Start Building Evidence
We believe that understanding human behavior is key to transforming business performance. Every engagement begins with a thorough analysis to identify opportunities, followed by carefully designed interventions that drive measurable results. We deploy our solutions in deliberate and transparent ways to demonstrate effectiveness before full-scale implementation.
Test What Works
Transform decision-making through systematic testing and validation. We help organizations understand exactly what drives results by:
Conducting systematic audits of initiatives, vendors, and services using controlled trials to identify which investments deliver proven value
Building robust measurement systems that create clear, actionable insights
Validating or debunking assumptions through rigorous testing
Optimize Operations
Eliminate waste and improve efficiency through evidence-based process improvement. Our approach combines rigorous testing with practical implementation:
Systematically identify and eliminate ineffective processes
Validate cost reduction opportunities before full implementation
Create optimization roadmaps based on proven results, not assumptions
Increase Conversions
Maximize revenue through proven behavioral interventions and validated strategies. We help you:
Identify and fix conversion barriers through systematic behavioral testing
Validate which activities truly drive revenue before scaling
Test and optimize growth strategies
Conduct rigorous behavioral audits to identify and fix friction points
Unbiased Analysis
Transform raw data into validated insights through unbiased analysis. Our expertise includes:
Design and analysis of randomized controlled trials
Advanced statistical modeling and causal inference
Machine learning applications
Academic research support
Statistical Analysis:
Power Analysis & Sample Size Determination
Descriptive Statistics & Exploratory Data Analysis
Regression Analysis (Linear, Logistic, Mixed Effects)
Time Series Analysis & Forecasting
Factor Analysis & Dimensionality Reduction
Survival Analysis
Bayesian Statistical Methods
Causal Inference:
Randomized Controlled Trials (RCT) Design
Difference-in-Differences Analysis
Regression Discontinuity Design
Instrumental Variables
Mediation Analysis
Machine Learning Applications:
Predictive Modeling
Feature Selection & Engineering
Cross-Validation Techniques
Random Forests & Gradient Boosting
Natural Language Processing
A/B Testing & Multi-Armed Bandits
Research Support:
Study Design & Protocol Development
Sample Size & Power Calculations
IRB Documentation Support
Grant Writing Statistical Support
Results Interpretation & Visualization
Publication-Ready Figures & Tables
