A large telecommunications company wanted to optimize conversions on its e-commerce page. It worked with an agency to create two design variants of the e-commerce page, and tested them against the existing page design. The company also set goals against which the A/B/C test would be evaluated. The test was conducted in Adobe Target.
We evaluated the test results in Adobe Analytics, to granularly understand drivers of performance differential between the exisiting design and the two design variants. We also uncovered externalities that contributed to over or under performance of specific design variants using time-series and market level data analysis.
Our analysis gave the company a holistic overview of the drivers of differences in performance between designs, as an input into the next round of iterative optimization.