(Week 03) A01. Data. Data Structure
|
|
- Kristin McCoy
- 5 years ago
- Views:
Transcription
1 (Week 03) A01. Data Data Structure Course Code: Course Name: Data Structure Period: Spring 2016 Lecturer: Prof. Dr. LEE, Sync Sangwon Department: Information & Electronic Commerce University: WONKWANG Prof. Dr. SSL {IDEA, STEM, RF, FP, C, LDV} / p. 1 Contents Prof. Dr. SSL {IDEA, STEM, RF, FP, C, LDV} / p. 2 1
2 01. Data Management Managerial class vs. activities vs. data Top manager (executive) Strategic planning for unstructured problem on KB Middle-manager Management control for semi-structured problem on DW First-line manager Operational control for structured problem on DB Scope Generalization Future-Oriented Externalization Strategic Planning for Unstructured Problem by Top Manager Management Controlling for Semi-structured Problem by Middle Manager Operational Controlling for Structured Problem by First-Line Manager Transaction Processing Timeliness Accuracy Frequency Materialization Past-Oriented Internalization Prof. Dr. SSL {IDEA, STEM, RF, FP, C, LDV} / p Marketing Science Marketing + data science Trends of marketing science Intuition < basis Goods < customer Sales < profit Simple statistics < analysis One channel (mass) < channel mix Old 제품중심의접근대중마케팅방식직감에의한마케팅기획규모의경제기반시장점유율확대중심신규고객획득 ( 단기고객 ) 중심매출액기반에의한실적평가 Now 고객중심의접근관계지향성일대일지향성고객점유율확대중심마케팅순환기능지향성다중채널지향성 Prof. Dr. SSL {IDEA, STEM, RF, FP, C, LDV} / p. 4 2
3 Definition of CRM Customer Relationship Management A sort of marketing science Activities to manage customer relationship efficiently & effectively Cf. Marketing = CRM (AMA, American Marketing Association) Prof. Dr. SSL {IDEA, STEM, RF, FP, C, LDV} / p. 5 System architecture of CRM Analytical CRM Operational CRM Collaborative CRM Prof. Dr. SSL {IDEA, STEM, RF, FP, C, LDV} / p. 6 3
4 Marketing offer of CRM 4R(Right customer, Right product, Right time, Right channel) Cf. marketing mix 4P(Product, Price, Place (of distribution), Promotion) Marketing Mix Product Price Place Promotion Marketing Offer Right Customer Right Product Right Time Right Channel Prof. Dr. SSL {IDEA, STEM, RF, FP, C, LDV} / p. 7 CRM strategy Customer segmentation 1 Infrastructure strategy 2 Relationship acquisition strategy 3 Relationship retention strategy 4 Relationship expansion strategy Prof. Dr. SSL {IDEA, STEM, RF, FP, C, LDV} / p. 8 4
5 Customer value Fair value line with PV & CE PV(Perceived Value) from the viewpoint of customer CE(Customer Equity) from the viewpoint of enterprise CLV(Customer Life Value) + CRV(Customer Referral Value) CS(Customer Share) RFM(Recency, Frequency, and Monetary) Prof. Dr. SSL {IDEA, STEM, RF, FP, C, LDV} / p. 9 1 Infrastructure strategy Customer information management Customer segmentation Core customer management Customer-driven NPD(New Product Development) Campaign management VOC(Voice of Customer) management Performance measurement management Customer survey management Prof. Dr. SSL {IDEA, STEM, RF, FP, C, LDV} / p. 10 5
6 2 Relationship acquisition strategy Prospective acquisition First buying inducement Customer win-back Prof. Dr. SSL {IDEA, STEM, RF, FP, C, LDV} / p Relationship retention strategy Second buying inducement Loyalty program Prediction and prevention of customer churn Personalized communication Prof. Dr. SSL {IDEA, STEM, RF, FP, C, LDV} / p. 12 6
7 4 Relationship expansion strategy Customer migration Cross/up-selling Customer referral management Customer involvement Prof. Dr. SSL {IDEA, STEM, RF, FP, C, LDV} / p. 13 Other problems Association rule analysis Logistics regression analysis Cluster analysis Decision tree analysis Artificial neural network analysis Prof. Dr. SSL {IDEA, STEM, RF, FP, C, LDV} / p. 14 7
Strategic Information Systems
Strategic Information Management Information Course Code: 166137-01 Course Name: Management Information Period: Autumn 2014 Lecturer: Prof. Sync Sangwon Lee, Ph. D Department: Business Administration University:
More information(Week 11) A06. IS Analysis & Design. Management Information Systems
(Week 11) A06. IS Analysis & Design Management Information Systems Course Code: 166137-01+02 Course Name: Management Information Systems Period: Spring 2016 Lecturer: Prof. Dr. LEE, Sync Sangwon Department:
More informationCHAPTER 8 APPLICATION OF CLUSTERING TO CUSTOMER RELATIONSHIP MANAGEMENT
CHAPTER 8 APPLICATION OF CLUSTERING TO CUSTOMER RELATIONSHIP MANAGEMENT 8.1 Introduction Customer Relationship Management (CRM) is a process that manages the interactions between a company and its customers.
