1. DB Marketing: Conjoint Analysis Project
Overview:
For the project I created a survey to help a ficticious online travel service understand which type of Hawaiian vacation would be
most appealing to prospective travellers. The vacation packages consisted of an island option (Maui or Kauai), type of
accomodation (hotel or condo), and activity (water sports or golf).
Vacation Package Options Offered In Survey
Each respondent was asked to rate each of the following packages (1 - 10), 10 being most appealing.
A Maui Hotel Golf
B Maui Hotel Water Sports
C Maui Condo Golf
D Maui Condo Water Sports
E Kauai Hotel Golf
F Kauai Hotel Water Sports
G Kauai Condo Golf
H Kauai Condo Water Sports
Option Coding
Island Accomodation Activity
Maui = 0 Hotel = 0 Golf = 0
Kauai = 1 Condo = 1 Water Sports = 1

2. Survey Results (13 respondents)
Aversage
Response (n=13)
A Maui Hotel Golf 4.08
B Maui Hotel Water Sports 6.31
C Maui Condo Golf 4.23
D Maui Condo Water Sports 6.15
E Kauai Hotel Golf 4.46
F Kauai Hotel Water Sports 6.69
G Kauai Condo Golf 4
H Kauai Condo Water Sports 6.23
Regression Analysis
Input
A 0 0 0 4.08
B 0 0 1 6.31
C 0 1 0 4.23
D 0 1 1 6.15
E 1 0 0 4.46
F 1 0 1 6.69
G 1 1 0 4
H 1 1 1 6.23

3. Utility Equation
U= 4.23 + 0.15*island + -.23*accomodation type + 2.15*activity
Maui, Hotel, Maui, Hotel, Maui, Condo, Maui, Condo, Kauai, Hotel, Kauai, Hotel, Kauai,
Golf Water Sports Golf Water Sports Golf Water Sports Condo, Golf
A B C D E F G
Intercept 4.23 1.00 1.00 1.00 1.00 1.00 1.00 1.00
island 0.15 0.00 0.00 0.00 0.00 1.00 1.00 1.00
Accomodations -0.23 0.00 0.00 1.00 1.00 0.00 0.00 1.00
Activity 2.15 0.00 1.00 0.00 1.00 0.00 1.00 0.00
Utility 4.23 6.38 4.00 6.15 4.38 6.54 4.15
Summary
The results of the conjoint analysis show that the optimal combination to market is a Kauai, water sports vacation with
accomodations at a hotel. A possible next step would be to propose a few combinations of this type of vacation at various
price points to determine the ideal package and price to offer.

4. Kauai,
Condo,
Water Sports
H
1.00
1.00
1.00
1.00
6.30

5. SUMMARY OUTPUT
Regression Statistics
Multiple R 0.99
R Square 0.99
Adjusted R Square 0.97
Standard Error 0.19
Observations 8.00
ANOVA
df SS MS F Significance F
Regression 3.00 9.42 3.14 90.01 0.00
Residual 4.00 0.14 0.03
Total 7.00 9.56
Standard Lower Upper Lower
Coefficients Error t Stat P-value 95% 95% 95.0% Upper 95.0%
Intercept 4.23 0.13 32.05 0.00 3.87 4.60 3.87 4.60
X Variable 1 0.15 0.13 1.15 0.31 -0.21 0.52 -0.21 0.52
X Variable 2 -0.23 0.13 -1.76 0.15 -0.60 0.13 -0.60 0.13
X Variable 3 2.15 0.13 16.30 0.00 1.79 2.52 1.79 2.52