Tree Testing Navigation Record

Template Overview

Visual design elements frequently mask underlying navigational flaws. Tree testing isolates category hierarchy to measure direct task success, backtracking frequency, and cognitive disorientation. The Tree Testing Navigation Record documents test protocols, category branches, task completion metrics, and structural recommendations in plain Markdown.

Markdown Template Structure

Copy the block below or click Download .md File to add this template directly to your personal vault:

---
title: "Tree Test Study: [Navigation Hierarchy Name]"
date: [YYYY-MM-DD]
lead_researcher: "[[Researcher Name]]"
tree_version: "v2.1"
total_participants: 25
average_success_rate: "78%"
tags: [ux-research, information-architecture, tree-testing, navigation]
---

# Tree Testing Navigation Study — [Navigation Hierarchy Name]

## 1. Research Objectives & Tree Scope
- **Research Goal:** Determine if knowledge workers can locate vault configuration settings and export controls within 3 navigation clicks.
- **Hierarchy Tested:** Text-only tree containing 4 top-level branches and 32 nested subcategories.

## 2. Evaluated Information Architecture Hierarchy
```text
Root
├── Vaults
│   ├── Local Storage Directory
│   ├── Indexing & Search Indices
│   └── Encryption Keys
├── Transcription
│   ├── Local Whisper Models
│   ├── Audio Device Inputs
│   └── Custom Vocabulary Lexicons
├── Templates
│   ├── Personal Vault Templates
│   └── Community Gallery
└── Export & Integration
    ├── Markdown Batch Export
    └── JSON-LD Schema

3. Task Performance Matrix

Task ID	Task Description	Direct Success	Indirect Success	Failure Rate	Directness Score
T01	Find where to change audio input microphone	88%	8%	4%	92%
T02	Locate custom vocabulary dictionary	56%	24%	20%	60%
T03	Export notes to plain text Markdown directory	92%	4%	4%	94%

4. Navigation Friction & Backtracking Analysis

• Task T02 Friction Point: 44% of participants first searched under Vaults > Local Storage instead of Transcription > Custom Vocabulary.
• Root Cause: Users conceptualized terminology as a vault-level dictionary rather than a model transcription setting.

5. Architectural Recommendations

[!IMPORTANT] Recommendation Relocate custom vocabulary access directly to Transcription root and cross-link from Vaults settings to align with user mental models.

6. Next Steps

• Revise navigation tree structure to version 2.2.
• Rerun unmoderated tree test validation on revised branch.

## Filled Real-World Example

Here is a realistic example demonstrating how this template captures actual deliberations:

```markdown
---
title: "Tree Test: Knowledge Vault IA — Study 4"
date: 2026-10-07
lead_researcher: "[[Marcus Vance]]"
tree_version: "v2.1"
total_participants: 30
average_success_rate: "82%"
tags: [ux-research, tree-testing, ia]
---

# Tree Testing Navigation Study — Knowledge Vault IA

## 1. Study Overview
Marcus Vance conducted a tree testing study with 30 technical writers and developers to evaluate the newly organized preferences tree.

## 2. Key Task Findings
Participants demonstrated 93% direct success finding export settings under `Export & Integration`. However, finding hardware acceleration settings had an initial 32% failure rate because users looked under `System` rather than `Transcription Engine`.

## 3. Structural Decision
The IA team agreed to promote `Hardware Engine` to a dedicated top-level category in the next desktop release.

When to Use and When to Avoid

When to Use

• Use when restructuring complex product navigation menus, documentation trees, or settings panels.
• Use before committing to high-fidelity visual mockups of navigation drawers or sidebars.
• Use to establish baseline findability metrics across sequential product versions.

When to Avoid

• Avoid using to evaluate visual layout, button colors, or responsive typography.
• Avoid using when testing free-form exploratory search queries.

On-Device AI Integration

Summarize your recording in Oyma with this local instruction:

Analyze the navigation tree testing dataset:
1. Identify tasks with failure rates exceeding 15% and trace common misdirected navigation paths.
2. Calculate average directness scores across all participant sessions.
3. Recommend specific label renames or category reorganizations in structured Markdown.

Your data remains securely on your Mac with zero cloud exposure.