Index
accelerated failure time (AFT) model
acquisition discount
acquisition model
actual acquisition probability
AdaCost boosting
AMOS software
analytical methods
ARPRO (Acquisition, Retention, and PROfitability) model
artificial intelligence
average order size
defined
multivariate regression (OLS)
three-stage least squares estimation in
balancing acquisition. See also retention modeling
modeling framework
SAS code
SAS output
B2B firm
contractual basis
improving acquisition rate
B2C firm
CRM implementation at
improve repurchase rate
bias
binary dependent variable
binary variable
Blogs
CDF. See cumulative distribution function (CDF)
ceiling rate
censoring issues
CLV. See customer lifetime value (CLV)
content communities
contractual business
CRM implementation
at B2C firm
challenges
CLV management framework
fashion retailer
focal firm background
implementation
at IBM
background
implementing CLV management framework
cross-buying
determine odds ratio
effect of acquisition channels on
identifying drivers
implementation
logistic regression
cutoff value
probability function
results from
predicted vs. actual cross-buy
transaction behavior
variables for model
cross-sectional data
cumulative distribution function (CDF)
customer acquisition
drivers of
joint distribution of acquisition time and duration
mixing distribution for univariate function
models
issues addressed in
review
questionniire
Sarmanov family of multivariate distributions
defining density functions and bounded mixing functions
SAS code
SAS output
select empirical studies modeling
selection decisions (See initial order quantity; lifetime duration; response probability)
variables, used for analysis
customer acquisition likelihood
customer asset value
customer churn
attrition effects
bagging and boosting classification trees for prediction
binary logistic regressions
data include variables
drivers and likelihood, studies
error term, properties
five-stage churn management framework
impact of
implementation
likelihood contribution of volunteer
MacKay's Bayesian ARD neural network and random forests
models
prediction accuracy of proposed techniques
probability calculation
probit model
proportional hazards model, to analyze customer attrition
results
computing MAD
interpreting parameter coefficients from AFT model
predictive accuracy of model
ratio of survival times
SAS code
SAS output
time series analysis
utility expression
variables, for studies
Weibull hazard model with time-varying covariates
customer–company relationships
baseline hazard
density function
duration/time
results from estimation
variables
generalized gamma models
hazard function
MLE method
non-contractual settings
survival function
Weibull distribution
customer equity
model
customer–firm relationship life cycle
customer influence effect (CIE) metric
customer influence value (CIV)
customer life cycle
customer lifetime value (CLV)
based churn models
based management framework at IBM
process assessing impact of
challenges in implementing framework
and implement CRM initiatives
management framework at fashion retailer
measurement approach
profitability
customer no longer repurchase
covariate coefficients
dependent variable in study
discrete-hazard approach
discrete-time model
duration of service retention dh
hazard rate of lapsing
hazards regression using baseline hazard function
household's probability of purchasing product
implementation
instantaneous probability
likelihood function
Markov chain Monte Carlo (MCMC) sampling algorithm
result of logistic regression
survival function for retention modeling
third-order polynomial expression
variables, for model
customer profitability
customer relationship management
defined
initiatives
customer retention
data
demographics
transaction information
factors, effects of
industries
integrated relationships
modeling
issues addressed in
review of
research on
SAS code
SAS output
significance of
strategies
customer-to-customer (C2C) exchanges
customer win-back
benifits of
cost of
data, including variables
effects of price changes
implementation
models
probability of customer terminating relationship
conditional regression
customer-specific preferences
error variances
latent duration of relationship
reacquisition and duration of second lifetime
probit model for probability of reacquisition
reacquisition model
cutoff value
likelihood of readoption
probit regression
variables
regain profit (RP) function
SAS code
SAS output
SCLV model
computing MAD
results
variables
second duration model
inverse Mills ratio
probit model
sample selection bias
