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Catalog structure

Define the fields your products need Validation runs on save

Twelve attribute types, rules that live on the field itself, and groups that keep the product editor in the same order every time.

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  • 12 attribute types
  • Validation on save
  • Groups reused across products

Key features

  • Pick a type per field

    Text, text area, number, decimal, date, date-time, select, multi-select, boolean, colour, image and file, each with its own settings.

  • Put the rule on the field

    Required, length limits, number ranges and pattern matching live on the attribute, so every product is checked the same way.

  • Group the fields that belong together

    Bundle dimensions or SEO fields into a group and assign the whole set to a product type in one step.

Attribute groups

The product editor, in your order

A group is a named set of attributes. Assign the group to a product type and every product of that type shows the same fields in the same place.

Each row is a group; the attributes inside it are the fields the editor shows together. Change the group and every product using it follows.

How it works

From an empty model to filled-in products

Three steps, and the last one is the only one you repeat.

  1. 01

    Create the attributes

    Name the field, pick its type, set the validation rules and help text, and drop it into a group with the fields it belongs with.

    A field that behaves the same everywhere it is used.

  2. 02

    Assign them to product types

    Attach a group to a product type, a category or an individual product, so similar products always ask for the same information.

  3. 03

    Fill them in, by hand or by AI

    Type the values, import them, or let an AI enrichment run write them per attribute. Validation runs on save and flags what is missing or malformed.

    Missing and malformed values surface in WISEPIM, not on a channel.

Types

One type per kind of value

Six of the twelve; date-time, colour, image and file cover the rest.

  • Text

    Single-line values: product name, SKU, brand. Character limits and pattern matching apply here.

  • Number and decimal

    Prices, weights, dimensions and quantities, with a minimum, a maximum and decimal precision.

  • Select

    One value from a list you define once, such as colour, material or status, so the same word is never spelled two ways.

  • Multi-select

    Several values from that list: certifications, compatible accessories, target audiences.

  • Rich text

    Formatted content for descriptions, care instructions and usage notes, kept as markup.

  • Date and boolean

    Release dates, end-of-life dates, and yes/no flags such as hazardous or free shipping.

Create an attribute

A new field takes one dialog

Name it, pick the type, set the rules, and it is available to every product type you attach it to.

  • The type decides the input

    A select gets a value list, a number gets a range and a unit, rich text gets an editor. The product editor renders what the type needs.

  • Rules are set here, not per product

    Mark it required, cap its length, bound its range or give it a pattern, and every product that carries the field is checked against it.

  • AI settings live on the attribute

    Add an instruction, an output format and an example value, and enrichment runs write this field the way you described it.

The create dialog: type on the left, its own validation options below, and the fields change with the type you pick.

In practice

Where a strict data model pays off

Three catalogs where the field list is the difference between a listing that publishes and one that bounces.

  • One catalog, very different products

    Electronics need voltage and wattage, apparel needs size and fabric, food needs ingredients and allergens. Each product type carries its own group.

    Result: no product asks for fields it will never have.

  • Marketplace requirements

    Amazon, bol and Google Shopping each demand their own fields. Model them as attributes and a missing one shows up before the export runs.

    Result: rejected listings become a filter in WISEPIM.

  • Supplier data that arrives messy

    Validation rules and select lists normalize what suppliers send: one unit, one spelling, one format per field.

    Result: the same value from three suppliers ends up written one way.

FAQs

Attribute questions, answered

Types, validation, groups and per-attribute AI settings, explained.

Still have questions?

Can't find the answer you're looking for? Please get in touch with our team.

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WISEPIM supports 12 attribute types: Text, Text Area, Number, Decimal, Date, DateTime, Select (dropdown), Multi-Select, Boolean (yes/no), Color, Image, and File. Each type has its own validation options and display settings.

The AI Data Architect looks at your product catalog and suggests attributes you might be missing, recommends types based on your data patterns, and can auto-generate attribute values from existing product information. It proposes the structure; you decide what to create.

Yes. Each attribute can have validation rules including text length limits, number ranges, pattern matching, and required field enforcement. Validation runs when products are created or updated, so invalid data is caught at the point of entry rather than at export.

Attribute groups let you organize related attributes together, for example Physical Dimensions (width, height, depth, weight) or SEO Fields (meta title, meta description, keywords). Groups decide how the product editor is laid out and let you assign a whole set of fields to a product type at once.

Yes. Each attribute has AI enrichment settings that control how AI generates values for it. You can add instructions, set the expected output format, provide example values, and choose whether the attribute is included in bulk AI enrichment runs.

Next step

Set the fields onceEvery product follows them

Set up your attributes on your own catalog for free, or bring one product type to a call and we model it with you.

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The full attributes guide

All 12 types, the validation options per type, AI enrichment settings, and how attribute groups are organized.

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