How to Reanalyze Past Incrementality Experiments with GeoLift by Recast - Recast
Reanalyze past geo-based incrementality tests with GeoLift by Recast. Validate results & apply synthetic controls with a step-by-step guide.| Recast
Not every lift-testing or incrementality experimentation platform is created equal. Customers have used GeoLift by Recast to design and analyze hundreds of incrementality experiments using the platform’s best-in-class algorithms. We believe these have led to the most accurate and actionable test results in the market. In fact, many Recast customers […] The post Why Recast’s Synthetic Control Methods are Better appeared first on Recast.| Recast
Reanalyze past geo-based incrementality tests with GeoLift by Recast. Validate results & apply synthetic controls with a step-by-step guide.| Recast
Learn how Gaussian Processes model time series data using covariance matrices and kernel functions with practical examples.| Recast
A guide on how to prioritize marketing tests by impact—not just precision—when you can’t run them all.| Recast
A guide on how to prioritize marketing tests by impact—not just precision—when you can’t run them all.| Recast
How three Recast model performance metrics are calculated, including Median Holdout Accuracy and Marketing Dollars Saved.| Recast
Learn how Recast configures the most rigorous MMM with deep business insights, validation checks, and iterative refinement.| Recast
Recast is built to be fully verifiable, update fully automatically (on a weekly cadence) and to be an actionable decision-making platform.| Recast
You're probably modeling seasonality the wrong way. Controlling for seasonality means underspending at peak times. Learn what to do instead.| Recast
Recast’s MMM employs Bayesian statistics. Discover why Bayesian approaches are transforming marketing attribution for top brands.| Recast