variables
second life-time value (SLTV)
split hazard model
customized marketing campaigns
cutoff value
database
categories of
customer database
inactive customers
sources of
transaction-related
variables
decision calculus
decision tree
defection behaviors
dependent variable
dummy variables
duration model
EQS software
ERP (Enterprise Resource Planning) systems
firm's performance
customers meet criteria
future profitability
predict CLV for each customers
results
variables, model include
First_Purchase model
Fisher-scoring solution
FREQ Procedure
GAUSS
Gini coefficient
inactive customers
information for documentation
independent variables
initial order quantity
biased estimates
cross-sectional data
list of variables
two-stage modeling framework
internet
inverse Mills ratio
lifetime duration
BG/NBD model
biased estimates
Hazard models
implementation
methods from machine learning fields
negative binomial distribution (NBD)/Pareto model
in non-contractual setting
probabilities
results
for retailing stores
sBG probabilities calculation
shifted-beta geometric (sBG) distribution
standard right-censored Tobit model
survival analysis
variables for model
lifetime value model (LTV)
LISREL software
LOGISTIC procedure
logistic regression
log-odds ratio
response probability
logit model
binary
MLE method
multinomial
machine learning
marketing functions
customer-centric
product-based
MATLAB
maximum likelihood estimates
mean absolute deviation (MAD)
mean absolute percent error (MAPE)
metrics
categories
commonly used CRM metrics
mobile marketing
mobile/Web-based online portals
newly acquired customers
prediction
newspaper subscriptions, business
null hypothesis
odds ratio
estimates
OLS regression model
online grocery retailing industry
optimal resource allocation
implementation
objective function
scenarios
variables for study
Acq_Exp
E(Duration)
E(Profit)
expected acquisition rate
results from simulation
Ret_Exp
order quantity
amount of usage
biased estimates
coefficient, specifies impact of lagged dollars spent on
implementation
independent variables in future usage equation
mean absolute deviation (MAD)
OLS regression model
probit model
result
sample selection correction variable
two-stage modeling framework
parameter
variables of model
order size
average
negative binomial regression
Poisson model to specify units ordered
pharmaceutical firm
phone-based technology
predicted probabilities
predicted vs. actual acquisition
predicted vs. actual cross-buy
predicted vs. actual repurchase
present value of revenue (PVR)
probit model
PROC Freq
PROC Lifereg procedure
PROC Logistic
PROC QLIM
PROC Reg
proc sql
profitability
ceiling rate
computing MAD
customer equity
implementation
OLS regression model
results
variables for model
profit model
proportional hazards model (PHM)
purchase behavior
p-value
repurchase
behavior
binary variable
complementary log–log model
industries for statistical analyses
logistic and probit regressions
logistic regression
logit model to predict
neural networks (NNs)
random intercept model
television entertainment service subscription industry
response probability
binary logit model
cumulative distribution function
for probit model
empirical example
Hessian matrix
independent variables
likelihood function for logit model
MLE method, for probit model
model, parameter estimates from
probability of response p
unobserved utility, variable for
WOM referral
retailer
directives
fashion
retention modeling
return on investment (ROI)
RFM value
R-Square
sample selection
SAS code
SAS Data
SAS output
SAS System
segmentation techniques
share-of-wallet (SOW)
banking industry
two-level latent class regression model
defined for customer
determine drivers
effect of loyalty programs
implementation
limited dependent variable
log-odds ratio
multinomial logit model
MLE method
predicted probability
predictive accuracy of model
results
two-stage least squares (2SLS) procedure
variables of model
shopping behavior
social coupons
social media
SOW. See share-of-wallet (SOW)
SPSS program
statcrm.customer_acquisition
statcrm.customer_trans
statistical software
switching behavior
telecommunications services
Tobit model
to estimate PVR for customers
mathematical specifications
for online grocery retailing industry
selectivity variable
lambda (λis)
standard right-censored
transactions behavior
validation
variance
variant across time (VAR) modeling
Ventriloquist Express
voice over internet protocol (VoIP) technology
Web-based technology
Weibull distributions
weighted average cost of capital (WACC)
Wheel-of-Fortune strategies