Which teams should take this?

Everyone whose work touches the store: operations and marketplace managers, catalog and content teams, customer service leads, and marketing or CRM staff. We group sessions by role, so a content team practices on listings while support practices on returns correspondence.

Do we need technical people for this?

The training assumes no technical background at all, building directly on the listings, tickets, and campaigns your team already handles.

How long is it, and can it be split?

Two days, roughly 13 hours of instruction, onsite or as live online sessions. Most commerce teams split it into half-day blocks so daily operations and campaign work continue uninterrupted.

Can the syllabus be customized to our platform and marketplaces?

Sample listings and campaign briefs from your team set the starting cases. A short discovery call before the training pins down the channels and depth to build around.

What is the price based on?

Four things move the number: group size, delivery format, customization depth, and location. We ask about group size and delivery format first, since those set the baseline. Customization depth is how much of the syllabus gets rebuilt around your actual catalog and ticket volume. Send a short brief on your team and where you're based, and a price follows from there.

What happens once the training is over?

The deliverables stay yours: prompt library, listing and reply templates, a 90-day rollout plan. Questions after the session go to us directly. Ahead of a big campaign, plenty of teams come back for a refresher.

What are we trained on?

ChatGPT, Microsoft Copilot, Gemini: that covers most of it, since that's what commerce teams already have licensed. Got a platform with built-in AI features, or an approved enterprise tool instead? We design the exercises around whatever you use.

Is our customer or order data used during the training?

No. The order histories and product feeds are synthetic, and where one is modelled on a real basket it is fully anonymized before anyone sees it. A whole module goes to the question of which tools may ever see customer and order data, and which never may.

AI Training · E-commerce

AI Training for E-commerce

Product descriptions, marketplace listings, support replies, campaign copy — an online store's day runs on text, and at a volume no content team outwrites by hand.

This training turns that workload into daily practice: safe, reviewable, and something your team can actually keep up with.

modules: 6
hours: 13

Some of the 500+ brands we've worked with

Selected brands we’ve worked with across industries.

See all references

A product feed with six thousand products needs full copy for every one of them, then again for Amazon, then again for every other marketplace with its own title rules and attribute schema. Support inherits the other half of the load: order status, returns, sizing, and shipping account for most ticket volume, the same handful of questions on repeat. Get either one wrong and the cost is immediate: an invented spec in a live listing, a refund promise a policy doesn't cover, a customer's address pasted into a consumer chatbot.

Over two days, operations, content, support, and marketing teams build a review-before-publish habit around ChatGPT, Copilot, and Gemini, with customer data staying inside GDPR and KVKK. That's hours back for assortment and pricing instead of rewrites. The full training catalogue covers dozens of other industries.

A product feed never stops growing

Every product needs a title, description, and attributes per channel and per language — a backlog that never clears by hand.

Support tickets ask the same five questions

"Where's my order?" tops the queue every time — a model drafts the on-policy reply so agents keep the cases that need judgment.

Stop writing the same listing five times

Your storefront and every marketplace want a different title format and schema — AI turns one version into all of them.

What happens when Black Friday compresses a quarter of copy into three weeks?

A season's worth of campaign copy lands in three weeks every peak — teams drafting variants with AI test more and still ship on time.

The browser already runs half of this

Most of this already sits in the browser or seller dashboard, paid for and rarely used well — reviewing before it goes live is the missing habit.

