Hypothesis
Define the audience, metric and decision rule.
Reduce uncertainty before a major investment: we turn an assumption into a testable scenario, gather evidence and give you a fact-based conclusion.
We take one key assumption, one audience and one metric, then agree the decision rule before work begins.
Whether the target audience needs a new service or feature
Whether users understand the value proposition
Whether users complete the key journey in a prototype
Whether the available data supports an AI scenario
Whether a new approach works on a limited sample
Which solution deserves the next investment
The test method and access to data or respondents are agreed before kickoff.
Define the audience, metric and decision rule.
Build a working scenario that is sufficient for the test.
Run it with the agreed data set or users.
Review the findings and make one adjustment.
Demonstrate the result and recommend the next step.
This format delivers an investment decision, not the promise of a production system.
A working prototype of the agreed scenario
Data and observations from the test
Documented limitations and risks
A conclusion: develop, change or stop
Recommendations and an estimate for the next stage
A production system is not the output of hypothesis testing unless it separately fits the agreed scope.
A full production product with scale and an SLA
Several independent hypotheses tested at once
A large market study or representative quantitative sample
Creating a missing data set from scratch
Multiple cycles of concept redesign
A guarantee of market success after a positive test
The sprint produces enough evidence for a decision without pretending to be a full research programme.
Describe the assumption, audience and decision you need to make. We’ll assess the format and reply within 24 hours.