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
November 13, 2025

Results of Experiment

ANOVA

contrast estimate conf.low conf.high adj.p.value
Ad-Control 0.13 −0.05 0.32 0.25
New Product-Control 0.37 0.18 0.55 0.00
Subscription-Control 0.23 0.04 0.41 0.01
New Product-Ad 0.24 0.05 0.42 0.00
Subscription-Ad 0.09 −0.09 0.27 0.54
Subscription-New Product −0.14 −0.32 0.04 0.17

Regression

Intent ~ Treatment

term estimate std.error statistic p.value
(Intercept) 3.98 0.05 77.42 0.00
treatmentAd 0.13 0.07 1.85 0.06
treatmentNew Product 0.37 0.07 5.15 0.00
treatmentSubscription 0.23 0.07 3.20 0.00
R Squared: 0.017

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 0.161 −0.048 0.056 0.913 −0.023 −0.001
a2 0.263 0.297 −0.147 0.786 0.091 0.033
a3 0.318 −0.119 0.090 0.812 0.023 0.008
n1 0.218 −0.097 0.876 0.061 −0.016 −0.016
n2 0.154 −0.122 0.908 0.057 −0.040 −0.044
n3 0.109 −0.054 0.938 −0.090 −0.011 0.024
e1 0.101 0.839 −0.178 0.165 0.370 0.005
e2 0.086 0.847 −0.118 0.197 0.377 −0.037
e3 0.065 0.854 −0.194 0.191 0.364 −0.005
f1 0.080 0.894 −0.125 0.041 0.005 0.323
f2 0.085 0.901 −0.082 0.007 −0.025 0.310
f3 0.085 0.870 −0.136 0.151 −0.059 0.335
h1 0.064 0.940 −0.005 −0.149 −0.076 −0.158
h2 0.042 0.948 −0.025 −0.115 −0.099 −0.191
h3 0.074 0.941 −0.027 −0.115 −0.048 −0.158

Reliability

Reliability Raw Scores
factor raw_alpha std.alpha
forced 0.97 0.97
habit 0.98 0.98
economic 0.97 0.97
affective 0.86 0.86
normative 0.93 0.94
Alpha Drops
variable raw_alpha std.alpha
forced
f1 0.95 0.95
f2 0.95 0.95
f3 0.96 0.96
habit
h1 0.97 0.97
h2 0.96 0.96
h3 0.97 0.97
economic
e1 0.96 0.96
e2 0.95 0.96
e3 0.95 0.95
affective
a1 0.75 0.75
a2 0.86 0.86
a3 0.82 0.82
normative
n1 0.92 0.92
n2 0.90 0.90
n3 0.90 0.90

Creating factor variables

Honest statistical differences

ANOVA with Tukey's HSD
contrast null.value estimate conf.low conf.high adj.p.value
economic-affective 0.00 −1.54 −1.72 −1.37 0.00
forced-affective 0.00 −1.57 −1.74 −1.39 0.00
habit-affective 0.00 −0.74 −0.92 −0.57 0.00
normative-affective 0.00 −2.23 −2.40 −2.05 0.00
forced-economic 0.00 −0.02 −0.20 0.15 1.00
habit-economic 0.00 0.80 0.62 0.97 0.00
normative-economic 0.00 −0.68 −0.86 −0.51 0.00
habit-forced 0.00 0.82 0.65 1.00 0.00
normative-forced 0.00 −0.66 −0.83 −0.48 0.00
normative-habit 0.00 −1.48 −1.65 −1.31 0.00

What about committment levels?

Intent based on committment

term estimate std.error statistic p.value
(Intercept) 2.19 0.11 19.11 0.00
fct_affective 0.10 0.02 5.33 0.00
fct_normative 0.05 0.01 3.19 0.00
fct_economic 0.21 0.02 9.11 0.00
fct_habit 0.11 0.02 5.24 0.00
fct_forced 0.01 0.02 0.33 0.74
R Squared: 0.382

New model

Regression: Intent ~ Treatment + Driver + Interaction
term estimate std.error statistic p.value
(Intercept) 2.19 0.24 9.11 0.00
treatmentAd −0.22 0.33 −0.66 0.51
treatmentNew Product 0.06 0.33 0.19 0.85
treatmentSubscription 0.15 0.32 0.48 0.63
fct_affective 0.08 0.04 2.07 0.04
fct_economic 0.24 0.05 4.62 0.00
fct_forced 0.00 0.04 0.10 0.92
fct_habit 0.07 0.05 1.50 0.13
fct_normative 0.04 0.03 1.26 0.21
treatmentAd:fct_affective 0.07 0.05 1.23 0.22
treatmentNew Product:fct_affective −0.07 0.05 −1.26 0.21
treatmentSubscription:fct_affective 0.04 0.05 0.73 0.46
treatmentAd:fct_economic 0.02 0.07 0.23 0.82
treatmentNew Product:fct_economic −0.03 0.07 −0.39 0.69
treatmentSubscription:fct_economic −0.09 0.07 −1.43 0.15
treatmentAd:fct_forced 0.00 0.06 0.02 0.99
treatmentNew Product:fct_forced 0.03 0.06 0.60 0.55
treatmentSubscription:fct_forced −0.02 0.06 −0.43 0.67
treatmentAd:fct_habit 0.02 0.06 0.24 0.81
treatmentNew Product:fct_habit 0.11 0.06 1.84 0.07
treatmentSubscription:fct_habit 0.03 0.06 0.43 0.66
treatmentAd:fct_normative −0.05 0.04 −1.22 0.22
treatmentNew Product:fct_normative 0.03 0.04 0.78 0.44
treatmentSubscription:fct_normative 0.07 0.04 1.65 0.10
r-squared = 0.425

What about the segmentation?

