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CUSTOMER PROFILING FOR
RURAL FINANCIAL SERVICES
Presented by :
Maruthi Nataraj
Sudhanshu Ranjan
Santosh Koppada
Madhumita ...
AGENDA
• INTRODUCTION
• DATA DESCRIPTION & PREPARATION
• METHODOLOGY
• ANALYSIS & INFERENCES
• RECOMMENDATION
INTRODUCTION
We, SSRM consultants were approached by leading financial
company that required profiling of customers in rur...
DATA DESCRIPTION & PREPARATION
Data Description:
 Dataset contains 1917 responses taken from respondents residing in rura...
METHODOLOGY
• We have used cluster analysis for customer profiling.
• Two cluster have been formed as per customer prefere...
ANALYSIS & INFERENCES
0%
5%
10%
15%
20%
25%
30%
35%
40%
East North South West
Percentage
Zone
Respondent Location
Segment ...
ANALYSIS & INFERENCES
0% 5% 10% 15% 20% 25% 30% 35%
Class 4 – Class 9
Graduate / Post graduate (General - BA, MA, B.Sc. et...
ANALYSIS & INFERENCES
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
18 to 25
yrs
26 to 25
yrs
36 to 45
yrs
46 to 55
yrs
56 to 65
y...
ANALYSIS & INFERENCES
0% 5% 10% 15% 20% 25% 30%
Bz/Ind <10 Emp
Bz/Ind >10 Emp
Bz/Ind 0 Emp
Clerk / Salesman
Officer / Exec...
ANALYSIS & INFERENCES
0% 20% 40% 60%
Television ads
Newspaper ads
Agents
Television ads Newspaper ads Agents
Segment 2 12....
ANALYSIS & INFERENCES
0% 5% 10% 15%
Agriculture purpose
New business /shop
setup
Construction or
purchase of house
Agricul...
Segment 1 mainly deals with agricultural activities and could be targeted for crop loans, gold
loans, livestock loans etc....
THANK YOU
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Customer Profiling For Rural Financial Services

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To design a comprehensive model to categorize the customers according to demographic perspective to assess their financial services requirements.

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Customer Profiling For Rural Financial Services

