# Product Research Methods Canon

Reference for method selection. Pairs with `study_designer.py`.

## The two-axis map

UX/product research methods sort along two axes (Rohrer, NN/g): **attitudinal vs behavioral** (what people say vs what they do) and **qualitative vs quantitative** (why/how vs how-many). The single most important pre-method decision is the **goal**:

- **Generative (discovery)** — you don't yet know the problem. Methods: semi-structured interviews, contextual inquiry, diary studies. Output: themes, unmet needs, jobs-to-be-done.
- **Evaluative** — you have a solution and want to know if it works. Methods: moderated/unmoderated usability tests, concept tests. Output: task-success, severity-rated problems.
- **Validation** — you want to confirm demand/desirability before building. Methods: surveys, preference tests, fake-door tests, and (when live) A/B experiments.

Picking an evaluative method for a generative goal — "let's usability-test our way to product strategy" — is the most common and most expensive error.

## Interviewing discipline

Steve Portigal's *Interviewing Users* is the operative craft reference: ask about **recent, specific, real behavior** ("tell me about the last time you…"), not hypotheticals or opinions ("would you use…"). People are unreliable narrators of their future selves but good storytellers of their past.

## Jobs-to-be-Done

Christensen's and Ulwick's JTBD reframes research around the **progress a person is trying to make** in a circumstance, not their demographics or feature preferences. Outcome-Driven Innovation (Ulwick) operationalizes this into measurable desired outcomes — a bridge between qualitative discovery and quantitative validation.

## Mixed methods

Strong research triangulates: qualitative discovery surfaces hypotheses; quantitative validation sizes them. Sauro & Lewis (*Quantifying the User Experience*) provides the statistical backbone for turning usability observations into defensible metrics (task time, completion, SUS) without over-claiming from small samples.

## Sources

1. Portigal, S., *Interviewing Users*, 2nd ed. (Rosenfeld, 2023).
2. Christensen, Hall, Dillon & Duncan, *Competing Against Luck* (2016) — Jobs-to-be-Done.
3. Ulwick, A., *Jobs to Be Done: Theory to Practice* (2016) — Outcome-Driven Innovation.
4. Rohrer, C., *When to Use Which User-Experience Research Methods* — Nielsen Norman Group.
5. Sauro, J., & Lewis, J., *Quantifying the User Experience*, 2nd ed. (Morgan Kaufmann, 2016).
6. Goodman, Kuniavsky & Moed, *Observing the User Experience*, 2nd ed. (2012).
