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Tools and Applications of Sensory Product Testing
Monday - November 2 (8:00 a.m. - 4:00 p.m.)
Topics
¨ Difference testing methods: m-AFC, triangle, duo-trio,
same-different, A/Not A, and degree of difference
¨ Estimating a measure of sensory difference, d',
and its variance from discrimination tests
¨ Power and sample sizes for discrimination
methods
¨ Proportion of discriminators in the
population
¨ Replicated testing: Beta-binomial
models
Cases
¨ Brand modification: Product bitterness using m-AFC tests
¨ Ingredient supplier change: Texture using 2-AFC, duo-trio, and triangle;
The issue of power
¨ Superiority claim: 2-AFC vs. duo-trio
¨ 2-AFC and 2-AC on carbonated water
Tuesday - November 3 (8:00 a.m. - 4:00 p.m.)
Topics
¨ How to get d' values
from intensity ratings data
¨ Rating means and scale means
¨ Ranking
¨ Ratio measurement
¨ Advanced concepts and applications:
Retasting, memory, and sequences
¨ Measuring the effect of training
¨ Statistical basis for management
decisions
Cases
¨ Memory and sequence effects: Duo-trio and m-AFC
¨ Improving discrimination by allowing retasting
¨ Relating trained panel and consumer sensitivities
¨ Ingredient change: Getting d' values
from descriptive analysis
¨ Generating a dose response relationship using ranking and rating
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Seeing the Market Through the Eyes of the Consumer
Wednesday - November 4 (8:00 a.m. - 5:00 p.m.)
Multivariate Approaches to Mapping Product Similarities
In this section you will learn how to develop support for superiority, equality and unsurpassed advertising claims. You will see how the National Advertising Division (NAD) reviews and decides advertising claims cases with numerous real world examples. Following this section, you will learn how to produce product maps to display similarity data. Emphasis will be placed on learning through the use of graphics and powerful visual tools. The ideas behind the construction of these maps will then be readily understood. Methods such as biplots, PCA, and multidimensional scaling will be discussed. Multivariate probabilistic approaches to the analysis of data from same-different judgements, degree of difference, Torgerson’s method of triads, and rated reasons for product consumption will be presented with applications to motivations analysis, product/concept fits, and understanding how consumers perceive product differences.
Cases
¨ Review of some cases before the NAD
¨ Plant variation: Mapping similarities of orange juices
¨ Multivariate mapping using a discrimination method
¨ Mapping consumers’ reasons for product consumption
¨ Adults’ and children’s food preferences
¨ Product/concept fit with fragrances
Thursday - November 5 (8:00 a.m. - 4:00 p.m.)
Drivers of Liking® and Portfolio Optimization
You will learn how to interpret liking, preference, and just-about-right data. The concept of an ideal will be explained and used to produce maps of products and ideal points for individual consumers and segments. We will illustrate techniques for using trained-panel, descriptive data and analytical data to explain the unfolded solutions and identify the variables that drive liking. Landscape Segmentation Analysis®, a method for simultaneously segmenting a market and finding drivers of liking, will be discussed. We will show you how a Landscape Segmentation Analysis map can then be used to identify the optimum location for placing a new or existing product as well as to optimize product portfolios.
Cases
¨ Using an ideal point model to analyze just-about-right data
¨ Consumer preference study: Hardness and chocolate flavor of cookies
¨ Individual ideal points: Investigating population segmentation based on liking ratings and finding the relevant drivers of liking
¨ Landscape Segmentation Analysis® on 25 beverages
¨ Product portfolio optimization for a population with three distinct segments
¨ Using Landscape Segmentation Analysis® to monitor and plan competitive moves
Friday - November 6 (8:00 a.m. - 12:00 Noon)
Portofolio Optimization and Competitive Simulations Using Landscape Segmentation Analysis®
Landscape Segmentation Analysis® provides a novel approach to the design of product portfolios and a unique opportunity to engage in competitive marketplace simulations. You will participate in a competition in which you will use Landscape Segmentation Analysis to optimize revenue and/or market share as you make product positioning and new product decisions. You will compete while learning about brand strength, consideration sets, product costs, cannibalization, and timing as new segments emerge. You will also learn to judge when and how much to spend on research since the quality of your information will determine competitiveness.
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