All Posts

Product Taxonomy Mutual Exclusivity - One Product, One Place

Mutual Exclusivity is an organizing principle for taxonomies which requires every SKU in your product catalog have one (and only one) place in the product taxonomy. 

A taxonomy is the collection of categories that represent the products you sell on your website and shows they relate to other types of products in your selection. 

Because taxonomies are built around product categories, they are designed such that each SKU can be filed under only one category. This concept of “each item can be classified to a single product category” is what defines Mutual Exclusivity.

Here is a simple thought experiment to illustrate the concept.  Imagine two online stores where lemons are sold.  In store A, you see:


  • Fruit
    • Citrus Fruit
    • Melons
    • Apples

It is easy to guess that Lemons, being a citrus fruit, would be found under Citrus Fruit.  They are Citrus Fruit and they are not Melons, nor are they Apples. Each SKU of Lemons that you sell would then be classified to the “Citrus Fruit” category. Obvious and helpful, right?

Now consider this taxonomy structure for store B:


  • Fruit
    • Citrus Fruit
    • Yellow Fruit
    • Sour Fruit

This is problematic – Lemons are Citrus Fruit, but they are also Yellow Fruit and they are Sour Fruit. So in this structure Lemons could be placed in any one of these categories.  This store has violated Mutual Exclusivity by creating multiple categories where a Lemon SKU could (correctly) be assigned. 

PRO TIPS: How Product Attribute Schema Design Works As A Competitive Advantage

Why does mutual exclusivity matter?

It might seem obvious with lemons – who would create a “yellow fruit” category?  Yet we see the second scenario frequently with ecommerce sites. 

When you have a LOT of SKUs to organize the problem is much more complex. 

But with more products to browse your organizing principles impact the experience of the buyer to an even greater degree.  So, mutual exclusivity is a golden rule that you must not break.  Here are some solid reasons:

  • When a product is found in more than one category, customers have to go multiple places on your site to see the full selection – this adds effort to product discovery and can negatively impact a site’s effectiveness.   People are busy.  When they get frustrated enough with digging through category after category, eventually they will give up and go elsewhere. 
  • Poor categorization reflects poorly on your company.  If your categories aren’t Mutually Exclusive, frustrated users may question your expertise - do you really know anything about what you are selling? Are you the right place for them to purchase this product?  You may lose not only that prospect but others they tell about your siteShow you know what you are doing by organizing wisely.
  • Governance of your product data is much simpler with a Mutually Exclusive taxonomy, as it ensures all SKUs of a particular type are managed together in a single home with a single set of rules for data quality.
  • New item launches and sharing data with partners and suppliers are much easier when they can pair each of their categories with a single (Mutually Exclusive) category in your taxonomy. A 1:1 match between your taxonomy and your channel partners reduces time to launch and encourages your suppliers or distributors to carry more of your line.

What to do right now

Consider doing a “Store Walk” through your taxonomy from the point of view of the personas who would visit and purchase from your site. 

  • What kind of products are they looking for? 
  • Is it clear which categories they should choose to find each one? 

This exercise will likely lead to some valuable ah-ha moments regarding your site navigation and give you a path to improvement. 

Look at your Product Detail Pages as well.  The information displayed there can also be impacted by Mutual Exclusivity.  If your taxonomy is not mutually exclusive then you may have SKUs of the same product type appearing in multiple categories where different specifications are shown – making comparison difficult.

This can happen when the duplicate categories have different requirements for attribution (which can happen when duplicate categories exist).

Resolving this by combining the duplicate categories into a single Mutually Exclusive master category improves the user experience by making it easy to compare “apples to apples” in one place.  Be sure to add comparing like items as part of your “Store Walk” exercise.

What to do going forward

If you have a site already test for mutual exclusivity and fix what’s broken.  Have your product managers conduct “Store Walks” to look for issues.

If you haven’t built your site yet,  now is the perfect time to plan to build with mutual exclusivity in mind – before you waste money on site designs or wireframes.

Review your site regularly, and refine your taxonomy to keep it compliant as you grow.  Disorder has a way of creeping in if you aren’t paying attention.  Be sure to vet new items so that they fit into one, and only one, category; if you “bend” your categories (classifying SKUs there that don’t genuinely belong) you are only making more work in the near future.

Learn how we use customer data models, product data models, content models, and knowledge architecture to create a framework for unified commerce download our whitepaper: Attribute-Driven Framework for Unified Commerce

Chantal Schweizer
Chantal Schweizer
Chantal Schweizer is a taxonomy professional with over 10 years of experience in Product Information and Taxonomy. Prior to joining Earley Information Science, Chantal worked on the Product Information team at Grainger for 9 years, Schneider Electric’s PIM team for 2 years and had some previous work in PIM consulting.

Recent Posts

The Future of Bots and Digital Transformation – Is ChatGPT a Game Changer?

Digital assistants are taking a larger role in digital transformations. They can improve customer service, providing more convenient and efficient ways for customers to interact with the organization. They can also free up human customer service agents by providing quick and accurate responses to customer inquiries and automating routine tasks, which reduces call center volume. They are available 24/7 and can personalize recommendations and content by taking into consideration role, preferences, interests and behaviors. All of these contribute to improved productivity and efficiency. Right now, bots are only valuable in very narrow use cases and are unable to handle complex tasks. However, the field is rapidly changing and advances in algorithms are having a very significant impact.

[February 15] Demystifying Knowledge Graphs – Applications in Discovery, Compliance and Governance

A knowledge graph is a type of data representation that utilizes a network of interconnected nodes to represent real-world entities and the relationships between them. This makes it an ideal tool for data discovery, compliance, and governance tasks, as it allows users to easily navigate and understand complex data sets. In this webinar, we will demystify knowledge graphs and explore their various applications in data discovery, compliance, and governance. We will begin by discussing the basics of knowledge graphs and how they differ from other data representation methods. Next, we will delve into specific use cases for knowledge graphs in data discovery, such as for exploring and understanding large and complex datasets or for identifying hidden patterns and relationships in data. We will also discuss how knowledge graphs can be used in compliance and governance tasks, such as for tracking changes to data over time or for auditing data to ensure compliance with regulations. Throughout the webinar, we will provide practical examples and case studies to illustrate the benefits of using knowledge graphs in these contexts. Finally, we will cover best practices for implementing and maintaining a knowledge graph, including tips for choosing the right technology and data sources, and strategies for ensuring the accuracy and reliability of the data within the graph. Overall, this webinar will provide an executive level overview of knowledge graphs and their applications in data discovery, compliance, and governance, and will equip attendees with the tools and knowledge they need to successfully implement and utilize knowledge graphs in their own organizations. *Thanks to ChatGPT for help writing this abstract.

Innovation with Utility in Mind - What’s Ahead for 2023

It has been a year of advances in AI with new tools that create art, write essays, and have conversations that are often (but not always) startlingly eloquent.  It is that space of "not always" that keeps these tools from working out of the box to solve actual business problems without human intervention.