AI Training · E-commerce

AI Training for E-commerce

Product descriptions, marketplace listings, support replies, and campaign copy: an online store's day runs on text at a volume no content team outwrites by hand. This training turns that workload into safe, reviewable daily practice.

modules: 6
hours: 13

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 draft catalog copy and customer replies with ChatGPT, Microsoft Copilot, and Gemini. They build a review-before-publish habit into every workflow while keeping customer data inside GDPR and KVKK. The full training catalogue covers dozens of other industries. This program gives teams hours back for assortment and pricing. Growth gets more attention too because less time goes to rewrites.

A product feed never stops growing

Every product needs a title, a description, and attributes, often once per channel and once per language, and a backlog like that never clears by hand or on its own.

Support tickets ask the same five questions

Order status, returns, sizing, shipping: a handful of patterns account for most support volume. A language model drafts an accurate, on-policy reply for exactly this kind of ticket. That leaves an agent the case that actually needs judgment.

#1how often "Where's my order?" tops the support queue, ahead of every other question

Stop writing the same listing five times

Your own storefront and every marketplace you sell on, Amazon included, want a different title format, a different attribute schema, and a different content policy. AI turns one written version into all of them without starting from zero.

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

Ads, emails, banners, landing pages: a season's worth of campaign copy lands in a few weeks every peak. Teams that draft variants with AI test more and ship on time. Teams that don't pick between speed and accuracy.

The browser already runs half of this

Most of what this training covers already sits in the browser, the office suite, or the seller dashboard, paid for and rarely used well. A content lead can draft a listing today. Whether someone reviews it before it goes live is a habit nobody has built yet.

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

Zeo started in 2011 and now works out of San Francisco, Istanbul, Ankara, and Lisbon. We run Copilot Academy and organize Digitalzone, an international digital marketing conference. This program draws on the 10+ years of consulting and training work behind that, applied to corporate AI adoption.

2011founded in Istanbul
10+years of consulting and training experience
3offices: San Francisco, Istanbul, Ankara, Lisbon

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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.

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AI Training for E-commerce