Drivers Isolated, Impact Quantified
CFR Solutions builds regression models that isolate which variables actually move your outcome, controlling for the noise, so you know the real weight of each driver behind satisfaction, sales, or brand equity.
Every Driver Tested, Every Coefficient Checked
Variables are checked for multicollinearity before they ever enter a model, each coefficient is tested for significance rather than assumed, and the final model is validated against a hold-out sample before it's handed over.
Regression Models Built Around Your Question
Whether you're isolating a key driver or predicting an outcome, we match the model to what you're actually trying to explain.
Key Driver Analysis
Ranks the factors behind satisfaction or loyalty by how much each one actually moves the outcome.
Learn more →Linear & Multiple Regression
Quantifies how one or several variables jointly explain change in a continuous outcome.
Learn more →Logistic Regression
Models the probability of a yes/no outcome, such as purchase, churn, or conversion.
Learn more →Shapley Value Regression
Fairly splits credit for the outcome across correlated variables instead of overstating one.
Learn more →Structural Equation Modeling
Maps direct and indirect relationships across multiple linked variables at once.
Learn more →Predictive Modeling
Builds a model that forecasts a future outcome from current and historical data.
Learn more →Explore Our Other Essential Services
Every technique is built on the same rigorous, quota-clean data — pick the analysis that matches the question your study needs to answer.
Brand Mapping
Perceptual maps showing how brands sit relative to each other on key attributes.
Learn more →CHAID Analysis
Decision-tree segmentation that splits respondents by the strongest predictors.
Learn more →Cluster Analysis
Groups respondents into natural segments based on shared attitudes or behavior.
Learn more →Conjoint Analysis
Measures the trade-offs respondents make between product features and price.
Learn more →Correlation Analysis
Measures how strongly two or more variables move together.
Learn more →Discriminant Analysis
Classifies respondents into known groups using their strongest predictors.
Learn more →Factor Analysis
Reduces a long list of variables down to the underlying factors driving them.
Learn more →Multidimensional Scaling
Visual maps of how respondents perceive similarity between items or brands.
Learn more →Regression Analysis
Quantifies how much each predictor moves the outcome you care about.
Learn more →