The West Michigan Whitecaps Fanning Fan Loyalty Marketing Research Help

The Situation

The West Michigan Whitecaps amin or league baseball team in Grand Rapids, wondered what they should do to develop fan loyalty. How could they best keep it, make it grow, and take advantage of it? General Manager Scott Lane got Message Factors  a Memphis, Tennessee-based research firm, to help them determine how to effectively maintain fan loyalty on a limited budget. Message Factors developed a study that used a proprietary value analysis technique that would examine the relationship between the overall perceived value and specific satisfaction attributes in order to determine loyalty drivers. It helps determine the four things your customers want to tell you, which are the basics-what customer sex pect of the company; value issues-what customers value about the company; irritations- what customers do not like about the company; and unimportants- what customers do not care abou

questionnaire designed to incorporate the 71 attributes was administered to fans at Whitecaps games. The questionnaire was administered to 1,010 respondents. From this, the marketing research company was able to determine the information they were looking for. The basics were determined to be values such as stadium safety, restroom cleanliness, and variety in the fcod items available. The Whitecaps not only want to meet these basic expectations, but also to surpass them to guarantee that fans will return and be loyal. The value issues are the ones that can really help the team build loyalty. These included things like helpful box office personnel. convenience of purchasing tickets, convenience of parking, and providing the opportunity for autographs. Irritations were determined to involve souvenir price, quality, and lack of variety. However, the research also showed that fans don’t really expect to be pleased with this area of sports attendance.It was also determined that there were no unimportant aspects in this survey.

The Marketing Research Decision

1. In order to determine the.relative importance of value drivers, what type of data analysis should Message Factors conduct?
2. Discuss the role of the type of data analysis you recommend in enabling Scott Lane to determine the relative importance of the four value drivers

The Marketing Management Decision

1. In order to enbance the value of Whitecaps games to the fans, what should Scott Larie do?
2. Discuss how the marketing management decision action that you recommend to Scott Lane is influenced by the type of data analysis that you suggested earlier and by the findings of that analysis

Cross-Validation

Before assessing the relative importance of the predictors or drawing any other inferences, it is necessary to cross-validate the regression model. Regression and other multivariate procedures tend to capitalize on chance variations in the data. This could result in a regression model or equation that is unduly sensitive to the specific data used to estimate the model. One approach for evaluating the model for this, and other problems associated with regression, is cross-validation. Cross-validation examines whether the regression model continues to hold on comparable data not used in the estimation. The typical cross-validation procedure used in marketing research is as follows:

1. The regression model is estimated using the entire data set.
2. The available data are split into two parts, the estimation sample and the validation sample. The estimation sample generally contains 50 to 90 percent of the total sample.
3. The regression model is estimated using the data from the estimation sample only. This model is compared to the model estimated on the entire sample to determine the agreement in terms of the signs and magnitudes of the partial regression coefficients.
4. The estimated model is applied to the data in the validation sample to predict the values of the dependent variable, Y, for the observations in the validation sample. S. The observed values, Yj,and the predicted values, Yj, in the validation sample are correlated to determine the simple r-. This measure.r-, is compared to R2 for the total sample and to R2 for the estimation sam ole to assess the degree of shrinkage.

A special form of validation is called double cross-validation. In double cross-validation, the sample is split into halves. One half serves as the estimation sample, and the other is used as a validation sample in conducting cross-validation. The roles of the estimation and validation halves are then reversed, and the cross-validation is repeated

Regression with Dummy Variables

Cross-validation is a general procedure that can be applied even in some special applications of regression, such as regression with dummy variables. Nominal or categorical variables may be used as predictors or independent variables by coding them as dummy variables. The concept of dummy variables was introduced in In that chapter, we explained how a categorical variable with four categories (heavy, medium,light, and nonusers) can be coded in terms of three dummy variables, D., D2′ and D3′ as shown

Regression with Dummy Variables

Regression with Dummy Variables

Suppose the researcher was interested in running a regression analysis of the effect of attitude toward the brand on product use. The dummy variables D i- D2′ and D3 would be used as predictors. Regression with dummy variables would be modeled as:

Regression with Dummy Variables

Regression with Dummy Variables

In this case, “heavy users” has been selected as a reference category and has not been directly included in the regression equation. Note that for heavy users, D., D2′ and D3 assume a value of 0, and the regression equation becomes

Thus the coefficient bl is the difference in predicted Yj for nonusers. as compared to heavy users. The coefficients b2 and b3 have similar interpretations. Although “heavy users” was selected as a reference category. any of the other three categories could have been selected for this purpose.

Posted on December 2, 2015 in Correlation and Regression

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