Research Method Explorer
An interactive tool that guides you to the right UX research method based on your goals, constraints, and context.
A research platform with verified participants, built and run by behavioral scientists.
Custom research, consulting, training, and strategy for teams who need strategic clarity.
B2B and B2C audiences from our proprietary panel. Recruiting, testing, and analysis for Market & Consumer Research and UX.
Strategic research for decision-makers who can't afford to guess.
"Business decisions based on gut feeling"
Strategic research that connects customer evidence to business decisions.
"Hard to reach audiences and target groups"
Proprietary panel with verified research participants for feedback on concepts and live products.
"Campaigns that miss the mark"
Brand validation through consumer psychology and intelligence.
"No clear view on employee experience"
Internal clarity instead of misalignment through employee experience insights.
"Internal playtests are biased; 'fun' is hard to measure."
Objective player data. From genre verification (Steam) to biometric lab testing.
Real people, accelerated impact.
Research goals, target audience, and methodology defined by the team.
Panel recruitment, screening, scheduling, and data collection run through our platform. AI-assisted, human-monitored.
Prioritized findings with strategic recommendations. Every deliverable is built for decision-makers, not filing cabinets.
Every study we run is reverse-engineered from the decision it needs to inform. If a finding doesn't connect to something your team can act on, it doesn't make the report.
Tell us about your challenge. We'll show you how ground truth can de-risk your next move.
Or reach us directly at marc.busch@busch-labs.at or +43 699 197 101 86
Strategic thinking and practical guidance from our team
An interactive tool that guides you to the right UX research method based on your goals, constraints, and context.
An interactive sample size calculator for UX research, with the statistical foundations explained — from binomial problem discovery to power analysis.
Four pillars that protect your data: verified participants, respectful experience, study review before launch, and continuous quality monitoring.