How do you balance consistency and creativity when labeling and categorizing content?

2 Categorizing principles

Categorizing is the process of grouping and organizing content items into meaningful and logical units, such as categories, subcategories, facets, or tags. To ensure effective categorizing, categories should reflect the users' needs and goals, and help them filter and refine their search for information. Clear and distinct criteria should be used for defining and separating categories to avoid overlapping or ambiguous groups. Additionally, hierarchical and flat structures should be used appropriately depending on the complexity and diversity of the content. Multiple and flexible ways of categorizing content should also be employed, such as by topic, audience, function, or format, to accommodate different user preferences and scenarios. Finally, it is important to test and validate your categories with users, revising them based on feedback and analytics.

4 Labeling and categorizing best practices

In order to create effective labels and categories for your content and overcome the associated challenges, there are several best practices to keep in mind. You should define your goals and objectives for labeling and categorizing content, and ensure they are aligned with user research and content strategy. Additionally, it is beneficial to use a combination of methods and techniques to generate and evaluate labels and categories, such as card sorting, tree testing, content modeling, and content auditing. Furthermore, tools and standards can be used to support and document labeling and categorizing decisions, such as style guides, glossaries, taxonomies, and ontologies. Lastly, it is important to review and update labels and categories regularly in order to monitor their performance and impact on user behavior and satisfaction.

5 Labeling and categorizing examples

To illustrate the principles and practices we have discussed, here are some examples of labeling and categorizing content in various domains and contexts. For instance, Amazon uses descriptive and suggestive labels for its product categories, subcategories, and facets, such as "Books", "Fiction", and "Best Sellers". They also rely on user-generated labels, including ratings, reviews, and wish lists. Similarly, Coursera implements clear and consistent labels for its course categories, subcategories, and formats; they also categorize their courses by level, language, or partner. Lastly, Mayo Clinic uses concise and standard labels for its health topics, subtopics, and sections; plus dynamic labels to reflect current relevant content - such as "COVID-19".