Data mining techniques in CRM: inside customer segmentation
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Chichester
Wiley
2009
|
| Edition: | 1. publ. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Literaturverz. S. [349] - 350 |
| Physical Description: | XI, 357 S. Ill., graph. Darst. |
| ISBN: | 9780470743973 |
Staff View
MARC
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| 650 | 4 | |a Customer relations |x Management | |
| 650 | 4 | |a Customer relations |x Management |x Data processing | |
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Record in the Search Index
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| adam_text | DATA MINING TECHNIQUES IN CRM INSIDE CUSTOMER SEGMENTATION KONSTANTINOS
TSIPTSIS CRM 6- CUSTOMER INTELLIGENCE EXPERT, ATHENS, GREECE ANTONIOS
CHORIANOPOULOS DATA MINING EXPERT, ATHENS, GREECE WILEY A JOHN WILEY AND
SONS, LTD., PUBLICATION CONTENTS ACKNOWLEDGEMENTS XIII 1 DATA MINING IN
CRM 1 THE CRM STRATEGY 1 WHAT CAN DATA MINING DO? 2
SUPERVISED/PREDICTIVE MODELS 3 UNSUPERVISED MODELS 3 DATA MINING IN THE
CRM FRAMEWORK 4 CUSTOMER SEGMENTATION 4 DIRECT MARKETING CAMPAIGNS 5
MARKET BASKET AND SEQUENCE ANALYSIS 7 THE NEXT BEST ACTIVITY STRATEGY
AND INDIVIDUALIZED CUSTOMER MANAGEMENT 8 THE DATA MINING METHODOLOGY
10 DATA MINING AND BUSINESS DOMAIN EXPERTISE 13 SUMMARY 13 2 AN OVERVIEW
OF DATA MINING TECHNIQUES 17 SUPERVISED MODELING 17 PREDICTING EVENTS
WITH CLASSIFICATION MODELING 19 EVALUATION OF CLASSIFICATION MODELS 25
SCORING WITH CLASSIFICATION MODELS 32 MARKETING APPLICATIONS SUPPORTED
BY CLASSIFICATION MODELING 3 2 SETTING UP A VOLUNTARY CHURN MODEL 33
FINDING USEFUL PREDICTORS WITH SUPERVISED FIELD SCREENING MODELS 36
PREDICTING CONTINUOUS OUTCOMES WITH ESTIMATION MODELING. 37 UNSUPERVISED
MODELING TECHNIQUES 39 SEGMENTING CUSTOMERS WITH CLUSTERING TECHNIQUES
40 REDUCING THE DIMENSIONALITY OF DATA WITH DATA REDUCTION TECHNIQUES 47
FINDING WHAT GOES WITH WHAT WITH ASSOCIATION OR AFFINITY MODELING
TECHNIQUES 50 DISCOVERING EVENT SEQUENCES WITH SEQUENCE MODELING
TECHNIQUES 56 DETECTING UNUSUAL RECORDS WITH RECORD SCREENING MODELING
TECHNIQUES 59 MACHINE LEARNING/ARTIFICIAL INTELLIGENCE VS. STATISTICAL
TECHNIQUES 61 SUMMARY 62 VIII CONTENTS 3 DATA MINING TECHNIQUES FOR
SEGMENTATION 65 SEGMENTING CUSTOMERS WITH DATA MINING TECHNIQUES 65
PRINCIPAL COMPONENTS ANALYSIS 65 PC A DATA CONSIDERATIONS 67 HOW MANY
COMPONENTS ARE TO BE EXTRACTED? 67 WHAT IS THE MEANING OF EACH
COMPONENT? 75 DOES THE SOLUTION ACCOUNT FOR ALL THE ORIGINAL FIELDS? 78
PROCEEDING TO THE NEXT STEPS WITH THE COMPONENT SCORES 79 RECOMMENDED PC
A OPTIONS 80 CLUSTERING TECHNIQUES 82 DATA CONSIDERATIONS FOR CLUSTERING
MODELS 83 CLUSTERING WITH K-MEANS 85 RECOMMENDED K-MEANS OPTIONS 87
CLUSTERING WITH THE TWOSTEP ALGORITHM 88 RECOMMENDED TWOSTEP OPTIONS 90
CLUSTERING WITH KOHONEN NETWORK/SELF-ORGANIZING MAP 91 RECOMMENDED
KOHONEN NETWORK/SOM OPTIONS 93 EXAMINING AND EVALUATING THE CLUSTER
SOLUTION 96 THE NUMBER OF CLUSTERS AND THE SIZE OF EACH CLUSTER 96
COHESION OF THE CLUSTERS 97 SEPARATION OF THE CLUSTERS 99 UNDERSTANDING
THE CLUSTERS THROUGH PROFILING 100 PROFILING THE CLUSTERS WITH IBM SPSS
MODELER S CLUSTER VIEWER 102 ADDITIONAL PROFILING SUGGESTIONS 105
SELECTING THE OPTIMAL CLUSTER SOLUTION 108 CLUSTER PROFILING AND SCORING
WITH SUPERVISED MODELS 110 AN INTRODUCTION TO DECISION TREE MODELS 110
THE ADVANTAGES OF USING DECISION TREES FOR CLASSIFICATION MODELING 121
ONE GOAL, DIFFERENT DECISION TREE ALGORITHMS: CIRRT, C5.0, AND CHAID 123
