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Project
Funny Munny
Market Research Analytics
Team members:
1) Devawrat S. Bhave - A15010
2) Kamalika Some – A15012
2) Soumyadip Majumder - A15027
3) Varun Gopathi - A15030
4) 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 Overall
lliterate 1.53 1.56 1.45 1.3 5.84
Literate, but no formal education
2.29 2.34 1.93 6.17 12.73
Up to Class 4
2.29 2.73 2.9 1.62 9.54
Class 4 – Class 9
12.98 23.44 12.56 11.36 60.34
SSC/HSC
26.72 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 31.17 128.28
Graduate / Post graduate (Professional –
B.E, B. Tech, M.B.B.S, etc.)
5.85 1.56 4.83 3.9 16.14
Grand Total 100 100 100 100 400.00
 Customer profiling of loan-takers
Occupation Level (Figures in %)
Occupation Type
East West North South Overall
Unskilled manual worker 1.53 1.17 6.76 2.68 12.14
Skilled manual worker 15.27 8.59 12.08 11.89 47.83
Small trader 16.79 22.36 6.76 8.34 54.25
Shop Owner 3.31 6.25 5.8 3.59 18.95
Businessman / Industrialist -with no
employees
11.7 23.05 9.18 8.81 52.74
Businessman / Industrialist -with less than
10 employees
8.65 7.81 6.76 11.24 34.46
Businessman / Industrialist -with more than
10 employees 2.8 2.34 0 2.92 8.06
Self Employed Professional 32.77 20.79 38.64 42.56 134.76
Clerk / Salesman 1.78 0.78 0.97 0.34 3.87
Supervisor 1.78 0.78 0.97 0.34 3.87
Officer / Executive – Junior level
2.54 1.56 2.42 2.92 9.44
Officer / Executive – Middle / Senior level
1.53 3.52 9.66 4.47 19.18
Grand 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 Overall
Yes
79.9 81.64 95.65 72.08 109.02
No
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 Overall
Less than 75,000
5.85 4.69 4.83 3.9 19.27
75,000 –
1,50,000 15.52 20.7 14.98 18.18 69.38
1,50,001 –
3,00,000 37.66 37.89 37.68 40.58 153.81
3,00,001 –
5,00,000 27.23 26.95 28.02 26.3 108.5
More than
5,00,000 13.74 9.77 14.49 11.04 49.04
Grand Total 100 100 100 100 400
 Customer profiling of loan-takers
Immovable property
(Figures in %)
Agricultural Land East West North South Overall
Yes
52.16 40.63 33.82 43.18 169.78
No 47.84 59.38 66.18 56.82 230.22
Grand Total
100 100 100 100 400
Immovable property
(Figures in %)
Residential Plots East West North South Overall
Yes
37.37 35.16 29.47 47.73 147.73
No 64.63 64.84 70.53 52.27 252.27
Grand Total
100 100 100 100 400
 Customer profiling of loan-takers
Immovable property
(Figures in %)
Pucca House East West North South Overall
Yes
51.65 51.56 59.42 31.49 194.12
No 48.35 48.44 40.58 68.51 205.88
Grand Total
100 100 100 100 400
Immovable property
(Figures in %)
Kutcha House East West North South Overall
Yes
0.76 1.95 6.28 2.6 11.59
No 99.24 98.05 93.72 97.4 388.41
Grand Total
100 100 100 100 400
 Customer profiling of loan-takers
Immovable property
(Figures in %)
Shops East West North South Overall
Yes
5.09 1.95 4.83 6.17 18.04
No 94.91 98.05 95.17 93.83 381.96
Grand Total
100 100 100 100 400
Immovable property
(Figures in %)
Others East West North South Overall
Yes
3.05 9.77 3.38 3.9 20.1
No 96.95 90.23 96.62 96.1 379.9
Grand Total
100 100 100 100 400
 Customer behavioural profiling
Customer 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 8.76
Livestock 0.25 0.39 0.48 0.65
Vehicle 79.13 81.25 77.78 59.74
Gold 1.01 0.78 2.90 13.96
Education 0.50 0.00 0.00 0.32
Housing 5.60 3.52 10.62 8.44
Personal 1.27 3.52 3.38 7.14
Others 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 19.80
1,00,001–
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 12.35
Total % 100 100 100 100
Repayment tenure
<3 yrs 32.06 16.80 24.15 34.74
3 – 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 Estimates
Hierarchy of Attribute
Importance
19 A
Time taken for your loan application
processing 0.70402 I
19 B
Documentation and proof requirements
0.02638 V
19 C
Timely disbursement of funds
0.06347 III
19 D
Loan collection process
0.05444 IV
19 E
Customer 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 Estimates
Hierarchy of Attribute
Importance
19 A
Time taken for your loan
application processing 0.7135 I
19 C
Timely disbursement of funds
0.07075 III
19 D
Loan collection process
0.05719 IV
19 E
Customer 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 Segmentation
5 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!

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Market Research Analytics

  • 1. Project Funny Munny Market Research Analytics Team members: 1) Devawrat S. Bhave - A15010 2) Kamalika Some – A15012 2) Soumyadip Majumder - A15027 3) Varun Gopathi - A15030 4) Vibhu Singh - A15032
  • 2.  Agenda • Customer profiling of loan-takers. • Customer behavioural profiling of loan-takers. • Customer attributes driving Satisfaction & Hierarchy of Attributes. • Customer Psychographic Segmentation.
