Customer Satisfaction and Scaling in R
Estimated Time Commitment: 4 Hours
In this course we will introduce methods to measure and identify satisfied customers so that adjustments can be made to the product or service. To measure customer satisfaction we will measure customers’ expectations, customers’ perceived performance, and the disconfirmation of the offered product or service. Because there are a variety of ways to measure customer satisfaction, we will compare and contrast various measurement and scaling techniques.
Finally, we introduce Multidimensional Scaling (MDS). MDS is used in marketing to understand the pair-wise similarity of the individual cases (e.g., brands) of a data-set. This technique maps the individual cases onto a 2-dimensional Cartesian graph for visual analysis. This graph can then be analyzed to identify various marketing strategies, and potential product innovations.
Upon successful completion, you will be able to:
Develop an understanding of customer satisfaction and marketing analytics concepts
Interpret various components of measuring customer satisfaction.
Compare and contrast various measurement and scaling techniques
Identify opportunities to build and develop appropriate marketing strategies
Create a distance matrix, perform classical multidimensional scaling, and plot the results on a spatial distance graph
Introduction to Customer Satisfaction and Scaling
Introduction to the Skill
Glossary
Customer Satisfaction
Primary Scales of Measurement
Knowledge Check 1
Comparative Scaling
Non-Comparative Scaling
Multidimensional Scaling - Introduction
Knowledge Check 2
Conducting a Multidimensional Scaling Analysis
Multidimensional Scaling - R Example
Knowledge Check 3
Instructions
Exercise Files
Debriefing
Conclusion
Final Quiz
Survey Instructions
Feedback Survey
Survey Verification
Next Steps