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Project Funny Munny
Market Research Analytics
Team members:1) Devawrat S. Bhave - A150102) Kamalika Some – A150122) Soumyadip Majumder - A150273) Varun Gopathi - A150304) Vibhu Singh - A15032
Agenda
• Customer profiling of loan-takers.• Customer behavioural profiling of loan-takers.• Customer attributes driving Satisfaction &
Hierarchy of Attributes.• Customer Psychographic Segmentation.
Customer profiling of loan-takers• Sample size= 1164
Zone wise Profiling
Zones North South East West Overall
Grand total 17.7% 26.5% 33.8% 22.2% 100%
Educational Level (Figures in %)
Educational Level North South East West Overalllliterate 1.53 1.56 1.45 1.3 5.84
Literate, but no formal education2.29 2.34 1.93 6.17 12.73
Up to Class 42.29 2.73 2.9 1.62 9.54
Class 4 – Class 912.98 23.44 12.56 11.36 60.34
SSC/HSC26.72 28.91 22.22 25 102.85
HSC+, but not graduate (Diploma etc.)17.05 11.33 16.43 19.48 64.29
Graduate / Post graduate (General - BA, MA, B.Sc.etc.)
31.3 28.13 37.68 31.17 128.28Graduate / Post graduate (Professional –
B.E, B. Tech, M.B.B.S, etc.)
5.85 1.56 4.83 3.9 16.14Grand Total 100 100 100 100 400.00
Customer profiling of loan-takers Occupation Level (Figures in %)
Occupation TypeEast West North South Overall
Unskilled manual worker 1.53 1.17 6.76 2.68 12.14Skilled manual worker
15.27 8.59 12.08 11.89 47.83Small trader 16.79 22.36 6.76 8.34 54.25Shop Owner 3.31 6.25 5.8 3.59 18.95
Businessman / Industrialist -with no employees
11.7 23.05 9.18 8.81 52.74Businessman / Industrialist -with less than
10 employees8.65 7.81 6.76 11.24 34.46
Businessman / Industrialist -with more than 10 employees
2.8 2.34 0 2.92 8.06Self Employed Professional 32.77 20.79 38.64 42.56 134.76
Clerk / Salesman 1.78 0.78 0.97 0.34 3.87Supervisor
1.78 0.78 0.97 0.34 3.87Officer / Executive – Junior level
2.54 1.56 2.42 2.92 9.44Officer / Executive – Middle / Senior level
1.53 3.52 9.66 4.47 19.18Grand Total 100.00 100.00 100.00 100.00 400.00
Customer profiling of loan-takers Regular Income (Figures in %)
Income Earned East West North South OverallYes
79.9 81.64 95.65 72.08 109.02No
20.1 18.36 4.35 27.92 70.73 Grand Total
100 100 100 100 400
Annual House-Hold Income (Figures in %)
Income Group East West North South OverallLess than 75,000
5.85 4.69 4.83 3.9 19.2775,000 – 1,50,000 15.52 20.7 14.98 18.18 69.381,50,001 – 3,00,000
37.66 37.89 37.68 40.58 153.813,00,001 – 5,00,000
27.23 26.95 28.02 26.3 108.5More than 5,00,000 13.74 9.77 14.49 11.04 49.04Grand Total 100 100 100 100 400
Customer profiling of loan-takersImmovable property
(Figures in %)
Agricultural Land East West North South OverallYes
52.16 40.63 33.82 43.18 169.78
No 47.84 59.38 66.18 56.82 230.22Grand Total
100 100 100 100 400
Immovable property
(Figures in %)
Residential Plots East West North South OverallYes
37.37 35.16 29.47 47.73 147.73
No 64.63 64.84 70.53 52.27 252.27Grand Total
100 100 100 100 400
Customer profiling of loan-takersImmovable property
(Figures in %)
Pucca House East West North South OverallYes
51.65 51.56 59.42 31.49 194.12
No 48.35 48.44 40.58 68.51 205.88Grand Total
100 100 100 100 400
Immovable property (Figures in %)
Kutcha House East West North South OverallYes
0.76 1.95 6.28 2.6 11.59
No 99.24 98.05 93.72 97.4 388.41Grand Total
100 100 100 100 400
Customer profiling of loan-takersImmovable property
(Figures in %)
Shops East West North South OverallYes
5.09 1.95 4.83 6.17 18.04
No 94.91 98.05 95.17 93.83 381.96Grand Total
100 100 100 100 400
Immovable property (Figures in %)
Others East West North South OverallYes
3.05 9.77 3.38 3.9 20.1
No 96.95 90.23 96.62 96.1 379.9Grand Total
100 100 100 100 400
Customer behavioural profilingCustomer Loan-taking behaviour (Figures in %)
Parameter East West North South
Which loan did you taken in last 2 years?