More informationDATA MINING IN THE FINANCIAL SERVICES INDUSTRY
DATA MINING IN THE FINANCIAL SERVICES INDUSTRY PRESENTATION TO KNOWLEDGE DISCOVERY CENTRE (15 FEBRUARY 2001) Steven Parker Head CRM Consumer Banking Standard Chartered 1 STANDARD CHARTERED World s leading
More informationWhat are enterprise business systems? So is that what we will be studying?
Slide 1 Chapter What are enterprise business systems? Good Question!! The term Enterprise Content Management (ECM) refers to the technologies used to capture, manage, store, preserve, and deliver content
More informationData Mining. Implementation & Applications. Jean-Paul Isson. Sr. Director Global BI & Predictive Analytics Monster Worldwide
Data Mining Implementation & Applications Jean-Paul Isson Sr. Director Global BI & Predictive Analytics Monster Worldwide Mar-2009 Agenda Data Mining & BI Vision Implementation : Success Criteria Knowledge
More informationOracle Retail Data Model (ORDM) Overview
Oracle Retail Data Model (ORDM) Overview May, 2014 Content Retail Business Intelligence Key Trends Retail Industry Findings Foundation for Business Information Flows Retail is being Redefined Challengers
More informationSession 15 Business Intelligence: Data Mining and Data Warehousing
15.561 Information Technology Essentials Session 15 Business Intelligence: Data Mining and Data Warehousing Copyright 2005 Chris Dellarocas and Thomas Malone Adapted from Chris Dellarocas, U. Md. Outline
More informationMARKETING IN THE MODERN WORLD
MARKETING IN THE MODERN WORLD Traditional Marketing and Sales Marketing provides air cover Sales takes down deals But the Buyers Journey has Changed Buyers are doing more research before they call you
More informationChapter 6: Customer Analytics Part II
Chapter 6: Customer Analytics Part II Overview Topics discussed: Strategic customer-based value metrics Popular customer selection strategies Techniques to evaluate alternative customer selection strategies
More informationMarketing Technology Platform Overview
Marketing Technology Platform Overview What is Marketing Automation? The Right Message To the Right Person At the Right Time Technology that helps streamline, automate and measure marketing activities
More informationBusiness Data Analytics
MTAT.03.319 Business Data Analytics Lecture 1: Introduction Marlon Dumas and Anna Leontjeva FirstName. LastName @ ut.ee Your background Your expectations Warm-up question We are a charity. We have a database
More informationEnterprise Information Systems
ACS-1803 Introduction to Information Systems Instructor: Kerry Augustine Enterprise Information Systems Lecture Outline 6 ACS-1803 Introduction to Information Systems Learning Objectives 1. Explain how
More information12/02/2018. Enterprise Information Systems. Learning Objectives. System Category Enterprise Systems. ACS-1803 Introduction to Information Systems
ACS-1803 Introduction to Information Systems Instructor: Kerry Augustine Enterprise Information Systems Lecture Outline 6 ACS-1803 Introduction to Information Systems Learning Objectives 1. Explain how
More informationAnalytics for Banks. September 19, 2017
Analytics for Banks September 19, 2017 Outline About AlgoAnalytics Problems we can solve for banks Our experience Technology Page 2 About AlgoAnalytics Analytics Consultancy Work at the intersection of
More informationDONALD K. WEDDING, P.E., PH.D ANDOVER DR. TWINSBURG, OH (330) SUMMARY
DONALD K. WEDDING, P.E., PH.D. 10371 ANDOVER DR. TWINSBURG, OH 44087 (330) 405-0922 dwedding@acm.org SUMMARY DATA MINING SOFTWARE ENGINEERING Ten years experience in and Mathematical Modeling. Experienced
More informationValue Proposition for Financial Institutions
