<!-- SPDX-License-Identifier: MIT -->
<!-- SPDX-FileCopyrightText: 2025-2026 Marcus Quinn -->

## Data Foundation

### Quantitative Sources

| Tool Type | Examples | Provides |
|-----------|----------|----------|
| Web analytics | GA4, Adobe Analytics, Matomo | Traffic, behavior, funnel performance, acquisition |
| Behavioral analytics | Hotjar, Crazy Egg, FullStory | Heatmaps, session recordings, form analytics, rage clicks |
| A/B testing | Optimizely, VWO, GA4 Experiments | Variant performance, statistical significance |
| Business intelligence | Internal BI tools | Revenue, LTV, churn, returns, support volume |

### Qualitative Sources

| Method | Tools | Provides |
|--------|-------|----------|
| Surveys | Qualaroo, Typeform, SurveyMonkey | Motivations, satisfaction, NPS |
| User interviews | Direct conversations | Motivations, objections, customer language |
| Session recordings | Hotjar, FullStory | Confusion points, decision-making process |
| Customer support data | Help desk, CRM | Common questions, objections, complaints |
| User testing | UserTesting.com, UsabilityHub | Task completion, usability issues |

### Combining Data Types

- **Quantitative** = *what* is happening (45% abandon on payment page)
- **Qualitative** = *why* (users concerned about security; mobile form fields hard to use)

Combine both to form targeted hypotheses before running tests.
