Deck 7: Database and Customer Data Development
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Deck 7: Database and Customer Data Development
1
Most data mining efforts use a data mart as their source for data and information.
True
2
RFM is an easy and cost effective data mining technique.
True
3
Decision trees are structured like a tree, where leaves represent classifications and branches represent conjunctions of features that lead to these classifications.
True
4
Cluster analysis uses three key variables as part of its process: recency, frequency and monetary.
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5
Fuzzy logic is not a data mining method.
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6
Regression analysis and correlation are statistic methods that can be used as part of a data mining process.
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7
Consumer fatigue prevention is a benefit of data mining.
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8
Data mining has many benefits, but the ability to create new differentiation strategies is not one of them.
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9
The casino industry is one of the best examples of dynamic CRM.
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10
Organizations in the financial services industry are very proficient in data mining techniques.
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11
It is extremely hard, if not impossible, for a small business to perform data mining.
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12
An ancillary benefit of data mining is identification of unusual customer activity.
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13
Fraud detection is a major benefit of data mining.
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14
A major data mining challenge is organizational obstacles to attaining the data necessary for analysis.
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15
_______ is an example of a data mining process.
A)Sorting and analyzing data
B)Processing all online orders immediately
C)Updating a data warehouse
D)Browsing information in search of patterns and anomalies
E)Data preparation
A)Sorting and analyzing data
B)Processing all online orders immediately
C)Updating a data warehouse
D)Browsing information in search of patterns and anomalies
E)Data preparation
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16
____ is not a data mining activity.
A)Transaction buyer identification
B)Word of mouth calculation
C)LTV calculation
D)Clustering
E)POS sales transmission
A)Transaction buyer identification
B)Word of mouth calculation
C)LTV calculation
D)Clustering
E)POS sales transmission
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17
Recently the term "dashboard" is used to describe a (an) ______.
A)Automobile part
B)ERP
C)DSS
D)EIS
E)RIP
A)Automobile part
B)ERP
C)DSS
D)EIS
E)RIP
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18
Identifying transaction buyers is a (an) ____ function.
A)Prospecting
B)RFM
C)Data Mining
D)ERP
E)EIS
A)Prospecting
B)RFM
C)Data Mining
D)ERP
E)EIS
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19
A data warehouse could contain_____.
A)Demographic information
B)Product information
C)Promotion information
D)Prospect information
E)All of the above
A)Demographic information
B)Product information
C)Promotion information
D)Prospect information
E)All of the above
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20
A ____ would be the best source of information on the last 10 years of customer transactions.
A)Data mart
B)Operational data store
C)Data warehouse
D)Reference database
E)Web site database
A)Data mart
B)Operational data store
C)Data warehouse
D)Reference database
E)Web site database
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21
A (An) _____ would be a less-than-optimal source of information for data mining.
A)Data warehouse
B)Operational data store
C)Web site database
D)Data warehouse or data mart
E)Data mart
A)Data warehouse
B)Operational data store
C)Web site database
D)Data warehouse or data mart
E)Data mart
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22
Data mining usually accesses a ________ for its source of information.
A)Data warehouse
B)Operational data store
C)Web site database
D)Reference database
E)Data mart
A)Data warehouse
B)Operational data store
C)Web site database
D)Reference database
E)Data mart
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23
RFM is a (an) _____ technique.
A)Costly
B)Simple
C)Complex
D)Outdated
E)None of the above
A)Costly
B)Simple
C)Complex
D)Outdated
E)None of the above
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24
RFM is a _____ technique.
A)Pattern recognition
B)Regression
C)Clustering
D)Sorting
E)Suppression
A)Pattern recognition
B)Regression
C)Clustering
D)Sorting
E)Suppression
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25
RFM is dependent on the use of ___ variable (s)
A)Three
B)Six
C)Two
D)Five
E)One
A)Three
B)Six
C)Two
D)Five
E)One
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26
A _____ can be learned by splitting the source set into subsets based on an attribute value test.
A)Clustering
B)RFM
C)Decision Tree
D)Regression analysis
E)Fuzzy Logic
A)Clustering
B)RFM
C)Decision Tree
D)Regression analysis
E)Fuzzy Logic
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27
___ is the process of placing customers into groups such that everyone in the group has similar traits.
A)Geo-analysis
B)Clustering
C)Sorting
D)Decision tree analysis
E)Suppression
A)Geo-analysis
B)Clustering
C)Sorting
D)Decision tree analysis
E)Suppression
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28
Cluster analysis would not include _____ as a variable category.
A)Behavior
B)Psychographic
C)Geographic
D)Demographic
E)Scalable
A)Behavior
B)Psychographic
C)Geographic
D)Demographic
E)Scalable
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29
Home ownership is an example of a _____ variable.
A)Behavior
B)Psychographic
C)Geographic
D)Demographic
E)Scalable
A)Behavior
B)Psychographic
C)Geographic
D)Demographic
E)Scalable
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30
Product usage rate is an example of a _____ variable.
A)Behavior
B)Psychographic
C)Geographic
D)Demographic
E)Scalable
A)Behavior
B)Psychographic
C)Geographic
D)Demographic
E)Scalable
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31
State and climate are examples of a _____ variable.
A)Behavior
B)Psychographic
C)Geographic
D)Demographic
E)Scalable
A)Behavior
B)Psychographic
C)Geographic
D)Demographic
E)Scalable
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32
Data mining helps answers all of the following questions except ____.
A)Who are my customers
B)Which database entity is the optimal data repository
C)How can I retain customers
D)What does a loyal customer look like
E)What do my customers buy
A)Who are my customers
B)Which database entity is the optimal data repository
C)How can I retain customers
D)What does a loyal customer look like
E)What do my customers buy
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33
_____is not a common data mining method.
A)Fuzzy logic
B)Pattern recognition
C)ERP
D)Artificial Neural Network
E)Data stream mining
A)Fuzzy logic
B)Pattern recognition
C)ERP
D)Artificial Neural Network
E)Data stream mining
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34
____ is not a statistical method.
A)RFM
B)Chi-square
C)Regression analysis
D)Correlation
E)Analysis of Variance
A)RFM
B)Chi-square
C)Regression analysis
D)Correlation
E)Analysis of Variance
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35
By adding the modeling component, organizations can enhance data mining by making it
A)Cost-justified
B)Measurable
C)optimal
D)B and C
E)A, B, and C
A)Cost-justified
B)Measurable
C)optimal
D)B and C
E)A, B, and C
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36
The best industry example of dynamic CRM is the
A)Toy
B)Packaged goods
C)Casino
D)Computer
E)Grocery
A)Toy
B)Packaged goods
C)Casino
D)Computer
E)Grocery
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37
______ is an ancillary benefit to data mining.
A)Unusual customer activity
B)Data transformation into information
C)Privacy issues
D)Interpretation of information
E)Information transformation into knowledge
A)Unusual customer activity
B)Data transformation into information
C)Privacy issues
D)Interpretation of information
E)Information transformation into knowledge
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38
______ is not a challenge to data mining.
A)Inability to capture customer transactions
B)Cost versus benefit
C)Organization expertise
D)Fraud detection
E)Privacy issues
A)Inability to capture customer transactions
B)Cost versus benefit
C)Organization expertise
D)Fraud detection
E)Privacy issues
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