  1. 1. CUSTOMER PROFILING FOR RURAL FINANCIAL SERVICES Presented by : Maruthi Nataraj Sudhanshu Ranjan Santosh Koppada Madhumita Ghosh Rohit Kumar Ayan Das
  2. 2. AGENDA • INTRODUCTION • DATA DESCRIPTION & PREPARATION • METHODOLOGY • ANALYSIS & INFERENCES • RECOMMENDATION
  3. 3. INTRODUCTION We, SSRM consultants were approached by leading financial company that required profiling of customers in rural and semi-urban areas to identify their target market for extending loans and also to design marketing strategies to achieve other key benefits to the organization. Objective: To design a comprehensive model to categorize the customers according to demographic perspective to assess their financial services requirements. Customer Profiling Targeting Positioning
  4. 4. DATA DESCRIPTION & PREPARATION Data Description:  Dataset contains 1917 responses taken from respondents residing in rural and semi-urban areas spread across pan India  490 attributes, both numerical and categorical attributes  No missing values Preparation:  All the respondent data who have not answered(6) a single question were removed  All the no responses(6) at attribute level were replaced by respective mode  All the neutral responses at respondent level were removed  For Cluster analysis we have used total 16 variable(Q38- Q53) with 1816 responses Tools Used: SPSS, MS Excel 2013
  5. 5. METHODOLOGY • We have used cluster analysis for customer profiling. • Two cluster have been formed as per customer preferences like loan repayment, loan availed, banks visited, etc. Sl. No. Mean Std. Deviation Q38 3.504 1.0964 Q39 3.453 .9936 Q40 3.651 .9599 Q41 3.195 1.0268 Q42 2.765 1.0909 Q43 3.067 1.0725 Q44 3.463 .9305 Q45 3.813 .8425 Q46 3.539 .8812 Q47 3.485 .9174 Q48 3.604 .9284 Q49 3.433 .9897 Q50 3.775 .7564 Q51 3.758 .7873 Q52 3.640 .8951 Q53 3.797 .8806 Low Income Clusters Agriculture More Educated Working Professional
  6. 6. ANALYSIS & INFERENCES 0% 5% 10% 15% 20% 25% 30% 35% 40% East North South West Percentage Zone Respondent Location Segment 1 Segment 2
  7. 7. ANALYSIS & INFERENCES 0% 5% 10% 15% 20% 25% 30% 35% Class 4 – Class 9 Graduate / Post graduate (General - BA, MA, B.Sc. etc.) Graduate / Post graduate (Professional – B.E, B. Tech, M.B.B.S, etc.) HSC+, but not graduate (Diploma etc.) Illiterate Literate, but no formal education Not answered SSC/HSC Up to Class 4 Education Segment 2 Segment 1
  8. 8. ANALYSIS & INFERENCES 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 18 to 25 yrs 26 to 25 yrs 36 to 45 yrs 46 to 55 yrs 56 to 65 yrs 66 and above yrs Percentage Age Group Respondent Age Segment 1 Segment 2 0% 5% 10% 15% 20% 25% Salary Tuition income etc Agriculture income Rental income (shop etc.) Percentage Source Repay Loan sources Segment 1 Segment 2
  9. 9. ANALYSIS & INFERENCES 0% 5% 10% 15% 20% 25% 30% Bz/Ind <10 Emp Bz/Ind >10 Emp Bz/Ind 0 Emp Clerk / Salesman Officer / Executive – Jr Officer / Executive – Mid/Sr Self Employed Professional Shop Owner Skilled manual worker Small trader Supervisor Unskilled manual worker Respondent Occupation Segment 2 Segment 1 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Single instalment (end) Weekly instalment Monthly instalment / EMI Yearly instalment Percentage Repay Option Repay loan options Segment 1 Segment 2 City Segment 1 City Segment 2 Aligarh 61 Chennai 65 Gorakhpur 54 Indore 47 Siliguri 50 Kolkata 36 Durgapur 35 Jaipur 27 Vijayawada 31 Trichy 24
  10. 10. ANALYSIS & INFERENCES 0% 20% 40% 60% Television ads Newspaper ads Agents Television ads Newspaper ads Agents Segment 2 12.49% 8.97% 44.04% Segment 1 9.84% 9.84% 49.95% Information about Loans 0.00% 2.00% 4.00% 6.00% 8.00% House Segment 1 4.71% Segment 2 7.59% Property mortgaged to get Loan 0% 1% 2% 3% 4% 5% 6% 7% 8% Crop Loan Education Loan Housing Loan Segment 1 6.63% 0.11% 5.13% Segment 2 4.54% 0.57% 7.72% Type of Loan requirement
  11. 11. ANALYSIS & INFERENCES 0% 5% 10% 15% Agriculture purpose New business /shop setup Construction or purchase of house Agriculture purpose New business /shop setup Construction or purchase of house Segment 2 9.99% 7.95% 11.01% Segment 1 13.05% 12.19% 8.98% Immediate requirement of Loan 0% 5% 10% 15% 20% 25% 30% Loan Amount (INR) willing to avail Segment 1 Segment 2
  12. 12. Segment 1 mainly deals with agricultural activities and could be targeted for crop loans, gold loans, livestock loans etc.  As it includes low salaried employees like manual workers, self employed professionals, junior level employees, we can make them use of the banking resources by creating more awareness.  As the television viewership is low among them other media like local newspapers, banners/hoardings etc. should be used. Campaigns can also contribute in people- turn up to banks.  Since the repayment is dependent on agricultural income to certain extent, suitable time period is to be fixed taking crop seasons into consideration. Segment 2 focuses on people who relate to personal activities like construction of house, mortgaging property for regular pension etc.  They can be targeted with high ticket loans such as a housing loan, mortgage loan etc. and proper appraisal has to be carried out by checking their CIBIL score etc. in order to avoid the defaults.  At the same time, they need a quality service from the staff which is an important area to be taken care of. RECOMMENDATIONS
  13. 13. THANK YOU

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