Attribute

An Attribute is a product characteristic (a parameter) used to describe and compare products in a consistent way.
Examples: Weight, Number of USB ports, Nominal power, Operating pressure, Material grade.

In Actualog, products are described as:

Category (class) + a set of Attribute values

That structure is the foundation for data quality, filtering, multilingual content, and catalog publishing.

Where attributes are used

Attributes power the most important workflows in Actualog:

  • Product Profile 360° — structured specifications instead of “text everywhere”
  • Validation and completeness — required fields, correct types, consistent formats and units
  • Comparison and search — technical selection, filtering, matching
  • Catalogs and marketplace publishing — products become discoverable and comparable
  • Naming automation — attribute-based product name templates (governed and predictable)
  • Integrations — cleaner exchange with ERP/MDM/eProcurement systems

Attribute library vs contextual attribute

Actualog supports two practical scopes:

  • Library Attribute
    A reusable attribute stored in a shared dictionary. It can be added to many categories.

  • Contextual (Category-specific) Attribute
    A specialized attribute created for a single category (or a narrow domain) when reuse is not appropriate.

Best practice: prefer Library Attributes for anything that can be standardized across multiple categories (units, definitions, controlled lists). Use contextual attributes only when the meaning is truly category-specific.

Attributes and categories (templates and inheritance)

Attributes are not added to products directly. They are assigned to Category Templates:

  • Products in the same category share the same attribute template
  • Subcategories inherit attributes from parent categories
  • Subcategories can extend the template with additional attributes (recommended when the subcategory adds meaning)

Attribute definition (what an attribute contains)

Each attribute is defined by:

  • Name and Description (clear meaning, not marketing text)
  • Area (for governance and UI grouping):
    Technical / Functional / Logistics / Marketing
  • Importance level: High / Medium / Low
    (helps teams focus on what really matters for selection and procurement)
  • Optional Synonyms / labels (multilingual naming and searchability)
  • Optional Controlled values (for consistent selection and translation)
  • Optional Measure + Unit rules (for numeric or enumerated measured values)

Mandatory attributes and product name templates

An attribute can be marked as Mandatory for a category.

  • All products in that category must have values for mandatory attributes
  • Mandatory attributes are the safest foundation for product name templates because they guarantee the name can be generated consistently

Best practice: keep the mandatory set small and meaningful (procurement/engineering-critical), and use importance levels to guide completeness beyond the minimum.

Attribute types in Actualog

Actualog supports four attribute types:

  1. Numeric
  2. Text
  3. Yes/No
  4. List of values

1) Numeric attribute

Numeric attributes are used for measurable specifications (e.g., power, pressure, length).

You can configure:

  • Precision: number of digits and decimals
  • Percentage flag (value interpreted as %)
  • Allowed range: minimum and maximum values
  • Value model:
    • single value
    • multiple values
    • range
    • multiple ranges
  • Permissible deviation (tolerance):
    • absolute value, or
    • percentage (%)

Use numeric attributes when the value must be comparable and filterable (engineering and procurement use cases).

2) Text attribute

Text attributes are used for identifiers, notes, or descriptions that are not safely numeric or enumerated.

You can configure:

  • Minimum characters
  • Maximum characters

Best practice: avoid using text fields for data that should be standardized (e.g., materials, standards, connection types). Use lists instead.

3) Yes/No attribute

Yes/No attributes are used for binary characteristics (e.g., “Explosion-proof”, “Food-grade”, “RoHS compliant”).

You can configure:

  • localized labels for positive and negative values (per language)

This keeps UI consistent and makes multilingual catalogs cleaner.

4) List attribute (controlled values)

List attributes are used when values must come from a controlled set (e.g., material type, standard, connection type).

You can configure:

  • single-value or multi-value
  • value list in multiple languages

Best practice: list attributes are the fastest way to improve data quality, reduce duplicates, and make filtering reliable.

Measures and units of measurement

For Numeric attributes (and measured enumerations where applicable), you can enable Unit of measurement:

  • turn on the unit flag
  • select a Measure (what is being measured: Length, Pressure, Power, etc.)
  • select the default Unit (mm, bar, kW, …)

This ensures values stay meaningful and comparable across:

  • different suppliers and markets
  • imports and integrations
  • catalogs and technical filtering

Governance and quality (how attributes stay trustworthy)

Actualog uses attribute definitions as a governance mechanism:

  • the same rules apply in the UI, imports, and integrations
  • structured types prevent “anything goes” data entry
  • controlled lists and units reduce ambiguity
  • attribute definitions can be curated by experts and reused across categories

AI-assisted future (how attributes evolve and scale)

Actualog’s roadmap treats attributes as the backbone of AI-ready product data:

  • suggesting missing attribute values based on documents and patterns
  • detecting inconsistent units, suspicious ranges, and duplicates
  • recommending category templates and controlled value lists
  • accelerating multilingual labels and terminology normalization

AI works best when attributes are well-defined, typed, and governed—so the platform is designed to keep attributes structured first, then use AI to scale enrichment safely.