microexperiments

Microexperiments are small-scale, rapid experiments designed to test a specific hypothesis with minimal resources, time, and risk. They emphasize speed over comprehensiveness and are used across disciplines to generate evidence early in a project. Typical features include a narrowly defined objective, a minimal viable protocol, short duration, small or selective samples, and pre-defined success criteria.

Applications span product development (A/B testing of features with a subset of users), education and psychology (quick classroom or behavioral studies), software engineering (feature flag experiments), and biology or environmental sciences (small-scale, low-cost tests). In practice, microexperiments aim to produce actionable insights quickly, without committing to large, expensive studies.

Methodology generally follows a simple loop: articulate a hypothesis, design a lean protocol with a single primary outcome, select participants or items, randomize if possible, collect data, and decide on a go/no-go decision or next steps. Ethical considerations and data privacy should be addressed, even in small studies. Results are interpreted with attention to noise and external validity; positive results often require replication at larger scale.

Advantages include speed, lower cost, iterative learning, and reduced risk of large-scale failures. Limitations involve limited statistical power, potential bias, and limited generalizability; they are not substitutes for comprehensive studies when causal inference or external validity is critical. The term is used descriptively across fields and practices, with exact methods varying by context.