WWW.CUSTOMERS-DNA.COM VALUE PROPOSITION FINANCIAL INSTITUTIONS Value Proposition for Financial Institutions Customer Intelligence in Banking CRM & CUSTOMER INTELLIGENCE SERVICES INFO@CUSTOMERS-DNA.COM
More informationMachine Learning 101
Machine Learning 101 Mike Alperin September, 2016 Copyright 2000-2016 TIBCO Software Inc. Agenda What is Machine Learning? Decision Tree Models Customer Analytics Examples Manufacturing Examples Fraud
More informationFrom Customer Adoption to Retention Loyalty & Optimization for Mobile Commerce. From Customer Adoption to Retention
From Customer Adoption to Retention From Customer Adoption to Retention Loyalty & Optimization for Mobile Commerce Marika HACECKA, Dr. Tamer KESHI MAR - 2012 1 Agenda Proper Targeting with Products & M-Commerce
More informationCustomer Relationship Management (CRM) Basics
Customer Relationship Management (CRM) Basics Dr. Ulaş Akküçük AMA Definition A discipline in marketing combining database and computer technology with customer service and marketing communications. Customer
More informationPrime Performance Modeling. Changing the face of modeling through superior techniques
Prime Performance Modeling Changing the face of modeling through superior techniques Information is power Power to see. Power to understand. Power to act. Information is the power that drives business
More informationEnterprise Information Systems
Instructor: Kevin Robertson Enterprise Information Systems Lecture Outline 6/7 Learning Objectives 1. Explain how organizations support business activities by using information technologies across the
More informationIM S5028. Architecture for Analytical CRM. Architecture for Analytical CRM. Customer Analytics. Data Mining for CRM: an overview.
Customer Analytics Data Mining for CRM: an overview Architecture for Analytical CRM customer contact points Retrospective analysis tools OLAP Query Reporting Customer Data Warehouse Operational systems
More informationNew Features Summary. Version 11 February 2017
New Features Summary Version 11 February 2017 A better way to manage the entire business, at a lower cost and on a global scale 1 Most important new features and Financial Supply Chain Production Cloud
More informationNew Features Summary Product Version 11.0 February 2018
New Features Summary Product Version 11.0 February 2018 A better way to manage the entire business, at a lower cost and on a global scale 1 Most important new features and Financial Supply Chain Production
More informationMicrosoft Enterprise Cube. BPM Solutions for Today s s Business Needs
Microsoft Enterprise Cube BPM Solutions for Today s s Business Needs Today s OSS / BSS Reality in CSPs Portal Server CRM KM Communicator Collaboration & Tactics Server Federated Servers Network Monitor
More informationFinding Hidden Intelligence with Predictive Analysis of Data Mining
Finding Hidden Intelligence with Predictive Analysis of Data Mining Rafal Lukawiecki Strategic Consultant, Project Botticelli Ltd rafal@projectbotticelli.com Objectives Show use of Microsoft SQL Server
More informationCustomer Value Analytics for Banking & Capital Markets
Customer Value Analytics for Banking & Capital Markets Powered by SMART Analytics built on IBM Understand your customers, markets, business opportunities and risks As money is the heart of a financial
More informationIBM s Analytics Transformation
IBM s Analytics Transformation Value Capture from Big Data, Analytics and Cognitive Technologies Martin Fleming VP, Chief Analytics Officer, and Chief Economist Chief Analytics Office Analytics Aligned
More informationHostLogic SAP Hybris Marketing Presentation