Segmentation

Committment variables only

Characteristics by cluster

Another view

Significance test

Factor contrast null.value estimate conf.low conf.high adj.p.value
affective 2-1 0.00 1.78 1.63 1.94 0.00
affective 3-1 0.00 1.35 1.21 1.49 0.00
affective 3-2 0.00 −0.43 −0.58 −0.29 0.00
economic 2-1 0.00 1.84 1.70 1.98 0.00
economic 3-1 0.00 −2.09 −2.22 −1.96 0.00
economic 3-2 0.00 −3.93 −4.06 −3.79 0.00
forced 2-1 0.00 1.18 1.02 1.35 0.00
forced 3-1 0.00 −2.80 −2.95 −2.65 0.00
forced 3-2 0.00 −3.98 −4.14 −3.83 0.00
habit 2-1 0.00 0.36 0.20 0.52 0.00
habit 3-1 0.00 −3.52 −3.66 −3.37 0.00
habit 3-2 0.00 −3.88 −4.03 −3.73 0.00
normative 2-1 0.00 −2.02 −2.21 −1.84 0.00
normative 3-1 0.00 −0.43 −0.60 −0.26 0.00
normative 3-2 0.00 1.59 1.41 1.77 0.00

Key Statistics

Cluster N Gross Profit Mean Profit Mean Tenure Total Classes Profit/Ride-Year Margin
1-Fitness 484 $588,989 $1,217 3.2 53,940 $384.21 36%
2-Faithful 420 $1,649,578 $3,928 8.6 159,958 $456.69 34%
3-Bargain 596 $208,873 $350 1.5 23,208 $234.16 30%

Clusters & Treatments

Regression: Intent ~ Treatment + Cluster + Interaction
term estimate std.error statistic p.value
(Intercept) 4.15 0.07 56.90 0.00
treatmentAd 0.01 0.10 0.11 0.91
treatmentNew Product 0.50 0.10 4.89 0.00
treatmentSubscription 0.22 0.10 2.19 0.03
ClusterFaithful 0.54 0.11 4.94 0.00
ClusterBargain −0.79 0.10 −7.99 0.00
treatmentAd:ClusterFaithful 0.28 0.15 1.85 0.07
treatmentNew Product:ClusterFaithful −0.05 0.15 −0.35 0.72
treatmentSubscription:ClusterFaithful −0.25 0.15 −1.68 0.09
treatmentAd:ClusterBargain 0.10 0.14 0.72 0.47
treatmentNew Product:ClusterBargain −0.38 0.14 −2.77 0.01
treatmentSubscription:ClusterBargain 0.21 0.14 1.53 0.13
r-squared = 0.350

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

Exploring other possible influences

Regression: Intent ~ Treatment + Cluster + Tenure + Interaction
term estimate std.error statistic p.value
(Intercept) 4.20 0.08 50.37 0.00
treatmentAd 0.01 0.10 0.05 0.96
treatmentNew Product 0.50 0.10 4.90 0.00
treatmentSubscription 0.22 0.10 2.16 0.03
tenure −0.02 0.01 −1.46 0.15
ClusterFaithful 0.63 0.13 5.00 0.00
ClusterBargain −0.82 0.10 −8.12 0.00
treatmentAd:ClusterFaithful 0.29 0.15 1.92 0.06
treatmentNew Product:ClusterFaithful −0.05 0.15 −0.35 0.73
treatmentSubscription:ClusterFaithful −0.25 0.15 −1.65 0.10
treatmentAd:ClusterBargain 0.11 0.14 0.77 0.44
treatmentNew Product:ClusterBargain −0.39 0.14 −2.78 0.01
treatmentSubscription:ClusterBargain 0.21 0.14 1.55 0.12
r-squared = 0.351

Exploring other possible influences

Regression: Intent ~ Treatment + Cluster + CSAT + Interaction
term estimate std.error statistic p.value
(Intercept) 3.69 0.11 32.76 0.00
treatmentAd 0.02 0.10 0.20 0.84
treatmentNew Product 0.50 0.10 4.90 0.00
treatmentSubscription 0.21 0.10 2.11 0.04
csat 0.14 0.03 5.21 0.00
ClusterFaithful 0.54 0.11 5.01 0.00
ClusterBargain −1.09 0.11 −9.59 0.00
treatmentAd:ClusterFaithful 0.25 0.15 1.68 0.09
treatmentNew Product:ClusterFaithful −0.07 0.15 −0.48 0.63
treatmentSubscription:ClusterFaithful −0.26 0.15 −1.72 0.09
treatmentAd:ClusterBargain 0.09 0.14 0.63 0.53
treatmentNew Product:ClusterBargain −0.37 0.14 −2.70 0.01
treatmentSubscription:ClusterBargain 0.21 0.13 1.59 0.11
r-squared = 0.351