A Comparison of the Taguchi Method and Evolutionary Optimization in Multivariate Testing

• DOI: 10.48550/arxiv.1808.08347
• Publication Date: 2018-01-01
• Authors: Jingbo Jiang; Diego Legrand; Robert Severn; Risto Miikkulainen
• Keywords: Interface (matter); Orthogonal array

Multivariate testing has recently emerged as a promising technique in web interface design. In contrast to the standard A/B testing, multivariate approach aims at evaluating large number of values few key variables systematically. The Taguchi method is practical implementation this idea, focusing on orthogonal combinations values. This paper evaluates an alternative method: population-based search, i.e. evolutionary optimization. Its performance compared that several simulated conditions, including one designed favor method, and two realistic conditions with dependences between variables. Evolutionary optimization found perform significantly better especially suggesting it forms good for design future.