HostLogic SAP Hybris Marketing Presentation Overview Business Environment SAP Hybris Marketing functionality SAP Hybris Marketing references Overview Business Environment SAP Hybris Marketing functionality
More informationMateri 11 Enterprise Business Systems. Management Information System Dr. Hary Budiarto
Materi 11 Enterprise Business Systems Management Information System Dr. Hary Budiarto Customer Relationship Management (CRM) Definition: The use of information technology to create a cross-functional enterprise
More informationCustomer Value Analytics for Banking & Capital Markets
Customer Value Analytics for Banking & Capital Markets Powered by SMART Analytics built on IBM Understand your customers, markets, business opportunities, and risks As money is the heart of a financial
More informationThe usage of Big Data mechanisms and Artificial Intelligence Methods in modern Omnichannel marketing and sales
The usage of Big Data mechanisms and Artificial Intelligence Methods in modern Omnichannel marketing and sales Today's IT service providers offer a large set of tools supporting sales and marketing activities
More informationHarnessing Predictive Analytics to Improve Customer Data Analysis and Reduce Fraud
Harnessing Predictive Analytics to Improve Customer Data Analysis and Reduce Fraud Patrick Shearman General Manager, Information Management HCF of Australia Ltd Technology and Innovation for Insurance
More informationThe Age of Intelligent Data Systems: An Introduction with Application Examples. Paulo Cortez (ALGORITMI R&D Centre, University of Minho)
The Age of Intelligent Data Systems: An Introduction with Application Examples Paulo Cortez (ALGORITMI R&D Centre, University of Minho) Intelligent Data Systems: Introduction The Rise of Artificial Intelligence
More informationH E L P F O R SALES TEAMS
HELP FOR SALES TEAMS LEAD RELATIONSHIP ANALYZE MARKET OPPORTUNITIES GENERATE, CULTIVATE, AND TRACK LEADS LEAD RELATIONSHIP Our Lead Relationship Manager helps sales teams track, rank-order, and follow-up
More informationCHAPTER 4 A FRAMEWORK FOR CUSTOMER LIFETIME VALUE USING DATA MINING TECHNIQUES
49 CHAPTER 4 A FRAMEWORK FOR CUSTOMER LIFETIME VALUE USING DATA MINING TECHNIQUES 4.1 INTRODUCTION Different groups of customers prefer some special products. Customers type recognition is one of the main
More informationEffective CRM Using. Predictive Analytics. Antonios Chorianopoulos
Effective CRM Using Predictive Analytics Antonios Chorianopoulos WlLEY Contents Preface Acknowledgments xiii xv 1 An overview of data mining: The applications, the methodology, the algorithms, and the
More informationRetail Business Intelligence Solution
Retail Business Intelligence Solution TAN Ser Yean Regional Sales Manager Data Servers & Business Intelligence IBM Software ASEAN Retail leaders will enhance traditional intuitive approaches with Advanced
More informationAchieving customer intimacy with IBM SPSS products
Achieving customer intimacy with IBM SPSS products Transformative technologies for the new era of customer interactions Highlights: Customer intimacy is an innovative strategy for helping organizations
More informationData-Driven Conversion Optimization Daniel Reinert Enterprise Sales Manager Oracle Marketing Cloud
Data-Driven Conversion Optimization Daniel Reinert Enterprise Sales Manager Oracle Marketing Cloud Swiss Online Marketing, Zurich 05.04.2017 Copyright 2017 Oracle and/or its affiliates. All rights reserved.
More informationTargeting & Segmentation
Targeting & Segmentation Targeting and Segmentation If Direct Marketing is the focusing of resources on the superior opportunity then targeting is the activity which identifies the superior opportunity.