Crop 11.95 6.64 2.90 8.76Livestock 0.25 0.39 0.48 0.65Vehicle 79.13 81.25 77.78 59.74
Gold 1.01 0.78 2.90 13.96Education 0.50 0.00 0.00 0.32Housing 5.60 3.52 10.62 8.44Personal 1.27 3.52 3.38 7.14Others 0.29 3.90 1.93 0.99
Total % 100 100 100 100
Loan amount taken
<=1,00,000 10.94 6.25 19.32 19.801,00,001– 3,00,000 25.44 26.56 25.12 25.64
3,00,001 – 5,00,000 23.15 20.70 19.81 20.78
5,00,001- 10,00,000 20.61 30.85 22.22 21.43
>10,00,000 19.86 15.64 13.53 12.35Total % 100 100 100 100
Repayment tenure
<3 yrs 32.06 16.80 24.15 34.743 – 5 yrs 58.01 68.36 64.25 51.94
5 – 10 yrs 7.12 12.50 6.28 8.11>10 yrs 2.81 2.34 5.31 5.21
Total % 100 100 100 100
Loan-taking behaviour by North India vs South India
* Cells highlited in Yellow Color:Those cells are of range where there is a significant difference and no overlapping ( At 95% CI)
Loan-taking behaviour by North India vs South India
* Cells highlited in Yellow Color: Those cells are of range where there is a significant difference and no overlapping ( At 95% CI)
Customer attributes driving Satisfaction & Hierarchy of Attributes
MODEL I
Customer attributes driving Satisfaction & Hierarchy of Attributes
• Model I shows that the 5 independent variables explain 84.02% variation in the dependent variable
• The estimate for Q19 A-Time taken for your loan application processing is the highest at 70.42% indicating it is the most imp factor
• For Q19 B-Documentation and proof requirements the P value is 0.153 indicating it is not that significant in our model so we need to build a model removing this variable
Ques No Attributes EstimatesHierarchy of Attribute
Importance
19 ATime taken for your loan application processing
0.70402 I
19 BDocumentation and proof requirements
0.02638 V
19 CTimely disbursement of funds
0.06347 III
19 DLoan collection process
0.05444 IV
19 ECustomer service
0.15091 II
Customer attributes driving Satisfaction & Hierarchy of Attributes
MODEL II
Customer attributes driving Satisfaction & Hierarchy of Attributes• Model II shows that the 4 independent variables explain 84.01% variation in the dependent variable • Attribute Q19 B-Documentation and proof requirements the estimate is off loaded from the model. • The estimate for Q19 A-Time taken for your loan application processing has increased to 71.35%• The Overall Rsquare is .8406 and Multiple R squared is .8401 indicating no significant drop of the model fit.
Ques No Attributes EstimatesHierarchy of Attribute
Importance
19 A
Time taken for your loan application processing
0.7135 I
19 CTimely disbursement of funds
0.07075 III
19 DLoan collection process
0.05719 IV
19 ECustomer service
0.15295 II
Customer Psychographic Segmentation•Optimal number of components or factors to retain , through Eigen Values and Parallel Analysis.
5 Optimal Factors Extracted through the Scree Plot.
Customer Psychographic Segmentation5 Segmentation Breaking up of Factors.
Factor 1: 1.76. Factor 2: 1.82. Factor 3: 1.42. Factor 4: 1.39. Factor 5: 1.29.
Clustering can be done and data can be segmented based on factors we have derived
Customer Psychographic Segmentation
Young/Bachelors
Launchers
Full Nest I
Full Nest II
Empty Nest
Customer Psychographic Segmentation Attributes & 5 Factor Explanation.
End of Presentation
Thank- You!