1.
PJ’s CoffeeA Study of Consumer Satisfaction
and Dissatisfaction Factors

2.
Company Background
• 1978- Phyllis Jordan
• 65 Locations
• 20% growth in the last 2 years
• Top 100 Private Companies (2011)
ü New Orleans City Business
• Named Best Coffeehouse
ü New Orleans Magazine (2011)
ü Where Y’at Magazine (2011, 2012, 2014)
ü Gambit (2011, 2012,2013)

3.
PJ’s Customer
Satisfaction
Product Quality
Variety
Signature Iitems
Intensity
Price
Uniqueness
Quality
Atmosphere
Cleanliness
Wi-Fi
Music
Sitting
Attractiveness
Decor
Customer
Service
Experience
Friendly Staff
Professionalism
Speed of Service
Advertisement
Rewards
Program
PJ’s Hypothesis Model
Convenience
Parking
Close to
home/office
Drive-Thru
Location
Hours

4.
Instrument - Survey
• Paper and pencil
• PJ’s customers on site
• 100 samples
• Greater New Orleans Area
• Likert Scale: Strongly Disagree to Strongly Agree

5.
0
5
10
15
20
25
30
35
40
18-24 25-35 36-45 46-55 56-65 66+
19%
39%
17% 17%
6%
2%
#ofparticipants
Age Group
Age
41%
59%
Gender
Male Female
Sample Background

6.
Sample Background
0 5 10 15 20 25 30
Less than $25,000
$25,000-$45,000
$45,001-$65,000
$65,001+
18%
23%
30%
29%
# of participants
IncomeGroup
Income
0
5
10
15
20
25
30
35
40
45
0-1 Mile
2-5 Miles
6-10 Miles
11+ Miles
43%
41%
10%
6%#ofparticipants
Distance Group
Distance

7.
Factor & Reliability Analysis
Factor
Initial number
of items
Initial Cronbach’s
Alpha*
Number of
Dropped Items
Final Cronbach’s
Alpha
Average of
Good Items
Customer Service 6 .716a 1 .757 4.2540
Product Quality 6 .827 0 .827 4.0500
Convenience 5 .673b 1 .720 4.1950
Atmosphere 6 .731 0 .731 4.0497
Overall Satisfaction 7 .873 0 .873 4.1857
• When addressing the validity and reliability of our model, we discovered that the
items “Rewards Program” and “Parking” did not show meaningfulness or accuracy
when measuring factors customer service and convenience, respectively.
• Therefore, we decided to drop both items to minimize the error of our model.

8.
PJ’s Customer
Satisfaction
Product Quality
Variety
Signature Iitems
Intensity
Price
Uniqueness
Quality
Convenience
Close to
home/office
Drive-Thru
Locations
Hours
Atmosphere
Cleanliness
Wi-Fi
Music
Sitting
Attractiveness
Decor
Customer Service
Experience
Friendly Staff
Professionalism
Speed of Service
Advertisement
PJ’s Aggregated Model

9.
Multiple Regression Analysis
Criterion: Overall Satisfaction
• Predictors: Customer Service,
Product Quality, Convenience
and Atmosphere
The predictors, product
quality and convenience are
statistically significant.
Since both of them have
significant beta-weights, we
can conclude that they
matter when explaining the
variance in the criterion
variable, overall satisfaction.
Customer
Satisfaction
Customer
Service
Convenience
Atmosphere
Product
Quality
.101
.124
.175.549
𝐶𝑢𝑠𝑡𝑜𝑚𝑒𝑟 𝑆𝑎𝑡𝑖𝑠𝑓𝑎𝑐𝑡𝑖𝑜𝑛 = .077 + 0.545 𝑃𝑄 + 0.168 𝐶𝑂

10.
Multiple Regression Analysis
• Criterion: Overall Satisfaction
• Predictors: Customer Service, Product Quality, Convenience and
Atmosphere
Model Summary
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
1 .781a .609 .593 .44223
a. Predictors: (Constant), AT_SCALE, CS_SCALE, CO_SCALE, PQ_SCALE
R-square= .593; the proportion of variance in criterion (overall
satisfaction) explained by predictors (customer service, product
quality, convenience and atmosphere) is 59.3%.
Model is acceptable for
practical applications

11.
Qualitative Data Analysis
Gender
Overall
Satisfaction
Gender & Overall
Satisfaction
F-value= .464 P-value: .497
Conclusions
P-value > .05; failed to reject the Null.
There is no significant difference between Males and Females on
Overall Satisfaction.
Distance
Overall
Satisfaction
Distance & Overall
Satisfaction
F-value= 1.988 P-value: .121
Conclusions
P-value > .05; failed to reject the Null.
There is no difference in the means of overall satisfaction for the 4
distance groups.
It is inappropriate to interpret the difference in men and women’s means
because F-ratio was not significant. Statistically, the means are the same.
It is inappropriate to interpret the difference in distance group means
because F-ratio was not significant. Statistically, the means are the same.

12.
Qualitative Data Analysis
Gender & Income Chi- square= 3.446 P-value: .328
Conclusions
P-value > .05; failed to reject the Null.
There is no statistically significant relationship between Gender
and Income.
Null Hypothesis: There is no statistically significant relationship between
Gender and Income.
Alternative Hypothesis: Men are more likely to have a higher income
compared to women.
Gender & Distance Chi- square= 15.426 P-value: .080
Conclusions
P-value > .05; failed to reject the Null.
There is no statistically significant relationship between Gender
and Distance.
Null Hypothesis: There is no statistically significant relationship between
Gender and Distance.
Alternative Hypothesis: Men are more likely to be closer to a PJ’s Coffee Shop
compared to women.

13.
Open-Ended Questions
• From this information and from the open-ended question responses,
it is apparent that PJ’s needs to increase the hours of operation,
extend product selections (pastries, coffee and tea varieties) and
provide drive –thru options.
• Therefore, we can conclude that atmosphere and customer service
are important to the customer, but not as significant as product
quality and convenience.

14.
Conclusions
• Product Quality and Convenience are the two predictors that have a
direct, positive, and significant relationship with overall customer
satisfaction at PJ’s.
• The interpretation of the regression data allows us to infer that
customers are most satisfied at PJ’s coffee shops when products
have high quality, such as intensity of the coffee and offering
unique flavors.
• The data also allowed us to conclude that customers are most
satisfied when provided with adequate amenities or services at PJ’s
coffee shops.