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Customer Satisfaction/Loyalty

Customer Satisfaction/Loyalty. Turna Koksal. Goal. Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction and loyalty. Domain. Collection of answers given to survey questions by customers 6500 customer records 174 attributes .

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Customer Satisfaction/Loyalty

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  1. Customer Satisfaction/Loyalty Turna Koksal

  2. Goal • Characterize the customer of a bank • Customer satisfaction • Customer loyalty • Relationship between satisfaction and loyalty

  3. Domain • Collection of answers given to survey questions by customers • 6500 customer records • 174 attributes

  4. Method • Association rules • Relationships among items in dataset • WEKA • Apriori algorithm

  5. Implementation • Data cleaning • MS Excel • Clean data (Derived attributes) • Attribute selection • WEKA • Information gain algorithm • Top 15 attributes (>0.15)

  6. Implementation (cont.) • Data transformation • Transform attributes into nominal values • Attribute values 1 to 7 and 99 • Group into 4: • {1,2,3}  1 • {4,5}  2 • {6,7}  3 • {99}  4 • Divide into 6 groups • Attribute QTA : A,B,C,D,E,F

  7. Implementation (cont.) • Data transformation • Divide data into training (70%) & testing (30%) • Transform training file into .arff format • Rule properties • Generate 20 rules for each group • Minimum confidence: 0.8 • Minimum support: 0.45

  8. Dataset Rule • Q2_01=3 ==> Q2_03=3   • Information on site arranged logically = {strongly agree, agree} • Trust bank to protect privacy & confidential info = {strongly agree, agree} Accuracy: 60.86%  

  9. Group A Rule • Q20=3 ==> Q2_03=3 • How satisfied with online services {extremely satisfied, very satisfied} • Trust bank to protect privacy & confidential info {strongly agree, agree} Accuracy: 53.83%  

  10. Group B Rule • Q2_01=3 ==> Q2_03=3  • Information on site arranged logically {strongly agree, agree} • Trust bank to protect privacy & confidential info {strongly agree, agree} Accuracy:62.98 %  

  11. Group C Rule • Q48=3 ==> Q49_02=3 • Overall satisfaction with bank {extremely satisfied, very satisfied} • Remain customer {extremely likely, very likely} Accuracy: 49.23%  

  12. Group D Rule • Q2_01=3  ==> Q2_03=3 • Information on site arranged logically {strongly agree, agree} • Trust bank to protect privacy & confidential info {strongly agree, agree} Accuracy: 58.12%  

  13. Group E Rule • Q2_01=3 Q2_06=3 ==> Q2_03=3 • Information on site arranged logically {strongly agree, agree} • bank.com helps me take charge of my finances {strongly agree, agree} • Trust bank to protect privacy & confidential info {strongly agree, agree} Accuracy: 54.29% &  

  14. Group F Rule • Q1_01=3  ==> Q49_02=3 • Web site overall {extremely satisfied,  very satisfied} • Remain customer {extremely likely, very likely} Accuracy: 51.22%  

  15. Next-Steps • Try different methods and compare the results • Spend more time on data cleaning, preparation and transformation

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