RECOMMENDED CHAID OPTIONS 125 SUMMARY 127 4 THE MINING DATA MART 133
DESIGNING THE MINING DATA MART 133 THE TIME FRAME COVERED BY THE MINING
DATA MART 135 THE MINING DATA MART FOR RETAIL BANKING 137 CURRENT
INFORMATION 138 CUSTOMER INFORMATION 138 PRODUCT STATUS 138 MONTHLY
INFORMATION 140 SEGMENT AND GROUP MEMBERSHIP 141 PRODUCT OWNERSHIP AND
UTILIZATION 141 BANK TRANSACTIONS 141 LOOKUP INFORMATION 143 PRODUCT
CODES 144 CONTENTS IX TRANSACTION CHANNELS 145 TRANSACTION TYPES 145 THE
CUSTOMER SIGNATURE -FROM THE MINING DATA MART TO THE MARKETING
CUSTOMER INFORMATION FILE 148 CREATING THE MCIF THROUGH DATA PROCESSING
149 DERIVED MEASURES USED TO PROVIDE AN ENRICHED CUSTOMER VIEW 154 THE
MCIF FOR RETAIL BANKING 155 THE MINING DATA MART FOR MOBILE TELEPHONY
CONSUMER (RESIDENTIAL) CUSTOMERS 160 MOBILE TELEPHONY DATA AND CDRS 162
TRANSFORMING CDR DATA INTO MARKETING INFORMATION 162 CURRENT INFORMATION
163 CUSTOMER INFORMATION 164 RATE PLAN HISTORY 165 MONTHLY INFORMATION
167 OUTGOING USAGE 167 INCOMING USAGE 169 OUTGOING NETWORK 170 INCOMING
NETWORK 170 LOOKUP INFORMATION 170 RATE PLANS 171 SERVICE TYPES 171
NETWORKS 172 THE MCIF FOR MOBILE TELEPHONY 17 2 THE MINING DATA MART FOR
RETAILERS 177 TRANSACTION RECORDS 179 CURRENT INFORMATION 179 CUSTOMER
INFORMATION 179 MONTHLY INFORMATION 180 TRANSACTIONS 180 PURCHASES BY
PRODUCT GROUPS 182 LOOKUP INFORMATION 183 THE PRODUCT HIERARCHY 183 THE
MCIF FOR RETAILERS 184 SUMMARY 187 5 CUSTOMER SEGMENTATION 189 AN
INTRODUCTION TO CUSTOMER SEGMENTATION 189 SEGMENTATION IN MARKETING 190
SEGMENTATION TASKS AND CRITERIA 191 SEGMENTATION TYPES IN CONSUMER
MARKETS 191 VALUE-BASED SEGMENTATION 193 BEHAVIORAL SEGMENTATION 194
PROPENSITY-BASED SEGMENTATION 195 LOYALTY SEGMENTATION 196
SOCIO-DEMOGRAPHIC AND LIFE-STAGE SEGMENTATION 198 CONTENTS
NEEDS/ ATTITUDINAL-BASED SEGMENTATION 199 SEGMENTATION IN BUSINESS
MARKETS 200 A GUIDE FOR BEHAVIORAL SEGMENTATION 203 BEHAVIORAL
SEGMENTATION METHODOLOGY 203 BUSINESS UNDERSTANDING AND DESIGN OF THE
SEGMENTATION PROCESS 203 DATA UNDERSTANDING, PREPARATION, AND ENRICHMENT
205 IDENTIFICATION OF THE SEGMENTS WITH CLUSTER MODELING 208 EVALUATION
AND PROFILING OF THE REVEALED SEGMENTS 208 DEPLOYMENT OF THE
SEGMENTATION SOLUTION, DESIGN, AND DELIVERY OF DIFFERENTIATED STRATEGIES
211 TIPS AND TRICKS 211 SEGMENTATION MANAGEMENT STRATEGY 213 A GUIDE FOR
VALUE-BASED SEGMENTATION 216 VALUE-BASED SEGMENTATION METHODOLOGY 216
BUSINESS UNDERSTANDING AND DESIGN OF THE SEGMENTATION PROCESS 216 DATA
UNDERSTANDING AND PREPARATION -CALCULATION OF THE VALUE MEASURE 218
GROUPING CUSTOMERS ACCORDING TO THEIR VALUE 218 PROFILING AND EVALUATION
OF THE VALUE SEGMENTS 219 DEPLOYMENT OF THE SEGMENTATION SOLUTION 219
DESIGNING DIFFERENTIATED STRATEGIES FOR THE VALUE SEGMENTS 220 SUMMARY
223 SEGMENTATION APPLICATIONS IN BANKING 225 SEGMENTATION FOR CREDIT
CARD HOLDERS 225 DESIGNING THE BEHAVIORAL SEGMENTATION PROJECT 226
BUILDING THE MINING DATASET 227 SELECTING THE SEGMENTATION POPULATION
228 THE SEGMENTATION FIELDS 230 THE ANALYTICAL PROCESS 233 REVEALING THE
SEGMENTATION DIMENSIONS 233 IDENTIFICATION AND PROFILING OF SEGMENTS 237
USING THE SEGMENTATION RESULTS 256 BEHAVIORAL SEGMENTATION REVISITED:
SEGMENTATION ACCORDING TO ALL ASPECTS OF CARD USAGE 258 THE CREDIT CARD
CASE STUDY: A SUMMARY 263 SEGMENTATION IN RETAIL BANKING 264 WHY
SEGMENTATION? 264 SEGMENTING CUSTOMERS ACCORDING TO THEIR VALUE: THE
VITAL FEW CUSTOMERS 267 USING BUSINESS RULES TO DEFINE THE CORE SEGMENTS
268 SEGMENTATION USING BEHAVIORAL ATTRIBUTES 271 SELECTING THE
