Product Attribute Schema Design Best Practices
What is Product Attribute Schema?
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Attribute Schema Definition:
For a given product category, a list of attributes, attribute values, and related metadata. The structure of a category that houses attributes and captures attribute values for items. The schema establishes the principle attributes that define elements of a hierarchical category and capture the values for these attributes. Two schemata may share many attributes and their related metadata if they belong to sibling categories. Every attribute within a schema contains metadata that define the attribute, assign a data type, assign a unit of measure for numerical data types, determine whether the attribute may capture multiple values, etc. Typically, a hierarchy will contain multiple schemata for each terminal category and potentially some schemata for non-terminal categories. The term schema may refer to all of the schemata tied to terminal categories. Attribute Schema Full Definition.
Why is Product Attribute Schema Design Important?
Product attribute schemas are the most granular elements of a product taxonomy. Schema provides a framework for efficient product data management and determines what information will be captured and maintained for each product. Establishing the metadata parameters for a schema project typically requires data modeling to align expectations and define terms across various stakeholders.
Schemas are managed at the category level and serve to describe and differentiate products within a category. Schemas are rarely displayed in totality to a customer in an online store or other front end application.
Parts of schemas drive specific interfaces such as:
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Guided navigation filters
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Product detail pages
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Search functionality
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Administrative functions
How is Product Attribute Schema Used?
Product attribute schemas may drive elements of the following applications:
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eCommerce Platform / Online Store
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PIM or MDM Item Onboarding
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Mobile Applications
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Data Governance
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Data Fill Targeting
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Reporting and Analytics
Systems that require product schema design include:
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PIMs (product information management systems)
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MDMs (master data management systems)
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CMS (content management systems)
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eCommerce Platforms
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Recommendation engines
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Product data feeds
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ERPs (enterprise resource planning systems)
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CPQs (configure price quote systems)
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PLM (product lifecycle management)
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Business Intelligence Tools (BI Tools)
About Product Attribute Schema Metadata
Attribute metadata gives functionality to the schema and determines what it can do and how it will be managed. Metadata is customized to the needs of a given project or software.
Types of Product Schema Metadata:
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Attribute Name
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Attribute Definition
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Display Type
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Data Type
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Units of Measure
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List of Values
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Data Governance Flags
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Attribute Groups
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Inheritance Rules
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Navigation Sequence
Best Practices and Guidelines for Product Attribute Schema Design
Building strong schemas requires weighing and resolving conflicting priorities. Here are some key concepts to keep in mind during product attribute schema design:
1. Product Schema Does Not Equal Data Sheets
A good product schema is not a copy of a product data sheet or technical product specifications from a catalog. A data sheet provides details about a single product, whereas schema allows comparison and differentiation across products. A data sheet focuses on the details, whereas schema focuses on how those details are captured, presented, and interpreted. A data sheet is typically “published” as a pdf.
2. Product Attribute Label and Value Transformation
Untangle messy attributes by separating compound attributes into individual attributes which represent a single aspect of the product whenever possible. In the example below, the compound attribute <Materials> has an attribute value of “Steel shell, butyl diaphragm”.
Consider separating into 2 attributes:
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Attribute <Shell Material> with attribute value of “Steel”
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Attribute <Diaphragm Material> with attribute value of “Butyl”
3. Establish Attribute Consistency
Aim for as much consistency as possible in labeling and defining attributes throughout the taxonomy, while avoiding forcing information that doesn’t fit the products. Ideally, attributes with the same name capture the same concept, regardless of the associated categories. Establish a list of attribute style guidelines to govern attribute management.
4. Develop Appropriate Attribute Labels
Attribute labels should capture distinct characteristics (nouns) and be worded such that all attribute values make sense in the context of the label. In general, attribute labels should be 25 characters or shorter.
If a concept can be conveyed with the same clarity using a shorter version of a word, use the shorter version to keep the length of the label manageable.
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<Lock Type> over <Locking Type>
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<Mount Style> over <Mounting Style>
5. Sequencing Navigation Attributes
Navigation attributes (aka “left navigation” or "guided navigation" attributes) help users filter a large number of products to arrive at a smaller group or single SKU. Navigation sequencing should prioritize important attributes to help users differentiate products quickly using a “greatest good for the greatest number” guiding principle. Attributes with long LOVs require more time from users and can be difficult to use. Attributes for which the majority of items have the same value are typically less useful for filtering. When available, leverage clickstream data to re-evaluate sequencing over time.
6. Companion Attributes
If two or more attributes refer to complementary characteristics, they should be named using similar formatting to clearly relate the attributes while also making the distinction clear. Companion attributes should be sequenced consecutively where possible.
Companion attributes typically reference relationships such as:
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Front/Rear
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Left/Right
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Minimum/Maximum
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Top/Bottom
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Outer/Inner
7. Schema Depth
Unlike taxonomy, schema depth can be highly variable and depends on item counts and user needs. At one extreme, a large distributor aiming to be the industry leader may build exhaustive lists of all known attributes based on market research. On the other hand, a new website may design a thin navigation schema of 3 - 5 attributes to meet a go-live date. Most projects will fall between these two extremes, balancing both completeness and pace. The best schemas are not always the most exhaustive.
IDA Solutions for Product Attribute Schema Design
Industrial Data Associates has 9 years’ experience developing complex product attribute schema for industrial product manufacturers, online stores and eCommerce applications. Staffed with highly technical taxonomists and product data analysts, we employ academic and strategic taxonomy principles to organize, categorize and classify product data.
Past product schema design projects include:
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Designing eCommerce product schema for use in guided navigation for product search and select.
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Designing product schema for a master product hierarchy syndicating attributes to multiple downstream channels.
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Designing product schemas to facilitate new item onboarding for over 1 million SKUs being added to a PIM.
Contact IDA to learn about our product schema design services and solutions.