  • 3.  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 Overall lliterate 1.53 1.56 1.45 1.3 5.84 Literate, but no formal education 2.29 2.34 1.93 6.17 12.73 Up to Class 4 2.29 2.73 2.9 1.62 9.54 Class 4 – Class 9 12.98 23.44 12.56 11.36 60.34 SSC/HSC 26.72 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 31.17 128.28 Graduate / Post graduate (Professional – B.E, B. Tech, M.B.B.S, etc.) 5.85 1.56 4.83 3.9 16.14 Grand Total 100 100 100 100 400.00
  • 4.  Customer profiling of loan-takers Occupation Level (Figures in %) Occupation Type East West North South Overall Unskilled manual worker 1.53 1.17 6.76 2.68 12.14 Skilled manual worker 15.27 8.59 12.08 11.89 47.83 Small trader 16.79 22.36 6.76 8.34 54.25 Shop Owner 3.31 6.25 5.8 3.59 18.95 Businessman / Industrialist -with no employees 11.7 23.05 9.18 8.81 52.74 Businessman / Industrialist -with less than 10 employees 8.65 7.81 6.76 11.24 34.46 Businessman / Industrialist -with more than 10 employees 2.8 2.34 0 2.92 8.06 Self Employed Professional 32.77 20.79 38.64 42.56 134.76 Clerk / Salesman 1.78 0.78 0.97 0.34 3.87 Supervisor 1.78 0.78 0.97 0.34 3.87 Officer / Executive – Junior level 2.54 1.56 2.42 2.92 9.44 Officer / Executive – Middle / Senior level 1.53 3.52 9.66 4.47 19.18 Grand Total 100.00 100.00 100.00 100.00 400.00
  • 5.  Customer profiling of loan-takers Regular Income (Figures in %) Income Earned East West North South Overall Yes 79.9 81.64 95.65 72.08 109.02 No 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 Overall Less than 75,000 5.85 4.69 4.83 3.9 19.27 75,000 – 1,50,000 15.52 20.7 14.98 18.18 69.38 1,50,001 – 3,00,000 37.66 37.89 37.68 40.58 153.81 3,00,001 – 5,00,000 27.23 26.95 28.02 26.3 108.5 More than 5,00,000 13.74 9.77 14.49 11.04 49.04 Grand Total 100 100 100 100 400
  • 6.  Customer profiling of loan-takers Immovable property (Figures in %) Agricultural Land East West North South Overall Yes 52.16 40.63 33.82 43.18 169.78 No 47.84 59.38 66.18 56.82 230.22 Grand Total 100 100 100 100 400 Immovable property (Figures in %) Residential Plots East West North South Overall Yes 37.37 35.16 29.47 47.73 147.73 No 64.63 64.84 70.53 52.27 252.27 Grand Total 100 100 100 100 400
  • 7.  Customer profiling of loan-takers Immovable property (Figures in %) Pucca House East West North South Overall Yes 51.65 51.56 59.42 31.49 194.12 No 48.35 48.44 40.58 68.51 205.88 Grand Total 100 100 100 100 400 Immovable property (Figures in %) Kutcha House East West North South Overall Yes 0.76 1.95 6.28 2.6 11.59 No 99.24 98.05 93.72 97.4 388.41 Grand Total 100 100 100 100 400
  • 8.  Customer profiling of loan-takers Immovable property (Figures in %) Shops East West North South Overall Yes 5.09 1.95 4.83 6.17 18.04 No 94.91 98.05 95.17 93.83 381.96 Grand Total 100 100 100 100 400 Immovable property (Figures in %) Others East West North South Overall Yes 3.05 9.77 3.38 3.9 20.1 No 96.95 90.23 96.62 96.1 379.9 Grand Total 100 100 100 100 400
  • 9.  Customer behavioural profiling Customer 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 8.76 Livestock 0.25 0.39 0.48 0.65 Vehicle 79.13 81.25 77.78 59.74 Gold 1.01 0.78 2.90 13.96 Education 0.50 0.00 0.00 0.32 Housing 5.60 3.52 10.62 8.44 Personal 1.27 3.52 3.38 7.14 Others 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 19.80 1,00,001– 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 12.35 Total % 100 100 100 100 Repayment tenure <3 yrs 32.06 16.80 24.15 34.74 3 – 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
  • 10.  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)
  • 11.  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)
  • 12.  Customer attributes driving Satisfaction & Hierarchy of Attributes MODEL I
  • 13.  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 Estimates Hierarchy of Attribute Importance 19 A Time taken for your loan application processing 0.70402 I 19 B Documentation and proof requirements 0.02638 V 19 C Timely disbursement of funds 0.06347 III 19 D Loan collection process 0.05444 IV 19 E Customer service 0.15091 II
  • 14. Customer attributes driving Satisfaction & Hierarchy of Attributes MODEL II
  • 15. 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 Estimates Hierarchy of Attribute Importance 19 A Time taken for your loan application processing 0.7135 I 19 C Timely disbursement of funds 0.07075 III 19 D Loan collection process 0.05719 IV 19 E Customer service 0.15295 II
  • 16.  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.
  • 17. Customer Psychographic Segmentation 5 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
  • 19. Customer Psychographic Segmentation  Attributes & 5 Factor Explanation.
  • 20.  End of Presentation Thank- You!