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Customer Satisfaction/Loyalty Turna Koksal

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Page 1: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

Customer Satisfaction/Loyalty

Turna Koksal

Page 2: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

Goal

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

loyalty

Page 3: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

Domain

• Collection of answers given to survey questions by customers

• 6500 customer records • 174 attributes

Page 4: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

Method

• Association rules– Relationships among items in dataset

• WEKA– Apriori algorithm

Page 5: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

Implementation

• Data cleaning– MS Excel– Clean data (Derived attributes)

• Attribute selection– WEKA– Information gain algorithm

• Top 15 attributes (>0.15)

Page 6: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

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

Page 7: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

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

Page 8: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

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%

Page 9: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

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%

Page 10: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

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 %

Page 11: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

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%

Page 12: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

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%

Page 13: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

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%

&

Page 14: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

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%

Page 15: Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction

Next-Steps

• Try different methods and compare the results

• Spend more time on data cleaning, preparation and transformation