Advanced Consumer Product Testing and Mapping, 3 days
This course is a sequel to the popular Hands on Preference mapping course. The aim is to update attendees on recent developments in the fast moving field of Consumer Testing Methodology. The aim is as usual to present new analytical techniques and then give attendees the chance to make a small scale trial and analyse real life data using XLSTAT
Module 1 Extensions to Consumer Descriptive Methods:
This module will review the methodological research that is now guiding the use and conduct of CATA studies and then examine the wider application and analysis of Penalty analysis of JAR data including ASTM guidance. Recent extensions to the recording analysis of Time dependent data is dealt with next including TCATA analysis and a demonstration of the powerful TIMESENS software from Pascal Schlich of Dijon Institut de Gout.
Finally in this section we examine the collection and analysis of Best/Worst data and the MAXDIFF algorithm.
Module 2 New Consumer Methods
This module demonstrates the dynamism of research and development in Sensory and Consumer Science with many new methods coming to the fore. In particular the branch of methods examining how to measure the effects of different modalities such as sight and sound and tactile properties of containers on our perception and liking of foods beverages, and personal products.
A second branch of testing methodology examines the aspects of consumer appreciation that are reflected in non-verbal measures- using behavioural measures, eye-tracking or behavioural exercises such as auctions.
The third group of methods returns to the recording and analysis of data coming via pairwise comparisons and social media studies.
Finally in this module, we look at techniques that are aiming to take that broader view of product testing which view sensory as one component in the consumer decision making and understands that many consumers will use other criteria in reacting to the product: Conceptual Profiling and Hedonext.
Module 3 New Models
An ongoing concern with segmentation and mapping is the presence of large numbers of non-discriminating respondents. Two solutions to this issue are proposed: Removal of non-fitting respondents in the prefmap or the segmentation models. Marketing groups are asking that the segmentation on the basis of sensory assessment takes psychographic variables among the respondents into account. L shaped Analysis enables both consumer parameters and sensory data to contribute to the segmentation process.
Multi-modal models assume an ordered pathway in which modes affect each other according to the order in which they are perceived and we report a new method – Rotated Factor Modelling uses PCA in conjunction with correlation analysis. This method is a simpler version of Structural Equation Modelling and Path PLS. We will apply PLS Path Modeling to Brand diagnosis modelling to understand the contribution of brand, packaging and sensory to product acceptance.