Don’t read the manual.

Krosstabs is built to be intuitive. But if you want to check our math or learn a new technique, here it is.

Common Workflows

How to weight a sample

Step-by-step: Balancing a N=500 study to Census Age/Gender/Region targets in 3 minutes.

Read Guide

How we compare to SPSS

Don’t trust us blindly. See a side-by-side of significance outputs, features, and price against SPSS.

See comparison

Know the Math

Raking (IPF)

Iterative Proportional Fitting for weighting.

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Banner Table

Column %, sig letters (z-test), Holm/Bonferroni corrections, multi-coded variables.

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TURF Analysis

Total Unduplicated Reach and Frequency.

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Key Drivers

Relative Importance Analysis (Ridge Regression).

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Penalty Analysis

Mean Drop vs. JAR frequencies.

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SurveyStat

Significance testing (T-Test, Z-Test).

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Data Cleaner

Speeders, straight-liners, and gibberish detection.

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Sample Size

Confidence intervals and margin of error.

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Open-End Coder

Embeddings and clustering for text analysis.

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Harmonizer

Fuzzy matching and schema alignment.

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Label Mapper

RegEx and value remapping logic.

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Segment Builder

k-means++, Ward hierarchical clustering, silhouette scoring, and the elbow method.

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Resources

Performance Benchmark

21k-row banner table in under 400ms. Reproducible methodology and raw numbers.

View Benchmark

Import Formats

CSV, XLSX, UTF-8 rules, column header requirements, and common gotchas.

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Export Formats

SPSS variable mapping, Excel sig-letter encoding rules, and CSV structure.

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Sample Datasets

Brand Tracker (N=1000)

A standard brand tracking study with awareness, usage, and image attributes.

Open in Krosstabs

Concept Test (N=500)

Monadic concept test data including open-ended likes/dislikes.

Open in Krosstabs