Payment provider APIs
  • n8n/Zapier
  • BI dashboard

Channels

  • Customer portal
  • Email forms
  • Analyst console

Implementation

1) Discover

Goals, KPIs, data sources; success criteria and analytics events.

4) Launch

Pilot, QA, calibration; gradual rollout with dashboards.

2) Design

Flows, prompts & guardrails, UX, privacy filters, integration plan.

5) Handover

Docs, runbooks, enablement, and iteration roadmap.

3) Build

Connect data, implement logic, tag analytics, harden security.

Results & evidence

  • Refund abuse: −35% YoY
  • Manual review: −40% load
  • Cycle time: +20% faster for legit cases
  • Customer trust improved:

Significance verified via standard tests; GA4/BI dashboards tracked lift and seasonality.

Testimonial

“The triage freed our team to focus on real edge cases.”
— Client stakeholder

Governance & security

  • Least‑privilege access and environment isolation.
  • PII filters; no training on raw logs.
  • Transparent citations or decision trails.
  • Audit trail for changes and rollbacks.

Runbooks

Operational SOPs for updates, incident response, and periodic reviews.

Lessons learned

  • Tune thresholds gradually
  • Keep transparent customer comms
  • Review rules monthly

Next steps

  • Add device fingerprinting
  • Expand to chargebacks
  • Link with support bot

Want similar results?

We’ll tailor a sprint to your stack and seasonality, with clear KPIs and guardrails.

Published on

Category(s)E‑commerce & Retail

Related Posts ...