Reguron Content Team · 7 min · 2026-09-15
AI customer support for e-commerce: implementation checklist
The teams that get this right do not flip a switch. They run a staged rollout where accuracy is measured before it is trusted. This is the checklist we use ourselves.
Before you connect anything
Write down your actual policies
Returns window, exceptions, shipping times by region, warranty terms. If these live only in a teammate's head, the agent cannot read them.
Pull your last 90 days of tickets
Categorise them. You need a real baseline, not an estimate, to know what "better" looks like later.
Decide your escalation list up front
Refunds, damage claims, chargebacks, anything legal — name the categories that stay with humans before you build anything.
Connect and configure
1. Connect read-only first
Order, fulfilment and product data. No write access yet.
2. Load your policy documents
The more complete this is, the less the agent has to guess.
3. Set tone and escalation rules
Match your actual support macros, not a generic persona.
Validate before you trust it
Run the agent in shadow mode against your resolved ticket history and compare its drafts to what your team actually sent. Do this for at least two weeks, not two days — volume on slow weeks hides failure modes that show up under load.
Track accuracy per topic, not as one blended number. "Order status" and "warranty dispute" should not be judged on the same curve.
Release gradually
Turn on auto-send for the highest-confidence topic first. Watch the complaint rate on exactly those conversations for a week before adding the next topic.
Resist releasing everything at once because the demo looked good. A demo is not a distribution of your actual ticket volume.
What to monitor after launch
Complaint rate on auto-sent replies
The number that tells you if you released too fast.
Escalation accuracy
Conversations that should have escalated and did not are worse than ones that escalated unnecessarily.
Median first-response time
The customer-facing number that justifies the whole project.
FAQ
How long should shadow mode run?
Long enough to cover your actual ticket mix — for most stores that is two to four weeks, not a few days.
What is the most common rollout mistake?
Releasing every topic at once instead of staging by category. A single bad week of refund-tagged conversations going out wrong will cost more trust than a slow rollout ever saves in time.
Does this apply beyond Shopify?
Yes — the sequence is the same regardless of platform. What differs is how much tracking and order detail each platform's API exposes.
Related
Want help building this checklist against your own data?
Bring a sample of your ticket history and we will map the staged rollout with you.
Request a demo