More informationLeveraging Attitudinal & Behavioral Data to Better Understand Global & Local Trends in Customer Loyalty & Retention
Leveraging Attitudinal & Behavioral Data to Better Understand Global & Local Trends in Customer Loyalty & Retention Brian Griner, Ph.D. Science, Strategy & Technology for Relationship Management & Marketing
More informationUsing SAS Enterprise Guide, SAS Enterprise Miner, and SAS Marketing Automation to Make a Collection Campaign Smarter
Paper 3503-2015 Using SAS Enterprise Guide, SAS Enterprise Miner, and SAS Marketing Automation to Make a Collection Campaign Smarter Darwin Amezquita, Andres Gonzalez, Paulo Fuentes DIRECTV ABSTRACT Companies
More informationCOPYRIGHTED MATERIAL. Index. buying experience, impact on value perception buying patterns see purchasing patterns
Index 80:20 rule 19, 21, 32 accruals 49, 88 activity-based costing (ABC) 40, 58 60, 116 additional potential 130 1, 134, 147 8 evaluating 138 9 advocacy customer attractiveness criterion 212 13 measure
More informationNGDATA. Luc Burgelman, CEO
NGDATA Luc Burgelman, CEO Introduction The Company NGDATA Overview Helping data-rich companies drive connected customer experiences Recognised by the leading US-based CRM Magazine as one of the 7 Rising
More informationthe way we see it Insights & Data CustomerSMART Smarter decisions in customer value management
Insights & Data the way we see it SMART Smarter decisions in customer value management Capgemini s SMART solution helps enterprises better understand the behavior and buying preferences of customers, providing
More informationCustomer Profitability Customer Lifetime Value (CLV), Customer Equity (CE), and Shareholder Value
BA 597: Customer Profitability Customer Lifetime Value (CLV), Customer Equity (CE), and Shareholder Value 1 Today s Agenda To discuss how to calculate customer lifetime value (CLV) To show how it is calculated
More informationBusiness Data Analytics
MTAT.03.319 Business Data Analytics Lecture 1: Introduction Rajesh Sharma Marlon Dumas will give the last lecture on BPM Slides: Thanks to Anna and Marlon FirstName.LastName@ut.ee Your background Your
More informationIBM SPSS Predictive Analytics Workshop
An IBM Proof of Technology with IBM SPSS Modeler Agenda Welcome and Introductions Introduction to Predictive Analytics IBM SPSS Modeler Overview Exercise: Predictive in 20 Minutes IBM SPSS Modeler Basics
More informationClearing the Clutter: An Overview of the Marketing Analytics Ecosystem
Clearing the Clutter: An Overview of the Marketing Analytics Ecosystem Dr. Michael Koved Lecturer, School of Information November 14th, 2017 mkoved@ischool.berkeley.edu Introduction Speaker Introduction
More informationWhat s in Your Customer s Wallet? Best Practices to Grow Wallet & Market Share
What s in Your Customer s Wallet? Best Practices to Grow Wallet & Market Share October 26, 2017 Featuring: Jonathan Bein, Real Results Marketing Richard Blatcher, PROS Thomas P. Gale, Modern Distribution
More informationIncrease conversions, loyalty, and revenue through cross-channel experiences that are relevant, personal, and valuable.
Conversion OPTIMIZATION Webtrends for FINANCE Optimizing customer experiences Increase conversions, loyalty, and revenue through cross-channel experiences that are relevant, personal, and valuable. solution
More informationR CASE STUDY FROM EBAY APD.
