Crew’s Cup

Case Discussion

A capstone case on quantitative customer research.

Presented by:
Larry Vincent,
Professor of the Practice
of Marketing
Presented to:
MKT 512
April 28, 2026

Results of Experiment

ANOVA

contrast estimate conf.low conf.high adj.p.value
Ad-Control 0.25 0.05 0.46 0.01
New Product-Control 0.90 0.70 1.10 0.00
Subscription-Control 1.20 0.99 1.40 0.00
New Product-Ad 0.65 0.44 0.85 0.00
Subscription-Ad 0.94 0.74 1.15 0.00
Subscription-New Product 0.30 0.09 0.50 0.00

Regression

Intent ~ Treatment

term estimate std.error statistic p.value
(Intercept) 3.95 0.06 71.60 0.00
TreatmentAd 0.25 0.08 3.25 0.00
TreatmentNew Product 0.90 0.08 11.39 0.00
TreatmentSubscription 1.20 0.08 15.03 0.00
R Squared: 0.162

Committment Factors

Theory

Published Evidence

What do we expect to find?

Factor structure

 

Factor structure

Exploratory factor analysis
variable uniqueness fl1 fl2 fl3 fl4 fl5
a1 0.277 0.074 0.037 0.846 −0.010 −0.035
a2 0.067 0.004 −0.087 0.960 −0.058 −0.016
a3 0.266 0.070 −0.019 0.852 −0.024 −0.055
n1 0.365 −0.142 −0.146 −0.044 −0.018 0.769
n2 0.057 −0.061 −0.120 −0.012 −0.038 0.961
n3 0.378 −0.120 −0.180 −0.053 −0.053 0.755
e1 0.240 0.128 0.833 −0.039 0.143 −0.166
e2 0.078 0.134 0.928 −0.007 0.097 −0.181
e3 0.268 0.161 0.824 −0.019 0.083 −0.143
f1 0.203 0.877 0.122 0.045 0.019 −0.103
f2 0.045 0.963 0.090 0.078 −0.003 −0.117
f3 0.173 0.871 0.214 0.047 0.043 −0.134
h1 0.246 0.039 0.255 −0.072 0.821 −0.091
h2 0.211 0.045 −0.015 0.029 0.886 −0.018
h3 0.214 −0.025 0.094 −0.055 0.879 −0.010

Reliability

Reliability Raw Scores
factor raw_alpha std.alpha
forced 0.94 0.95
habit 0.90 0.90
economic 0.92 0.92
affective 0.92 0.92
normative 0.88 0.88
Alpha Drops
variable raw_alpha std.alpha
forced
f1 0.93 0.93
f2 0.89 0.89
f3 0.93 0.93
habit
h1 0.87 0.87
h2 0.85 0.85
h3 0.84 0.84
economic
e1 0.90 0.90
e2 0.84 0.84
e3 0.91 0.91
affective
a1 0.90 0.90
a2 0.84 0.84
a3 0.89 0.90
normative
n1 0.86 0.86
n2 0.77 0.77
n3 0.87 0.87

Commitment Drivers Overall

Honest statistical differences

ANOVA with Tukey's HSD
contrast null.value estimate conf.low conf.high adj.p.value
economic-affective 0.00 −1.13 −1.26 −0.99 0.00
forced-affective 0.00 −1.36 −1.50 −1.23 0.00
habit-affective 0.00 −1.31 −1.45 −1.18 0.00
normative-affective 0.00 −1.12 −1.26 −0.99 0.00
forced-economic 0.00 −0.24 −0.37 −0.10 0.00
habit-economic 0.00 −0.18 −0.32 −0.05 0.00
normative-economic 0.00 0.01 −0.13 0.14 1.00
habit-forced 0.00 0.05 −0.08 0.19 0.84
normative-forced 0.00 0.24 0.11 0.38 0.00
normative-habit 0.00 0.19 0.05 0.32 0.00

Commitment Correlations

Intent based on committment

Drivers Only
(Intercept) 2.846 (0.227)***
Affective 0.136 (0.025)***
Normative -0.019 (0.027)
Economic 0.128 (0.019)***
Habit 0.103 (0.026)***
Forced 0.058 (0.022)**
Num.Obs. 1500
R2 0.089
R2 Adj. 0.086
F 29.257

New model

Drivers Only Drivers + Treatment
Affective 0.14*** 0.14***
Normative -0.02 -0.02
Economic 0.13*** 0.12***
Habit 0.10*** 0.09***
Forced 0.06** 0.06**
TreatmentAd 0.23**
TreatmentNew Product 0.86***
TreatmentSubscription 1.18***
Num.Obs. 1500 1500
R2 0.089 0.247
R2 Adj. 0.086 0.243
F 29.257 61.296

What about the segmentation?

Segmentation

Committment variables only

Characteristics by cluster

Another view

Key Statistics

Cluster N Gross Profit Mean Profit Mean Tenure Total Classes Profit/Ride-Year Margin
1-Faithful 372 $1,547,984 $4,161 9.0 151,515 $464.30 34%
2-Fitness 509 $983,405 $1,932 5.1 91,290 $378.09 36%
3-Bargain 619 $278,488 $450 1.7 29,441 $260.27 32%

Clusters & Treatments

Treatment Only Clusters + Treatment
TreatmentAd 0.25** 0.95***
TreatmentNew Product 0.90*** -0.61***
TreatmentSubscription 1.20*** 0.07
ClusterFaithful -0.28*
ClusterBargain -1.80***
TreatmentAd × ClusterFaithful -1.51***
TreatmentNew Product × ClusterFaithful 1.51***
TreatmentSubscription × ClusterFaithful 0.10
TreatmentAd × ClusterBargain -0.56***
TreatmentNew Product × ClusterBargain 2.26***
TreatmentSubscription × ClusterBargain 2.59***
Num.Obs. 1500 1500
R2 0.164 0.533
R2 Adj. 0.162 0.530
F 97.536 154.689

Why didn’t I include the drivers in this model?

Exploring other influences

Treatment Only Clusters Clusters + Tenure Clusters + CSAT
TreatmentAd 0.25** 0.95*** 0.95*** 0.96***
TreatmentNew Product 0.90*** -0.61*** -0.60*** -0.60***
TreatmentSubscription 1.20*** 0.07 0.08 0.08
ClusterFaithful -0.28* -0.40*** -0.38***
ClusterBargain -1.80*** -2.04*** -1.86***
TreatmentAd × ClusterFaithful -1.51*** -1.51*** -1.52***
TreatmentNew Product × ClusterFaithful 1.51*** 1.48*** 1.50***
TreatmentSubscription × ClusterFaithful 0.10 0.08 0.08
TreatmentAd × ClusterBargain -0.56*** -0.56*** -0.57***
TreatmentNew Product × ClusterBargain 2.26*** 2.24*** 2.23***
TreatmentSubscription × ClusterBargain 2.59*** 2.58*** 2.59***
Tenure -0.03*
CSAT 0.07***
Num.Obs. 1500 1500 1500 1500
R2 0.164 0.533 0.535 0.537
R2 Adj. 0.162 0.530 0.531 0.534
F 97.536 154.689 142.704 143.906

On brand relationships

A personal story

A personal story

A personal story

Cult initiation

Relationships

Culture = Brand

Stress tests

 

Stress tests

Service Profit Chain

Source: Heskett, Sasser, and Schlesinger, 1994

The real troubles in your life are apt to be things that never crossed your worried mind. The kind that blindside you at 4 p.m. on some idle Tuesday.

Mary Schmich

Wear Sunscreen Speech, Chicago Tribune

A strong brand exceeds expectations through experience… but resonates in absence.