Pretotyping clarifies whether a customer problem and solution idea create enough real demand. It separates problem, assumption, solution, and evidence, and captures the result as a pretotyping sketch, test setup, and conversion data.
Pretotyping
Turns a product idea into a market claim and tests demand with the smallest possible real-world setup before investing in a prototype.
Does the market do what we claim it will do, or does the behavior fail to appear before we invest a cent in building?
The team formulates the idea as a market claim, chooses the smallest suitable pretotyping technique, tests with real behavior instead of opinions, measures conversion or action, decides whether to build, change, or discard the idea, and documents the learning.
Visual orientation
Method sketch for a quick mental model.
Flow
- 1Formulate the idea as a market claim
- 2Choose the smallest suitable pretotyping technique
- 3Test with real behavior, not opinions
- 4Measure conversion or behavior
- 5Decide whether to build, change, or discard
- 6Document the learning
The runsheet guides execution with 5 phases, timeboxes, 6 pitfalls, and clear stop criteria.
Open runsheetIdeal for
- Very early idea validation
- Market demand checks
- Reducing risk before prototype or MVP investment
- Evidence before engineering work
Not good for
- Detailed UX testing of existing products
- Pure technical feasibility questions
- Already validated problems
Deep dive
Pretotyping, coined by Alberto Savoia at Google, tests whether a product would be wanted before building a prototype. Pretotypes use minimal real materials such as a landing page, mock, poster, concierge service, or manual workflow, but collect real behavior: someone signs up, clicks, pays, waits, or declines. The data becomes a factual basis for deciding whether, what, and how to build.
Choose the pretotyping technique strictly from the question being tested. Define success thresholds before launch, and resist overinterpreting weak signals.
Pretotyping Working TemplateCompact working template for Pretotyping with context, input, output artifacts, and next step.markdown
pretotyping-working-template.md
Compact working template for Pretotyping with context, input, output artifacts, and next step.
Pretotyping Working Template
Goal
Tests whether there is demand at all before building a prototype, using minimal real data.
Context
When and for what do we use this method?
Input
Which data, observations, decisions, or materials are available?
Execution
Short notes along the runsheet.
Output artifacts
- Pretotyping sketch:
- Test setup:
- Conversion data:
- Go or no-go decision:
Assumptions and open questions
- ...
Decision / next step
Owner, date, and success signal.
When to choose differently
Short decision aid for existing alternatives.
Statt Pretotyping, wenn du mit Fake Door Test Nachfrage für eine Funktion direkt im Produkt statt über eine Landing Page messen willst.
Statt Pretotyping, wenn du mit Smoke Test Interesse mit minimalem Aufwand und klarer Botschaft validieren willst.
Similar methods
All methodsMoves customer problem, solution idea, and evidence toward a concrete result through "list assumptions", "map assumptions to dimensions", and "derive the test plan".
Turns customer problem, solution idea, and evidence into a tangible result by defining the hypothesis and signal, building the minimal test, and deriving the decision.
Statt Pretotyping, wenn du mit Smoke Test Interesse mit minimalem Aufwand und klarer Botschaft validieren willst.
Turns customer problem, solution idea, and evidence into a tangible result by defining the hypothesis and target signal, shaping the fake door, and deciding what to learn next.
Statt Pretotyping, wenn du mit Fake Door Test Nachfrage für eine Funktion direkt im Produkt statt über eine Landing Page messen willst.
Turns customer problem, solution idea, and evidence into a tangible result by formulating the value proposition, creating the landing page, and evaluating messaging and offer.
Turns customer problem, solution idea, and evidence into a tangible result by choosing target customers, delivering the outcome manually, and extracting productizable patterns.
Clarifies customer problems, solution ideas, and evidence by preparing a solution concept, recruiting target customers, and deriving risks and next tests.