For this assignment, you’ll design and conduct a conjoint analysis study focusing on understanding customer preferences for credit cards. This assignment will help you build skills in the following areas:
You are serving as the marketing manager for an online retailer that is introducing a new credit card product to its customer base. The company’s goal is to maximize the appeal and adoption of this credit card by tailoring it to the preferences of its customers. To achieve this, your team is conducting a conjoint analysis study. This will allow you to understand the relative importance customers place on various attributes of a credit card and will help inform. design choices that align closely with customer preferences.
The attributes and levels for this study were carefully chosen based on insights from both focus group discussions and depth interviews with industry experts (listed below).
|
Attribute
|
Attribute Levels
|
|
Brand
|
Mastercard, Visa, Discover
|
|
Late Fee
|
$0 fee, $10 fee, $25 fee
|
|
Interest (intro APR)
|
0% interest, 15% interest
|
|
Cashback
|
no cashback, 1% cashback
|
|
Credit Limit
|
$1,000, $3,000, $10,000
|
Through conjoint analysis, you will be able to break down each attribute’s contribution to the overall appeal of the credit card, allowing you to design features and packages that are most likely to succeed in the market.
To complete this assignment, you’ll need to use XLSTAT on the SU remote desktop (rds.syr.edu) to generate the design for the conjoint analysis questionnaire and conduct a conjoint analysis of the rating data collected from the sample of 5 customers. The responses are in the file CreditCardData.xls, which contains each customer's ratings of various credit card profiles based on different combinations of the specified features.
Part I: Designing a Conjoint Analysis Questionnaire
1. Log into the SU Remote Desktop
· Go to rds.syr.edu and log in using your SU credentials.
· Once logged in, open Excel with the XLSTAT add-in enabled.
2. Open the CreditCardData.xls File
· In Excel on the remote desktop, open CreditCardData.xls.
3. Generate the Conjoint Analysis Design
· Open a new worksheet in the Excel file to specify your attributes and levels. List each attribute and its levels in a table format.
· IMPORTANT: to ensure consistent designs for part II, please set a fixed random seed for XLSTAT via Menu >Options>Data>Fix the seed to 123456789>Save. This will lock the random seed at 123456789, providing reproducible results.
· go to XLSTAT > Advanced Features> Conjoint Analysis > Design for Conjoint analysis.
· A dialog box will appear where you can select:
o Factors/Categories Table: Highlight the table with the attributes and levels you just created.
o Maximum Number of Profiles: Enter 18 for the maximum number of profiles.
o Number of Respondents: Enter 5 to match the number of survey respondents.
o Make sure to check “Variable Labels” to indicate that the first row of your table contains attribute names.
· Click OK to generate the design. XLSTAT will produce a table with 18 profile combinations for use in the survey.
4. Design a credit card questionnaire using the template provided (“HW4 Rating-based Conjoint_creditcard.doc”).
· Open the template file HW4 Rating-based Conjoint_creditcard.doc.
· Copy each profile generated by XLSTAT (from the optimized table in the previous step) into the template, filling in the 18 credit card profiles with the corresponding feature levels.
· For each profile, ensure it lists the attribute levels for Brand, Late Fee, Interest, Cashback, and Credit Limit as shown in the XLSTAT design output.
Part II: Conducting a Conjoint Analysis
1. Set Up the Conjoint Analysis for Rating Data
· In Excel on the remote desktop, open CreditCardData.xls.
· Copy Ratings: In the CJT design tab, locate the section titled Designs for conjoint analysis (optimized). Copy and paste the ratings from 5 customers (Individual 1 to Individual 5) into this section.
2. Run the Conjoint Analysis for Rating data
· Following the step above, click “Run the analysis.”
· In the dialog box, please select the response type as “Rating.”
· Make sure to check “Variable Labels” to indicate that the first row of your table contains attribute names.
Part III: Predicting Customer Choices and Market Share
Based on the results, please answer the questions below.
1. What are the part-worths for each attribute for each of the 5 customers?
2. What is the relative importance of each attribute for each of the 5 customers?
3. What is the overall (market-level) relative importance of each attribute? List the attributes from most important to least important.
4. Which credit card would Customer 1 choose? Show your utility calculations.
o Card A: Discover, $10 fee, 15% interest, 1% cash back, $10,000
o Card B: Visa, $25 fee, 0% interest, 0% cash back, $3000
5. Which credit card would Customer 5 choose? Show your utility calculations.
o Card A: Discover, $10 fee, 15% interest, 1% cash back, $10,000
o Card B: Visa, $25 fee, 0% interest, 0% cash back, $3000
6. What are the market shares (out of these 5 individuals) of card A and card B? Show your work.
o Card A: Discover, $10 fee, 15% interest, 1% cash back, $10,000
o Card B: Visa, $25 fee, 0% interest, 0% cash back, $3000