To identify the hospitals’ segments with overall high sales. Then look for hospitals within that segment where the company sales of surgical equipments are low.

1. MARKET SEGMENTATION
Presented by
P Sunil Kumar (A13020)
Maruthi Nataraj K (A13009)
Praxis Business School, Kolkata

2. AGENDA
 Business background
 Objective
 Dataset
 Tools and Techniques
 Evaluation
 Analysis and Inferences
 Conclusions
 Future direction

3. BUSINESS BACKGROUND
 XYZ Surgical is the leading manufacturer, supplier and exporter of a
wide range of Orthopaedic Surgical Equipment.
 Orthopaedic Surgical Equipment
- Reasonable price
- Variety of options
 Products offered
- Bone plates
- Spinal system products
- Femur locking plates etc
 Products are manufactured under strictly quality control, sterile and
hygienic environment these are complete safe for these purposes.
 Have a list of satisfied and pleased customers based across major cities
in US market.

4. OBJECTIVE
 Business : To increase sales of
orthopaedic
equipment
from
XYZ
Surgical to hospitals in potential
markets of the United States.
 Analytical : To identify the hospitals’
segments with overall high sales. Then
look for hospitals within that segment
where the company sales are low.
 States identified are
California, Florida, Georgia and Texas.

5. DATASET
No of Variables – 19
No of Instances – 1150 (for states California (CA)
Florida (FL) ,Georgia (GA) and Texas (TX)
A teaching hospital is a hospital that
provides clinical education and training
to future and current
doctors, nurses, and other health
professionals, in addition to delivering
medical care to patients
Outpatient is one who is
not hospitalized
overnight but who visits a
hospital, clinic, or
associated facility for
diagnosis or treatment
A trauma centre is
a hospital equipped and staffed to
provide comprehensive emergency
medical services to patients
suffering traumatic injuries.
Inpatient Rehabilitation
Unit helps individuals who
have physical or cognitive
deficits to recover from
disease or injury
Ex: Brain, Spinal cord
Orthopedic injuries etc

6. DATASET

7. TOOLS AND TECHNIQUES
 Tools
 Technique
- Cluster Analysis

8. EVALUATION
Obtained using
Rapid Miner
X-means

9. EVALUATION

10. ANALYSIS AND INFERENCES
Cluster 0
 This is the segment where there the average sales is least with
lowest number of average operations and output patient visits.
 Even the average revenue from the inpatients is identified to
be lowest.
 Low average sales means that the hospitals in this segment
have few patients who would need our products. So, we are not
interested in them.
Type of Hospital units
100
80
60
40
20
0
TH
TRAUMA
CA
FL
GA
REHAB
TX

11. ANALYSIS AND INFERENCES
California has least average sales when though
the average no of operations are decent.
Cluster 0
Average Outpatient visits
Average Inpatient Revenue
25000
5000
20000
4000
15000
3000
10000
2000
5000
1000
0
0
CA
FL
GA
CA
TX
Average No of operations
in YR95
80
70
60
50
40
30
20
10
0
FL
GA
TX
Average Sales
35
30
25
20
15
10
5
0
HIP95
CA
KNEE95
FL
GA
TX
CA
FL
GA
TX

12. ANALYSIS AND INFERENCES
Cluster 1
Average Inpatient Revenue
10000
 This is a segment which has
got all the factors like no of
operations,
outpatient
visits, inpatient revenue etc
contributing to decent sales
(considering overall averages).
8000
6000
4000
2000
0
CA
Average Outpatient visits
160000
140000
120000
100000
80000
60000
40000
20000
0
CA
FL
GA
TX
FL
GA
TX

13. ANALYSIS AND INFERENCES
Cluster 1
In this segment, Texas
has least average sales
when though its average
no of operations are
higher.
Average no of operations
120
100
80
60
40
20
0
HIP96
KNEE96
CA
FL
GA
FEMUR96
Average Sales
TX
60
50
40
30
20
10
0
CA
FL
GA
TX

14. ANALYSIS AND INFERENCES
Cluster 2
 In this case, though it has highest number of outpatient visits
and administrative costs, we observe that average sales are not up
to the mark.
 It includes hospitals where most of them have trauma
units, teaching units and having highest average number of beds
also supports the same.
 One more aspect of this segments is that it has highest average
number of femur operations and also there is drop in number of
knee operations from YR95 to YR96.
 Decent revenues from inpatients hints towards being a potential
segment for equipment sales.

15. ANALYSIS AND INFERENCES
Cluster 3
 This particular segments has highest average sales where in
highest revenue from inpatients can be observed.
 Interestingly, majority of the hospitals here are teaching
hospitals.
 Greater number of hip and knee operations is also spotted.
No of hospitals with zero sales
6
5
4
3
2
1
0
CA
FL
GA
TX

16. CONCLUSIONS
From our analysis, we have chosen cluster 1 (segment) to increase
our sales because of following reasons :
 There has been a consistent demand for knee and hip
replacement implants in this segment contributing to the growth of
the market.
 As per the US census bureau, persons 65 years and
over, percent, 2012 in California ,Florida and Texas are 12%,18.2%
and 10.9% respectively leading most of them to opt for an
orthopaedic surgery due to osteoarthritis. There is a chance for
improvement of sales in hospitals where it is low in this cluster 1.
 California has been ranked as the most dangerous state for road
users in the US and also the incidence rate of sports injuries in the
younger population is growing across all other states.

17. CONCLUSIONS
 These states are witnessing the continued adoption of
innovative, premium-priced devices which is favourable factor for
increase in sales.
 Also , according to the American Academy of Orthopaedic
Surgeons, approximately 28.6 million people in the United States
sustain some type of musculoskeletal injury annually which is high
in these cities and will eventually trigger the necessity of quality
surgical equipments.

18. FUTURE DIRECTION
Dimension Reduction using
Factor Analysis
Fine Tuning of Cluster
Analysis using optimized
parameters
Regression Analysis to
determine the drivers for
sales

19. APPENDIX

20. APPENDIX

21. APPENDIX
Communality value for OUTV,TH and TRAUMA < 0.4.So,they are dropped.
(They are not contributing to formation of factors)

22. APPENDIX

23. APPENDIX

24. REFERENCES
 http://www.rci.rutgers.edu/~cabrera/sc/cs8/cs8.html
 www.nesug.org/Proceedings/nesug11/sa/sa11.pdf