In the digital age, retailers and all e-commerce vendors face the constant pressure to offer the latest and greatest technologies that make shopping online easy, and reliable. Before implementation, leading retailers are prioritizing performance validation of new technologies.
A/B testing has long-served as the gold standard for performance validation in the e-commerce industry, yet, the increasing complexity of modern websites and adoption-based technologies cause standard A/B tests to break down.
Traditional A/B tests rely on long-term stable implementations where users adopt the technology, and come back as loyal shoppers to make repeat visits. This performance validation method becomes problematic for adoption-based technologies.
We recommend Matched Cohort Analysis (MCA) as an alternative to A/B testing because of its difference-in-difference technique and synthetic control cohort that is designed to match the True Fit user’s cohort characteristics. MCA offers better, more reliable performance validation because it avoids many of the technical pitfalls that cause standard A/B tests to break down.
Retailers gain a better overview on True Fit’s ability to increase consumer satisfaction and loyalty, from a smooth implementation. Matched Cohort Analysis is the best alternative testing method to showcase the uses of this technology for consumers and retailers.
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