Yogapedia

Western Yoga Information Resource & Guide

Dec 2025 · Information Architecture · Taxonomy Design · Usability Testing

Overview
ROLE
Information Architect
TIMELINE
Oct 2025 – Dec 2025

A comprehensive information architecture and taxonomy system for a Western yoga learning resource. Designed to maximize both findability and discoverability.

Yogapedia is organizes the complex domain of Western yoga into clear, user friendly structures. I developed a domain model, structure map, and search/browse patterns to help users navigate yoga styles, poses, sequences, and related concepts. The final designs were iterated based on usability testing to improve findability and understandability.

Anticipated Impact

Make yoga concepts easier to find and explore
Support both beginners and teachers with structured browsing
Reduce confusion caused by inconsistent terminology

Final Solution

Bringing structure to how people explore Western yoga

Yogapedia is designed to help practitioners and teachers quickly find specific information (like a pose), while also supporting discovery.

Key Design Decisions

  • Structured taxonomies via faceted filters, controlled vocabulary search, and clickable descriptive metadata.
  • Search safety nets with suggestions and autocorrection to guide users.
  • Theme based class type grouping (e.g., Flow-Based, Heated) to improve findability.

Floor Poses Page

Users can browse poses through sorting by category, and using faceted filters.

Floor Poses page wireframe with numbered callouts

Firefly Pose Page

The pose detail page supports discovery through contextual tags and related content.

Firefly Pose page wireframe with numbered callouts

Global Search Page

A site wide search experience designed with query reformulation.

Global search wireframe with numbered callouts

Getting Started with Yoga Page

A beginner focused page that encourages exploration through guided content sections, local navigation, and a controlled vocabulary search.

Getting Started with Yoga wireframe with numbered callouts
Process

The designs above were developed through a deliberate process that combined domain research, taxonomy design, and usability testing to create the information architecture of the site. Here's the path I took:

  1. 1Domain expert interviews & domain model
  2. 2Open card sort
  3. 3Tree tests
  4. 4Structure map
  5. 5User flow
  6. 6Wireframe
  7. 7Evaluation & iteration

IA lens

For this project, the focus was optimizing:

Findability
Can users locate known items (e.g., "Power Yoga benefits") quickly and confidently?
Discoverability
Do labels + structure support exploration (e.g., "related poses", "prep sequences")?
Understandability
Does the hierarchy match mental models (less jargon, more meaning)?

✦ Understanding the Domain

The first step was to get a good handle on the topic of Western Yoga. I interviewed three yoga teachers (avg. 7 years teaching experience). I coded transcripts for entities (nouns) and relationships to build a domain model.

Research
3 expert interviews → extracted core entities + relationships.
Impact
Clarified the "center of gravity" of the domain (poses ↔ breathwork ↔ meditation).

✦ Creating the Site Structure

Card Sort: Understanding Mental Models

Once I felt that I had a handle on the domain of Western yoga, I ran an open card sort to understand how participants naturally group yoga concepts. The six participants were a combination of yoga teachers and practicioners. From the card sort, I used two signals to inform the structure map:

  1. The labels participants used
  2. The card groupings that had the highest agreement

Strongest label signal:

"Types of Yoga"
4 of 6 participants labeled yoga styles as "Types of Yoga."
Agreement
66.7%

Highest agreement groupings:

These high consensus clusters helped validate which entities should be grouped together in the hierarchy.

Physical Postures
100% Agreement
7 items
Standing Balancing Backbends Forward bends Twists Restorative Savasana
Equipment
92% Agreement
4 items
Mats Blocks Straps Bolsters
Yoga Styles
83% Agreement
11 items
Hatha Ashtanga Iyengar Aerial Yin Restorative Yoga Sculpt Hot Yoga Vinyasa Hot Power Prenatal
Impact
  • I used the highest agreement clusters to confirm which entities should share a parent category.
  • I used participant labels (especially "Types of Yoga") to guide top level naming.

The First Structure Map

Using the card sort results as a guide, I created a structure map and then tested it with a tree test to measure findability using only labels + hierarchy (no UI). Participants were recruited from Reddit's r/yogateachers community. I specifically tested yoga teachers (instead of practitioners) because teachers are more likely to recognize these entities and understand semantic categorization.

Tree Test 1: Lowest Performing Tasks
(n=22, 8 tasks)
Task Success
Where would you find information about the benefits of Power Yoga? 45.5%
Where would you find information about what you can expect from a Yoga Sculpt class? 50.0%
Key learning
For "class type" findability tasks, success was 47% which indicated that something was wrong with the current labels or information hierarchy.

The Second Structure Map

The first tree test showed friction in "class type" tasks. In v1, class types were organized around traditional categories (e.g., Hatha / Vinyasa). Because participants struggled with these findability tasks, I reorganized the class types into thematic groupings.

Version 1
Types of Yoga
  • Vinyasa ex: Power Yoga
  • Hatha ex: Iyengar
  • Hot Yoga ex: Bikram
  • Restorative ex: Yin Yoga
  • More ex: Yoga Sculpt
Version 2
Types of Yoga Classes
  • Flow Based Classes ex: Power, Vinyasa
  • Heated Classesex: Bikram
  • Strength & Fitness ex: Yoga Sculpt, Power
  • Gentle & Restorative ex: Yin Yoga
  • Non Traditional ex: Aerial, Yoga Sculpt

After iterating the hierarchy and labels, I ran a second tree test to verify that findability improved and that changes didn't introduce new confusion elsewhere.

Overall success rate improvement
Comparing tree test v1 vs v2.
Tree test 1 overall success rate (n=22)
68%
Tree test 2 overall success rate (n=5)
85%
Takeaway
The revised labels and hierarchy increased success supporting information findability.

Final Structure Map

✦ Detailed Design

Defining the User Flow

With the structure validated, I translated the information hierarchy into a detailed user flow that models both: known item retrieval (finding a specific pose) and guided discovery (related concepts).

Wireframes and Components

The component design operationalizes the taxonomy through faceted navigation, controlled vocabulary search, descriptive metadata, and search safety nets (autocorrect + autosuggest).

✦ Evaluation and Next Steps

User Evaluation

A task based evaluation was performed on the final designs with three representative users. The aim of the tasks was to test for findability, discoverability, and understandability.

Evaluation insight Change made
Users struggled to distinguish between global and local navigation. Moved local navigation into a vertical left menu to clearly separate it from global navigation.
Evaluators expected bookmarked content to be retrievable via filters. Added bookmarks in local nav and as a facet filter to create multiple retrieval paths.

Next Steps

  • Create a prototype to be able to run more IA evaluation such as first click testing.
  • Broader usability testing search and discovery.
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