Learning Management Marketing and Customer Support 12 potx
Learning Management Marketing and Customer Support_12 potx
... distribution, 130–132
null hypothesis and, 125 126
probabilities, 133–135
proportion, standard error of,
marketing campaign
approaches, 139–141
p-values, 126
q-values, 126
range values, 137
regression ...
sample sizes, marketing campaign
approaches, 145
sample variation, 129
standard deviation, 132, 138
standardized values, 129 –133
sum of values, 137–138
time series...
Learning Management Marketing and Customer Support_2 docx
... same number of records supporting it. As a general rule of thumb,
several dozen records for each category are a minimum to get adequate
support and hundreds or thousands of examples are not ... non-content-bearing words, such as “it,” and, ” and “of,” were
removed from the text of all stories in the training set. A total of 368
words in this category were identified and removed.
2...
Learning Management Marketing and Customer Support_3 ppt
... possibilities for information about customers and their
behavior over time. Demographic and trending information is available on
individuals and households to further augment customer profiles. This addi-
tional ... 2-by-4s also purchase nails; customers who
purchase paint buy paint brushes; oil and oil filters are purchased together, as
are hamburgers and hamburger buns, and...
Learning Management Marketing and Customer Support_4 docx
... step, the following counts are created:
■■ Milk and detergent, milk and soda, milk and cleaner
■■ Detergent and soda, detergent and cleaner
■■ Soda and cleaner
This is a total of 10 pairs of items. ... 200 are extra cheese
400 are mushroom and pepperoni, 300 are mushroom and extra cheese, 200 are pepperoni and extra cheese
100 are mushroom, pepperoni, and extra cheese....
Learning Management Marketing and Customer Support_5 ppt
... and evergreens, and between winter, spring, summer, and fall. People
know enough about woodland flora to predict that, of all the hundreds of vari-
ables associated with the forest, season and ... encountered in market-
ing, sales, and customer support are not about points in space. They are about
purchases, phone calls, airplane trips, car registrations, and a thousand other...
Learning Management Marketing and Customer Support_6 pot
... CENSORED
Hazard Functions and Survival Analysis in Marketing 401
470643 c12.qxd 3/8/04 11:17 AM Page 395
Hazard Functions and Survival Analysis in Marketing 395
Table 12. 1 (continued)
AGE PERCENT ... (Years)
Figure 12. 5 The shape of a bathtub-shaped hazard function starts high, plummets, and then
gradually increases again.
470643 c12.qxd 3/8/04 11:17 AM Page 412
412 Cha...
Learning Management Marketing and Customer Support_9 pptx
... Rock Candy Mountains,
There’s a land that’s fair and bright,
Where the handouts grow on bushes
And you sleep out every night.
Where the boxcars all are empty
And the sun shines every day
And ... their jobs. In the
ideal customer- centric organization, everyone is rewarded for increasing cus-
tomer value and understands that this requires learning from each customer
470643...
Learning Management Marketing and Customer Support_11 pptx
...
telephone data although few customers use them. One way to handle this is to
identify the handsets to keep and to add a new field “handset for analysis”
that keeps these handsets and places the rest ...
relationships are complex and change over time. Customers might change
their telephone numbers. Telephones might be added or removed from
accounts. Customers change handsets, and...
Learning Management Marketing and Customer Support_13 pptx
...
density function, 133
as disciplinary technique, 123
discrete values, 127 –131
experimentation, 160–161
field values, 128
histograms and, 127
marketing campaign approaches
acuity of testing, ...
probabilities, 133–135
p-values, 126
q-values, 126
range values, 137
regression ranges, 139
sample variation, 129
standard deviation, 132, 138
standardized values, 129 –133...
Data For Marketing Risk And Customer Relationship Management_4 potx
... variables into strong predictors. And every step of
the way, I worked through the one-model and two-model approaches. We are now ready to take our final candidate
variables and create the winning model. ... coefficients and create an output data set.
I am now ready to process my candidate variables in the final model for both Method 1 (one-step model) and Method 2
(two-step model...
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