Marketing Analysisfor Everyone.
No installs. No coding. No cost. Yes to insights.
From hypothesis to insight in minutes — run real statistical tests, build predictive models,
and simulate markets with tools that teach as you go.
Getting Started
Univariate Analyzer
Explore a single variable's distribution, outliers, and summary stats. Always start here.
Tool Finder
Not sure which tool to use? Browse all 42 tools, use our guided wizard, or find answers to common questions.
Pearson Correlation
Check if two continuous metrics move together (e.g., ad spend vs. revenue).
Categorization Studio
Transform continuous data into meaningful categories. See how the same data tells different stories.
Hypothesis Testing
Welch's t-test
Compare averages of two independent groups (e.g., Control vs. Treatment).
Paired t-test
Compare before/after scores for the same people (e.g., Pre vs. Post).
One-Way ANOVA
Compare averages across 3+ groups (e.g., 4 different landing pages).
A/B Proportion Test
Compare conversion rates between two variants.
Chi-Square Test
Check if two categorical variables are related (e.g., Device vs. Signup).
McNemar Test
Analyze "switchers" in paired yes/no data (e.g., before/after purchase).
Predictive Modeling
Simple Regression
Predict an outcome using one variable (e.g., Spend → Sales).
Multiple Regression
Predict a numeric outcome using multiple drivers.
MLR with Interactions
Model non-linear effects and interaction terms.
Logistic Regression
Predict binary outcomes like Churn vs. Retain.
Multinomial Logit
Predict choice among 3+ options (e.g., Brand A vs B vs C).
Mediation Visualization
Visualize direct, indirect, and total effects in mediation and moderated mediation models.
Model Fitting
Text Analysis
Qualitative Analyzer
Manually code and analyze interview transcripts or focus groups.
Theme Extractor
Automatically discover hidden topics in reviews using AI.
Sentiment Lab
Score text as positive, negative, or neutral.
Marketing Attribution
Shapley Value Attribution
Cooperative Game Theory. Assign fair credit to channels based on their marginal contribution to the team.
Markov Chain Attribution
Sequence-based attribution. Analyze how the order of touches acts as a bridge to conversion.
Advanced Analytics
Decision Tree Classifier
Build and interpret classification trees to segment customers and predict outcomes.
AI Prediction Lab
Build and visualize neural networks to solve complex marketing classification problems.
K-Means Clustering
Segment customers into distinct groups based on behavior.
k-Prototypes Clustering
Cluster mixed attributes (Numbers + Categories) like Spend + Region.
Latent Class Segmentation
Probabilistic customer segmentation using LCA/LPA. Discover hidden segments with soft class membership.
ARX Forecasting (Intro)
Learn time series basics with ARX models—easier than ARIMAX, no moving average terms.
ARIMAX Forecasting
Forecast sales over time with external predictors like ad spend.
Marketing Resource Optimizer
Allocate limited budgets or resources across channels to maximize ROI.
Territory Optimizer
Draw sales territories on a map, balance workloads, and optimize rep assignments.
Conjoint Study Creator
Design conjoint analysis experiments to measure customer preferences and willingness to pay.
Conjoint Analysis
Analyze conjoint study results to reveal customer preferences and part-worth utilities.
Basic Conjoint Analysis
Simplified conjoint analysis for quick preference insights.
Study Design & Probability
Sample Size (Single)
Plan n for one mean or proportion.
Sample Size (A/B)
Plan n for comparing two groups.
Sample Size (Reg)
Plan n for correlation/regression.
Multi-Arm A/B
Plan n for A/B/C/D tests.
Sampling Visualizer
See how different sampling methods work.
Selection Lab
Explore selection probabilities.
Probability Calc
Calculate likelihood of repeated events (Binomial/Poisson).
Model Fitting Foundations
MAE Calibration Lab
Manually fit linear & quadratic models by minimizing error. Discover what "model fitting" really means.
Log-Loss Classification Lab
Manually calibrate logistic regression by minimizing log-loss. Learn why probability calibration matters for marketing.
Overfitting Explorer
Explore bias-variance tradeoff through polynomial regression. Compare training vs. holdout performance across marketing scenarios.