Check out one of our analyses — prebuilt, checked end to end before release, and ready to run on your own data. Find yours the way you actually think about the problem: by the question you're asking, the shape of your data, or your industry.
Commissioned builds live in the pipeline case studies.
Compare two groups? Find what drives an outcome? Spot a trend? The question decides the statistics — get this wrong and everything downstream is wrong too.
Browse by question →One row per customer is a different problem from one row per customer per month. Shape decides which methods can apply to your file at all.
Browse by data shape →Churn in SaaS and readmission in healthcare are the same survival model wearing different clothes. Same maths, different vocabulary, different traps.
Browse by industry →They answer different questions, and they deliberately cross. Cohort Retention
sits on the Trends over time shelf, its data is a panel, and it matters in both
SaaS and Retail. One analysis, three true answers. A single category would force you to
pick one and lose the other two — which is exactly why browsing by method name never worked.
Every analysis here has been run on real data and the report is public. They come from two different places, and the difference matters when you're deciding what to buy.
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