Agile Learning: Next Generation Experimental Design
Agile Learning adds sophisticated experimental design, validation, and insights to GPS Enterprise platform
New York – June 17, 2020 - Analytic Partners, a global leader in marketing analytics, announced today the official launch of its test and learn solution, Agile Learning as part of the GPS Enterprise solution suite. Agile Learning supports data-driven decision making across an organization by designing experiments that provide accurate and faster validations.
Agile Learning makes sophisticated experimental design easy by guiding the user through test setup, including test vs. control group selection (i.e., market or other), statistically significant sample size, and test length, and by visualizing recommended selections, attributes, KPIs and media data. Contamination checks through the validation process ensure experiment outcomes are statistically sound, driving confidence in measurement and potential to scale. Finally, test results are integrated into the platform to visualize performance and success of the experiment, as well as highlight opportunities for broader application.
Agile Learning can address hypotheses and business questions such as:
As an integrated module of Analytic Partners’ GPS Enterprise platform, Agile Learning is built on the foundation of Commercial Mix Modeling. This integration provides a holistic understanding of marketing and non-marketing drivers to better position businesses facing market challenges and disruptions. Furthermore, by leveraging intelligence from Analytic Partners’ marketing intelligence solution, ROI Genome, Agile Learning goes beyond traditional test/control comparisons to capture and quantify current complexities, measure multiple KPIs, and minimize bias and contamination.
“In today’s disruptive environment, brands need to adapt quickly in order to thrive,” said Nancy Smith, President and CEO of Analytic Partners. “Agile Learning, as part of a Commercial Mix Modeling solution, allows organizations to act decisively, reduce risk and add confidence with advanced testing and experimentation.”
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