Companion is now on Google Play!GET IT ON GOOGLE PLAY
İçerik Yöneticisi logo

İçerik Yöneticisi

Digital Product Studio

Example scenarioSales & E-Commerce

E-Commerce Content and Operations Automation

A catalogue assistant that drafts product descriptions, key features and category suggestions from your product data, finds missing and inconsistent records, and puts every piece of content in front of your team before it goes live.

E-Commerce Content and Operations Automation

The problem

The catalogue keeps growing; the product pages fall behind

New products go live with a supplier's short spec sheet or no description at all. While descriptions are written one by one, some products stay with missing attributes and others in the wrong category, and colour, size and material are written differently from one product to the next. As the range grows the content team can't keep up, and customers can't find the information they're looking for.

  • Products go live with missing or one-line descriptions
  • Attributes and sizes are inconsistent across products
  • Category and filter assignments are wrong
  • The content team can't keep pace with new products

The solution

Ready-to-edit drafts from product data, with human approval before publishing

From each product's own data — specifications, materials, dimensions, usage — the assistant drafts a description that follows your brand's writing rules, plus key features and a category suggestion. It doesn't invent attributes that aren't in the data; it flags what's missing. It also scans the catalogue for missing attributes, inconsistent units and likely miscategorised products. No draft goes live until your content team approves it.

Possible benefits

  • New products don't sit waiting for a description
  • Product pages follow one consistent writing standard
  • Missing and inconsistent catalogue data becomes visible
  • Your content team spends its time editing and checking, not writing from scratch

How it works

  1. 01Your team

    Writing rules are agreed

    Brand voice, description length, phrases to avoid and mandatory information.

  2. 02System

    Product data is pulled in

    From your e-commerce platform or product spreadsheet, with each product's own attributes.

  3. 03AI

    Drafts and catalogue checks are prepared

    Description, key features, category suggestion, plus a list of missing and inconsistent fields.

  4. 04Your team

    The content team edits and approves

    Every text that will go live is read by a person.

  5. 05System

    Approved content is sent to the shop

    Only the approved fields are updated.

Example: an online home textiles shop

At the start of the season the shop imports hundreds of new duvet sets and towels from a supplier list; most have only a product code, size and fabric. For each product the assistant drafts a short description and key features based on fabric, size and care details. Products without care instructions go on a "missing information" list, and it points out that some sizes are in centimetres and others in inches. The content manager edits the drafts and approves them in batches.

What it needs

Information required

  • Structured product data: attributes, materials, dimensions, variants
  • Your brand writing rules and a few good example product pages
  • Your category tree and filter structure

Systems to connect

  • Your e-commerce platform: Shopify, WooCommerce or your own — through its admin API with the required access scopes (connected during setup)
  • A product information management (PIM) system or product spreadsheet
  • Optional: draft translations for a second language such as English

Where a person approves

No description, price or stock information goes live without approval. The assistant never touches price or stock fields. Any health, safety or environmental claim is checked separately.

Security and privacy

  • Shop access is limited to content fields, with the narrowest permissions needed
  • Changes are versioned and can be rolled back
  • No customer data is used in this scenario
  • AI calls are made server-side

What it does not do

  • It can't know attributes that aren't in the product data; weak data means weak descriptions
  • Descriptions of similar products can end up similar; originality needs each product's own data and an editor's touch
  • It does not promise any search ranking; Google treats mass-produced pages that add no value for visitors as spam
  • It does not create images; product photography is a separate job

How many products in your catalogue are waiting for a proper description?

Let's start with a few product categories and set up your writing rules and approval flow together.

This is an example scenario, not a completed client project. Setup and results depend on your business data and the systems you use.