Guide · AI for eCommerce
Claude Code for eCommerce
Claude Code is an AI assistant that works on your files and data in the terminal: it reads your catalog, transforms CSVs, generates feeds, makes bulk changes and writes small automations. You do not need to be a developer, you need to say clearly what you want. This guide shows how to put it to work in everyday store operations.
What it is
Claude Code runs in the terminal inside a folder you choose and sees the files there: catalog exports, price lists, feeds, listing dumps. You ask it in plain language (“split variants into separate rows and validate the EAN codes”) and it does the work on the files and shows you what it changed. That turns AI from a chat you paste into a tool that actually processes your data.
Before you start
- Work on a COPY of your data, not the original. Claude Code changes files on disk.
- Keep the data in one folder and run it there so it has context.
- Do not paste secrets (API keys, passwords) into files you share.
Five ecommerce uses
Cleaning and transforming the catalog (CSV)
Split variants into rows, standardise units and colours, fix encoding and quotes, generate slugs, validate EAN/GTIN codes, detect duplicates and gaps. Ask for a report of what changed and where the gaps are that need a human.
Generating and validating feeds
Map catalog columns to a Google Merchant or marketplace feed, fill required fields, check types and values, and flag listings that would be rejected before you upload them.
Bulk product-data edits
Replace phrases across hundreds of descriptions, reprice by a rule, assign categories and tags, add GPSR fields or the responsible party. Changes across many files at once, with a diff to review before saving.
Analysing listing errors and logs
Paste a marketplace rejection export or an error log. Claude Code groups the causes, points out the recurring problems and proposes concrete fixes, instead of clicking through listings one by one.
Small automations
Write a simple script that repeats a routine: a weekly price update from a supplier file, a report, preparing an image batch for marketplace dimensions. Set once, run whenever you need it.
How to brief it well
- Be specific: give an example of the input and the expected output (one “before” and “after” row).
- Break a big task into steps and check the result after each one before moving on.
- Ask for a report of changes and for anything it could not resolve automatically to be flagged.
- Always review the diff before saving and keep a copy of the input data.
We run this in production, inside your platform
In the AI Automation stage of the BEAM framework we turn workflows like these into durable, supervised processes inside your store, not manual runs in a terminal. If you want that in-house, let us talk.
Let us talk →