SEGMENTATION FIELDS 271 THE ANALYTICAL PROCESS 274 IDENTIFYING THE
SEGMENTATION DIMENSIONS WITH PCA/FACTOR ANALYSIS 274 SEGMENTING THE
PURE MASS CUSTOMERS WITH CLUSTER ANALYSIS 276 PROFILING OF SEGMENTS
276 CONTENTS XI THE MARKETING PROCESS 283 SETTING THE BUSINESS
OBJECTIVES 283 SEGMENTATION IN RETAIL BANKING: A SUMMARY 288 7
SEGMENTATION APPLICATIONS IN TELECOMMUNICATIONS 291 MOBILE TELEPHONY 291
MOBILE TELEPHONY CORE SEGMENTS - SELECTING THE SEGMENTATION POPULATION
292 BEHAVIORAL AND VALUE-BASED SEGMENTATION - SETTING UP THE PROJECT 294
SEGMENTATION FIELDS 295 VALUE-BASED SEGMENTATION 300 VALUE-BASED
SEGMENTS: EXPLORATION AND MARKETING USAGE 304 PREPARING DATA FOR
CLUSTERING - COMBINING FIELDS INTO DATA COMPONENTS 30 7 IDENTIFYING,
INTERPRETING, AND USING SEGMENTS 313 SEGMENTATION DEPLOYMENT 326 THE
FIXED TELEPHONY CASE 329 SUMMARY 331 8 SEGMENTATION FOR RETAILERS 333
SEGMENTATION IN THE RETAIL INDUSTRY 333 THE RFM ANALYSIS 334 THE RFM
SEGMENTATION PROCEDURE 338 RFM: BENEFITS, USAGE, AND LIMITATIONS 345
GROUPING CUSTOMERS ACCORDING TO THE PRODUCTS THEY BUY 346 SUMMARY 348
FURTHER READING 349 INDEX 351
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| language | English |
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| spelling | Tsiptsis, Konstantinos Verfasser aut Data mining techniques in CRM inside customer segmentation Konstantinos Tsiptsis ; Antonios Chorianopoulos 1. publ. Chichester Wiley 2009 XI, 357 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Literaturverz. S. [349] - 350 Datenverarbeitung Customer relations Management Customer relations Management Data processing Data mining Data Mining (DE-588)4428654-5 gnd rswk-swf Kundenmanagement (DE-588)4236865-0 gnd rswk-swf Data Mining (DE-588)4428654-5 s Kundenmanagement (DE-588)4236865-0 s b DE-604 Chorianopoulos, Antonios Verfasser aut GBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018887335&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Tsiptsis, Konstantinos Chorianopoulos, Antonios Data mining techniques in CRM inside customer segmentation Datenverarbeitung Customer relations Management Customer relations Management Data processing Data mining Data Mining (DE-588)4428654-5 gnd Kundenmanagement (DE-588)4236865-0 gnd |
| subject_GND | (DE-588)4428654-5 (DE-588)4236865-0 |
| title | Data mining techniques in CRM inside customer segmentation |
| title_auth | Data mining techniques in CRM inside customer segmentation |
| title_exact_search | Data mining techniques in CRM inside customer segmentation |
| title_full | Data mining techniques in CRM inside customer segmentation Konstantinos Tsiptsis ; Antonios Chorianopoulos |
| title_fullStr | Data mining techniques in CRM inside customer segmentation Konstantinos Tsiptsis ; Antonios Chorianopoulos |
| title_full_unstemmed | Data mining techniques in CRM inside customer segmentation Konstantinos Tsiptsis ; Antonios Chorianopoulos |
| title_short | Data mining techniques in CRM |
| title_sort | data mining techniques in crm inside customer segmentation |
| title_sub | inside customer segmentation |
| topic | Datenverarbeitung Customer relations Management Customer relations Management Data processing Data mining Data Mining (DE-588)4428654-5 gnd Kundenmanagement (DE-588)4236865-0 gnd |
| topic_facet | Datenverarbeitung Customer relations Management Customer relations Management Data processing Data mining Data Mining Kundenmanagement |
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