R CASE STUDY FROM EBAY APD 李忠 zholi@ebay.com AGENDA EBAY APD Introduction R@EBAY APD Site Speed Case Study Buyer Segmentation Case Study Lesson and Learn Q&A 2 4 Analytics Platform Architecture EDW Singularity
More informationThe Customer LIFE-TIME-VALUE in the INSURANCE-INDUSTRY
The Customer LIFE-TIME-VALUE in the INSURANCE-INDUSTRY Table of Contents: Introduction Applications of Data Mining Modelling: Life-Time-Value Example: Customer Segmentation Conclusions by Günter Schmölz,
More informationManagement Update: The Evolution of Customer Relationship Marketing
IGG-12032003-01 G. Herschel, J. Radcliffe, K. Collins Article 3 December 2003 Management Update: The Evolution of Customer Relationship Marketing The value states of customer relationship marketing are
More informationSynergies between Risk Modeling and Customer Analytics
Synergies between Risk Modeling and Customer Analytics EY SAS Forum, Stockholm 18 September 2014 Lena Mörk and Ramona Klein Agenda 1 2 Introduction Modeling in the financial sector 3 4 5 Consequences from
More informationAn e3-value Pattern for Valuing Customer Retention Initiatives
An e3-value Pattern for Valuing Customer Retention Initiatives Matthieu De Coster, Wim Laurier, Geert Poels Department of Management Information and Operational Management, Faculty of Economics and Business
More informationWKU-MIS-B11 Management Decision Support and Intelligent Systems. Management Information Systems
Management Information Systems Management Information Systems B11. Management Decision Support and Intelligent Systems Code: 166137-01+02 Course: Management Information Systems Period: Spring 2013 Professor:
More informationApproaching an Analytical Project. Tuba Islam, Analytics CoE, SAS UK
Approaching an Analytical Project Tuba Islam, Analytics CoE, SAS UK Approaching an Analytical Project Starting with questions.. What is the problem you would like to solve? Why do you need analytics? Which
More informationINTELIGÊNCIA EM AÇÃO. 23 de setembro IBM Client Center Lisboa
INTELIGÊNCIA EM AÇÃO 23 de setembro IBM Client Center Lisboa Como satisfazer as necessidades de um cliente sempre ativo JOAQUÍN LACAMBRA DIRETOR DE SOFTWARE E SOLUÇÕES ANALYTICS, COMMERCE & SECURITY IBM
More informationANALYTICS FOR RESTAURANTS
ANALYTICS FOR RESTAURANTS Make the right decision every time Through insights about every area of your restaurant business Increase Customer Engagement Identify Growth Opportunities Democratize Analytics
More informationClass 1: Customer Analytics Overview
Class 1: Customer Analytics Overview Professor Florian Zettelmeyer Kellogg School of Management Customer Analytics The information revolution has given firms the possibility to know much more about their
More informationAlessandro Lavazzi. Design for Customer Engagement Constructing the Composable Enterprise for your Digital Marketing Strategy
Alessandro Lavazzi Design for Customer Engagement Constructing the Composable Enterprise for your Digital Marketing Strategy 1 About the Speaker Alessandro Lavazzi Customer Engagement Practice Manager
More informationCloud Sales: How to Adapt your Company Sales for the Cloud? Based on the session at the 2014 Cloud Symposium. An Alexander Group ebook
Cloud Sales: How to Adapt your Company Sales for the Cloud? Based on the session at the 2014 Cloud Symposium Atlanta Chicago San Francisco Scottsdale Stamford An Alexander Group ebook So Just How Big Is
More informationSAP Hybris Marketing Engage in Context to Drive Conversion and Loyalty. SAP Forum für Customer Engagement & Commerce
SAP Hybris Marketing Engage in Context to Drive Conversion and Loyalty [@thomas_ruhl] SAP Forum für Customer Engagement & Commerce INCREASING CUSTOMER EXPECTATIONS Relevant Customer Engagements Ultra Personal
More information12. E-Commerce Marketing Mix Channel
12. (Contents) E-Commerce Marketing Mix Channel Contents 12. E-Commerce Marketing Mix Channel E-Commerce Marketing Mix Channel Code: 166145-01 Course: Electronic Commerce Marketing Period: Autumn 2011
More information<Insert Picture Here>
Oracle and SPL - Acquisition Announcement Delivering the most complete, integrated end-to-end packaged solution to meet the unique needs of the Utilities industry Customer and Partner
More informationSAS BIG DATA ANALYTICS INCREASING YOUR COMPETITIVE EDGE
SAS BIG DATA ANALYTICS INCREASING YOUR COMPETITIVE EDGE SAS VISUAL ANALYTICS STATE OF THE ART SOLUTION FOR FASTER, SMARTER DECISIONS AIMED AT THE MASSES Data visualization Approachable analytics Robust