01
Where language models help on a live storefront
120 minBeginner
What large language models get right, and where they invent a spec that was never true. This module gives operations and content teams, support included, the same starting picture before anyone touches a live listing.
What a model gets right on product text, and where it invents a spec
Hallucination in product data: from an invented size to a false spec or claim
Where AI already sits in your office suite and seller dashboard
What to delegate, and what stays a human call
One workflow before peak season
02
A prompt habit for commerce texts
120 minBeginner
Role, context, task, format, a check: the same five-part structure applied to listings and support replies, campaign emails included, that your store already produces.
A reusable prompt template built for commerce text
Feeding the model product data and brand voice without losing control of either
Rewriting a draft twice
Keeping one tone across a listing, a support reply, and a campaign email
A prompt folder your team can find again next quarter
03
Turning product data into catalog-ready copy
180 minIntermediate
Titles, descriptions, attributes, and category copy move from structured data to shelf-ready text in this module. Every flow ends with a review-before-publish check. An invented spec never reaches a live listing.
Drafting titles and descriptions straight from structured product data
Extracting and normalizing attributes from a supplier's raw feed
A channel-specific variant for your storefront and for each marketplace
Search-friendly copy that still sounds like the brand wrote it
Translating and localizing catalog content without losing accuracy
Catching an invented spec
04
Support replies and lifecycle email
150 minIntermediate
Ticket replies, returns correspondence, review responses, and lifecycle emails get rebuilt as AI-assisted drafts here, grounded in your actual return and shipping policy. Every flow keeps a clear line for the conversations that need a human.
Drafting ticket replies grounded in your return and shipping policy
Returns and refund correspondence that holds up under volume
Responding to reviews at every rating, praise through complaint
Mining tickets and reviews for a genuine product or content fix
Drafting a segmented campaign or lifecycle email from one brief
Where a ticket stops being a draft and starts needing a human
05
Order data and marketplace compliance
120 minIntermediate
GDPR and KVKK translated into commerce practice: what may go into a prompt, and what never does. The same module keeps AI-generated listings inside each marketplace's content rules.
What counts as personal data in an order, a ticket, or a CRM export
Keeping a customer's name and address out of a prompt entirely
A consumer AI account and an enterprise one don't behave the same way
Marketplace content policy and what an AI-generated listing must still respect
Where an order or invoice export is safe to paste into a prompt
One AI policy
06
Turning a pilot into a habit that sticks
90 minAdvanced
From a few trained people to a store that uses this daily. Pilots prove it first, then a metric library (time per listing, first-response time, content throughput) shows whether it's actually working.
Choosing a pilot workflow with a measurable time saved
A champions model for content and support, with marketing represented
A metric that ties adoption to time per listing or first-response time
What resistance looks like across three different teams, and what to say
A 90-day plan timed around your next campaign calendar

What you will learn

A listing that ships clean
Write one prompt your team reuses on listings and replies. Adapt it for campaigns
Produce a channel-specific variant for your storefront, then for each marketplace
Reply to a support ticket or review without drifting from your return policy
Keep a customer's address out of every prompt, GDPR and KVKK included
Catch an invented spec early
Move a single pilot into a rollout your leadership signs off on

Who should attend

E-commerce and marketplace operations managers
Catalog and content teams, product information included
Customer service and support team leads
Digital marketing and CRM teams, performance marketing included
Founders and general managers of online retail brands
Marketplace sellers scaling beyond a single channel

Store operations frame two days, usually split into half-day sessions so work never stops. Onsite and live-online formats cover the same syllabus.

Format: Onsite or live online
Duration: 2 days (about 13 hours, can be split into half-day sessions)
Group size: Up to 20 participants per group
Language: English or Turkish
Materials: Prompt library, listing and reply templates, and exercise workbook
Certificate: Certificate of completion

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What you sell and where you sell it changes the syllabus more than anything else. Give us that and name who you want in the room. We'll come back with a schedule and a price.

Two colleagues updating a workflow board and checking a process change

Which teams should take this?
Everyone whose work touches the store: operations and marketplace managers, catalog and content teams, customer service leads, and marketing or CRM staff. We group sessions by role, so a content team practices on listings while support practices on returns correspondence.
Do we need technical people for this?
The training assumes no technical background at all, building directly on the listings, tickets, and campaigns your team already handles.
How long is it, and can it be split?
Two days, roughly 13 hours of instruction, onsite or as live online sessions. Most commerce teams split it into half-day blocks so daily operations and campaign work continue uninterrupted.
Can the syllabus be customized to our platform and marketplaces?
Sample listings and campaign briefs from your team set the starting cases. A short discovery call before the training pins down the channels and depth to build around.
What is the price based on?
Four things move the number: group size, delivery format, customization depth, and location. We ask about group size and delivery format first, since those set the baseline. Customization depth is how much of the syllabus gets rebuilt around your actual catalog and ticket volume. Send a short brief on your team and where you're based, and a price follows from there.
What happens once the training is over?
The deliverables stay yours: prompt library, listing and reply templates, a 90-day rollout plan. Questions after the session go to us directly. Ahead of a big campaign, plenty of teams come back for a refresher.
What are we trained on?
ChatGPT, Microsoft Copilot, Gemini: that covers most of it, since that's what commerce teams already have licensed. Got a platform with built-in AI features, or an approved enterprise tool instead? We design the exercises around whatever you use.
Is our customer or order data used during the training?
No. The order histories and product feeds are synthetic, and where one is modelled on a real basket it is fully anonymized before anyone sees it. A whole module goes to the question of which tools may ever see customer and order data, and which never may.

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AI Training for E-commerce