A. Narayanan, Adjunct Assistant Professor, University of Cincinnati, OH, USA
Zhiwu Liang, Procter & Gamble, Brussels, Belgium
In this presentation, we use the longitudinal analysis capability of the Structural Equation Modeling (SEM) platform in JMP to measure the impact of temperature and usage amount on detergent performance from the consumer perspective using a measure of the overall rating of product.
In this diary study measured over time, data were collected from consumers who used one of two products in three phases of four-week time intervals. Using data collected from Week 5 to Week 9, we modeled the trajectories of the performance of the detergent in relation to the temperature and usage (number of pods). Using standard SEM fit measures, we found the linear growth curve model fit the data well for the underlying latent structures. Results showed that one of the test products performed significantly better under cold-wash temperatures and used fewer pods than the other product. This result was a significant win for the company under the sustainability platform and performance under colder wash conditions.
