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Chapter 21 - Multidimensional scaling and conjoint analysis. In this chapter, the following content will be discussed: Multidimensional scaling, approaches to creating perceptual maps, attribute based approaches, comparison of factor and discriminant analysis,...
1 Marketing Research Aaker, Kumar, Leone and Day Twelfth Edition Instructor’s Chapter TwentyOne Multidimensional Scaling and Conjoint Analysis Marketing Research 12th Edition Multidimensional Scaling Used to: • • • Identify dimensions by which objects are perceived or evaluated Position the objects with respect to those dimensions Make positioning decisions for new and old products Marketing Research 12th Edition Approaches To Creating Perceptual Maps Perceptual map Attribute data Nonattribute data Preference Similarity Factor analysis Correspondence analysis Discriminant analysis MDS Marketing Research 12th Edition Attribute Based Approaches • • Attribute based MDS MDS used on attribute data Assumption ▫ • • The attributes on which the individuals' perceptions of objects are based can be identified Methods used to reduce the attributes to a small number of dimensions ▫ Factor Analysis ▫ Discriminant Analysis Limitations ▫ Ignore the relative importance of particular attributes to customers ▫ Variables are assumed to be intervally scaled and continuous Marketing Research 12th Edition Comparison of Factor and Discriminant Analysis Discriminant Analysis • • • Identifies clusters of attributes on which objects differ • Identifies a perceptual dimension even if it is represented by a single attribute • Statistical test with null hypothesis that two objects are perceived identically • Factor Analysis Groups attributes that are similar Based on both perceived differences between objects and differences between people's perceptions of objects Dimensions provide more interpretive value than discriminant analysis Marketing Research 12th Edition Perceptual Map of a Beverage Market Marketing Research 12th Edition Basic Concepts of Multidimensional Scaling (MDS) • MDS uses proximities (value which denotes how similar or how different two objects are perceived to be) among different objects as input • Proximities data is used to produce a geometric configuration of points (objects) in a twodimensional space as output • The fit between the derived distances and the two proximities in each dimension is evaluated through a measure called stress • The appropriate number of dimensions required to locate objects can be obtained by plotting stress values against the number of dimensions Marketing Research 12th Edition Determining Number of Dimensions Due to large increase in the stress values from two dimensions to one, two dimensions are acceptable Marketing Research 12th Edition 10 Attributebased MDS Advantages • • Attributes can have diagnostic and operational value Disadvantages • Attribute data is easier for the respondents to use • • Dimensions based on attribute data predicted preference better as compared to nonattribute data • If the list of attributes is not accurate and complete, the study will suffer Respondents may not perceive or evaluate objects in terms of underlying attributes Marketing Research 12th Edition 11 Application of MDS With Nonattribute Data Similarity Data • • • Reflect the perceived similarity of two objects from the respondents' perspective Perceptual map is obtained from the average similarity ratings Able to find the smallest number of dimensions for which there is a reasonably good fit between the input similarity rankings and the rankings of the distance between objects in the resulting space Marketing Research 12th Edition 12 Similarity Judgments Marketing Research 12th Edition 13 Perceptual Map Using Similarity Data Marketing Research 12th Edition 14 Application of MDS With Nonattribute Data (Contd.) Preference Data • • An ideal object is the combination of all customers' preferred attribute levels Location of ideal objects is to identify segments of customers who have similar ideal objects, since customer preferences are always heterogeneous Marketing Research 12th Edition 15 Issues in MDS • • • • Perceptual mapping has not been shown to be reliable across different methods The effect of market events on perceptual maps cannot be ascertained The interpretation of dimensions is difficult When more than two or three dimensions are needed, usefulness is reduced Marketing Research 12th Edition 16 Conjoint Analysis • • • Technique that allows a subset of the possible combinations of product features to be used to determine the relative importance of each feature in the purchase decision Used to determine the relative importance of various attributes to respondents, based on their making tradeoff judgments Uses: ▫ To select features on a new product/service ▫ Predict sales ▫ Understand relationships Marketing Research 12th Edition 17 Inputs in Conjoint Analysis • • • The dependent variable is the preference judgment that a respondent makes about a new concept The independent variables are the attribute levels that need to be specified Respondents make judgments about the concept either by considering ▫ Two attributes at a time Tradeoff approach ▫ Full profile of attributes Full profile approach Marketing Research 12th Edition 18 Outputs in Conjoint Analysis • • • A value of relative utility is assigned to each level of an attribute called partworth utilities The combination with the highest utilities should be the one that is most preferred The combination with the lowest total utility is the least preferred Marketing Research 12th Edition 19 Applications of Conjoint Analysis • • • • Where the alternative products or services have a number of attributes, each with two or more levels Where most of the feasible combinations of attribute levels do not presently exist Where the range of possible attribute levels can be expanded beyond those presently available Where the general direction of attribute preference probably is known Marketing Research 12th Edition 20 Steps in Conjoint Analysis Marketing Research 12th Edition 21 Utilities for Credit Card Attributes Source: Paul E. Green, ‘‘A New Approach to Market Segmentation,’’ Marketing Research 12th Edition 22 Utilities for Credit Card Attributes (Contd.) Marketing Research 12th Edition 23 Fullprofile and Tradeoff Approaches Source: Adapted from Dick Westwood, Tony Lunn, and David Bezaley, ‘‘The Tradeoff Model and Its Extensions’’ Marketing Research 12th Edition 24 Limitations of Conjoint Analysis Tradeoff approach • • The task is too unrealistic Tradeoff judgments are being made on two attributes, holding the others constant Fullprofile approach • If there are multiple attributes and attribute levels, the task can get very demanding Marketing Research 12th Edition 25 End of Chapter TwentyOne Marketing Research 12th Edition ...2 Chapter TwentyOne Multidimensional Scaling and Conjoint Analysis Marketing Research 12th Edition Multidimensional Scaling Used to: • • • Identify dimensions by which objects are perceived ... interpretive value than discriminant analysis Marketing Research 12th Edition Perceptual Map of a Beverage Market Marketing Research 12th Edition Basic Concepts of Multidimensional Scaling (MDS) • MDS uses proximities (value which denotes how similar or how different two ... Where the range of possible attribute levels can be expanded beyond those presently available Where the general direction of attribute preference probably is known Marketing Research 12th Edition 20 Steps in Conjoint Analysis Marketing Research