All Posts

How Product Attribute Schema Design Works As A Competitive Advantage

Organizations compete on their data.  Every interaction with your organization is facilitated by data and content. Being able to present the appropriate information to customers and prospects depends on how well that data is designed and managed. Product attributes and the taxonomy that organizes products on a B2B or B2C website will determine whether your products are visible and findable.  If your customer can’t find it, they can’t buy it, and you will not be able to compete in the market. 

What is attribute schema design?

An attribute schema describes the details and characteristics of your products and allows for customers to select the details that are most important to them.  A schema delineates the different options for a product, such as size or color, brand, configuration, variations, types, and specifications, each of which is a metadata category. The attributes allow your customers to tell your products apart (a blue sweater vs. a white sweater) and how they are different from those of your competitors. 

New call-to-action

The schema is the overall structure for describing the products in your systems. It contains the list of attributes for the product or product family, and the attributes themselves contain the specific values that describe the product.  For example, the schema for a laptop will include things like price, weight, dimensions, screen size, storage capacity, RAM, processor speed, etc.  The schema for a phone will include some of these elements but also include additional elements such as carrier, wireless capability, number of cameras, etc.  This information is typically stored in a product information management (PIM) software system.

Consistency in attribute naming, definition and application across the entire portfolio of products will improve the customer experience, leading to increased conversions, click-throughs, and sales. Good data governance also supports improved product onboarding and data quality.  

How do you evaluate your product attribute schema design?

Design of product information attributes and schema is based on an understanding of your users and the things they are trying to accomplish.  It is important to define the personas – characteristics of your target prospect – so that designers can determine how the customers are making decisions about purchasing products.  For example, a B2B customer in the procurement department will have different factors in mind than will someone in the engineering department.   Procurement will care about pricing, supply chain, delivery, support and logistics, while engineering will be more concerned about technical specifications.  In each case, information about the appropriate factors needs to be available in the attribute model.

You can evaluate attribute schema design through a variety of approaches.  One is compliance with best practices or “heuristics” – the rules of thumb for a well-designed structure.  Another approach is to analyze user behaviors on the website.  For example, if visitors are coming to a landing page and then leaving without drilling down to products, it may be because they do not see the specifications or details that would help them choose the product they want.  The persona exercise includes development of use cases and user scenarios. Those use cases will reveal which attributes need to be in the schema design. User testing is then used to validate the design choices. 

Who should be concerned about product attribute schema design?

Many executives do not understand the importance of product schema design. Often times, we see responsibility for attribute schema design delegated to the IT organization or sometimes, even outsourced to a low cost-offshore provider.  But we advise against this because of the very real impact on your bottom line that poorly constructed product data models can have on your bottom line.  Correct attribute design is a sophisticated process and requires expertise in a range of areas including merchandising, user experience, product information management, ecommerce, taxonomy development, and information architecture. 

A poor product attribute design has a far-ranging impact, including reduced findability, poor search performance, inability to offer solution bundles, problems with cross-sell and upsell, and ultimately reduced conversions and lower sales.  If customers cannot locate what they need quickly, they will move on to your competitor’s site.  Business leaders, heads of ecommerce, product managers and digital marketing executives should all be concerned about having the solid foundation of a correctly designed product attribute schema. 

Best practices in attribute schema design

One of the critical elements for product attribute schema design is a deep understanding of users based on their role and their objectives.  This is done by creating personas and user journey maps.  One output of this process is a series of use cases that describe exactly what the user needs to do when they come to your site and are solving a problem. The goal is to understand how prospects think through their decision.  How will they select a particular product?  What are the most important factors?  What language do they use when describing challenges and requirements?  The goal is to understand the user’s “mental model” and reflect that model in the design of attributes so that the correct choices can be presented at each touchpoint (perhaps through refiners or facets on the left hand navigation, through related products or through solution bundles, for example).  

While the principles are the same across industries, the process will require different participants when the products are technically complex.  For example, B2B industrial manufacturers will require more input from people who have deep expertise in the domain when developing product schema.  Those subject matter experts will know more about how the product is used and how customers make decisions and solve problems – all of which needs to be reflected in attribute design.  The customer journey for consumers is quite different. B2C businesses will require understanding of the customer’s personal preferences and buying behaviors, rather than requiring deep technical expert input. 

Product display taxonomies are closely related to attribute schemas and inform how those attributes will be managed and optimized.  The display taxonomy leverages the attribute schema for faceted search and guided navigation. Consider the elements that one would click on to narrow a selection of products – size, brand, price, color – or in the case of technical product – the engineering specifications, tolerances and configuration options.  These elements populate refiners that customers use to locate exactly what they want. In this way, taxonomy design is closely related to product attribute design.

Fixing product attributes and product taxonomies leads to directly measurable uplift in click-throughs, conversions, and sales.  Every organization selling products and using a web presence (even if it is not conducting online commerce) can benefit from a well-tuned and tested product attribute schema.  This aids in findability, cross-sell and upsell. 

For a deeper dive into our approach to improving the customer experience through data models, taxonomy, and attributes, read our whitepaper: Attribute-Driven Framework for Unified Commerce.

 

 

Seth Earley
Seth Earley
Seth Earley is the Founder & CEO of Earley Information Science and the author of the award winning book The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable. An expert with 20+ years experience in Knowledge Strategy, Data and Information Architecture, Search-based Applications and Information Findability solutions. He has worked with a diverse roster of Fortune 1000 companies helping them to achieve higher levels of operating performance.

Recent Posts

[7/20/2022] Powering Personalized Search with Knowledge Graphs

Transforming Legacy Faceted Search into Personalized Product Discovery July 20, 2022 @ 1:00PM EDT, 6:00PM BST The latest in e-commerce trends is the transformation of legacy faceted search into a more personalized experience. By applying semantic reasoning over a knowledge graph, contextual information about a customer can be combined with product data, delivering relevant search results tailored to them. The first half of this webinar is designed for the business executive. We’ll focus on why personalized search is an essential e-commerce ingredient. And we’ll demystify the process of implementing a more personalized product discovery experience for your customers. The second half of the webinar is designed for the data strategist. We’ll cover the data modeling required to build knowledge graphs for successful personalized search. We’ll include a real-world demonstration and cover the steps you can take to get started. Who should attend: Executives who care about e-commerce and the data experts who enable them. Speakers:

AIs That Can Draw - It is Still About the Data

Creativity is considered to be a bastion of humanness and somewhat outside of the realm of artificial intelligence.  But AI can be used to generate variations of artistic themes that appear to be creations of their own. 

[RECORDED] Artificial Intelligence Begins With Information Architecture

Building An AI-Powered Enterprise Recorded Webcast In this webinar we establish the formula for AI success:  AI-Powered solutions are only as good as the data that fuels them. Successful AI requires a semantic data layer built on a solid enterprise information architecture. We’ll demystify this topic for executives and provide actionable advice for data strategists. Who should attend: Executives who care about AI and the data experts who enable them. Speakers: