Evaluating Insurance Marketing
Strategies through Data Mining
Spring 2016 – BIT 5534 Group Project
Group 3:
Thomas George
Shailesh Mittal
Lonnie Elrod Jr.
1
Business Objective
Business Strategy
Company’s business strategy to offer a wide range of insurance
policies mostly with higher end premiums which in turn returns
high benefits
Business Problem
The company needs to identify the correct demographic of
potential customers which can afford a higher premium offering
from a dataset of employee salaries from the city of San Francisco,
CA
2
Additional Problems to Explore
• Should the firm’s new insurance plans be marketed to previously held or current benefit
plans?
• Is there any different approach which can be adopted to sell insurance plans based on
nature of work one performs?
• Can we define customized schemes for different sets of employee groups?
• What group could be targeted first to maximize the success of the firm’s potential entry to
the market?
• Can we identify the premium policy price or prices?
3
Analytical Goal
• Bridge the gap between current action and
business strategy
• Identify the target audience
• Identify the predictive model of premium to
be offered for target audience
4
Data Description
5
Organization Group
Code
Group Name
Average total
compensation
Population size
1
Public Protection
$175,965.20
5,966
6
General Administration & Finance
$151,676.10
1,609
4
Community Health
$150,442.80
3,860
2
Public Works, Transportation & Commerce
$141,729.70
6,995
5
Culture & Recreation
$127,497.50
653
3
Human Welfare & Neighbourhood Development
$126,125.60
1,245
Group 1 Sub
No.
Department Name
Department Code
1
Superior Court
CRT
2
District Attorney
DAT
3
Department of Emergency Management
ECD
4
Fire Department
FIR
5
Juvenile Probation
JUV
6
Police
POL
7
Sheriff
SHF
Linear Regression Model
6
Linear Regression Model (continued)
7
Box Plot Interpretation
8
Leaf Report
9
Model Comparison
10
Conclusion
11
Future
12