More informationE-Learning Course: Understanding Retail
E-Learning Course: Understanding Retail Target Audience This program is designed for people who sell or market to retailers. It is ideal for both merchandise suppliers who sell directly to retailers, and
More informationAdobe and Hadoop Integration
Predictive Behavioral Analytics Adobe and Hadoop Integration JANUARY 2016 SYNTASA Copyright 1.0 Introduction For many years large enterprises have relied on the Adobe Marketing Cloud for capturing and
More informationActionable Intelligence that Accelerates Profitable Growth. An Introduction to Zilliant IQ for Salesforce
Actionable Intelligence that Accelerates Profitable Growth An Introduction to Zilliant IQ for Salesforce Across industries, leading enterprises are turning to artificiai intelligence and machine learning
More informationUncover possibilities with predictive analytics
IBM Analytics Feature Guide IBM SPSS Modeler Uncover possibilities with predictive analytics Unlock the value of data you re already collecting by extracting information that opens a window into customer
More informationE-commerce An expert perspective
WEBINAR E-commerce Email An expert perspective BRETT ROBBINS, HEAD OF BUSINESS DEVELOPMENT, JORDAN, HEAD OF CUSTOMER INSIGHTS, 1 QUESTIONS? A few reminders 1. Why we re here 2. Chat your questions 3. Q+A
More informationPERSONALIZED (AND FUN!) CUSTOMER EXPERIENCE MANAGEMENT
PERSONALIZED (AND FUN!) CUSTOMER EXPERIENCE MANAGEMENT David Solana Co-Founder & CMO dsolana@opinator.com CHALLENGE: COMPANIES ARE STRUGGLING TO BUILD EFFECTIVE AND RELEVANT INTERACTIONS WITH CONSUMERS
More informationA 2-tuple Fuzzy Linguistic RFM Model and Its Implementation
Available online at www.sciencedirect.com ScienceDirect Procedia Computer Science 55 (2015 ) 1340 1347 Information Technology and Quantitative Management (ITQM 2015) A 2-tuple Fuzzy Linguistic RFM Model
More informationHow to build a profitable customer loyalty program 7 key steps to create customers for life AGENCY OF THE YEAR
How to build a profitable customer loyalty program 7 key steps to create customers for life AGENCY OF THE YEAR INTRODUCTION Customer loyalty in the age of the customer 2 Customer loyalty in the age of
More informationData Mining in CRM THE CRM STRATEGY
CHAPTER ONE Data Mining in CRM THE CRM STRATEGY Customers are the most important asset of an organization. There cannot be any business prospects without satisfied customers who remain loyal and develop
More informationChapter 8 Analytical Procedures
Slide 8.1 Principles of Auditing: An Introduction to International Standards on Auditing Chapter 8 Analytical Procedures Rick Hayes, Hans Gortemaker and Philip Wallage Slide 8.2 Analytical procedures Analytical
More information06 March INVESTOR DAY 2018 Sabre GLBL Inc. All rights reserved. 1
06 March 2018 1 Retailing, Distribution and Fulfillment for Hotels Clinton Anderson President, Hospitality Solutions 06 March 2018 2 HOSPITALITY SOLUTIONS PLAN SHOP PURCHASE TRAVEL RETURN RETAILING DISTRIBUTION
More informationExploiting IT for business benefit
Exploiting IT for business benefit EITBB 5. Customer relationship management benefit. BCS 1 Transactions versus relationships Transactions are usually: One-off purchases or uses of services With no automatic
More informationKeywords acrm, RFM, Clustering, Classification, SMOTE, Metastacking
Volume 5, Issue 9, September 2015 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Comparative
More informationWhy CRM? Why CRM? Service CRM. Our Mission. Achieving CRM Profitability: Making CRM Work. Employee Performance Management (EPM)
Making CRM Work Employee Performance Management (EPM) Presented To Seaport Hotel Boston, April 20, 2005 Presented By Peter Djokovich, President & CEO Strategix Performance, Inc. Our Mission Strategix Performance
More informationWHITE PAPER. Integrated customer insights
WHITE PAPER Integrated customer insights Customer centricity is the new voice for brands the world over. Every brand will have online and offline customers, depending on the touch points they wish to deal
More informationKNOWLEDGE BRIEF. Intershop Communications is Recognized as the 2017 Company of the Year in the Global Digital Commerce Platforms Market
KNOWLEDGE BRIEF Intershop Communications is Recognized as the 2017 Company of the Year in the Global Digital Commerce Platforms Market KNOWLEDGE BRIEF BY Intershop Communications is Recognized as the 2017
More informationCustomer Value: RFM and CLV
Study Unit 1 Customer Value: RFM and CLV ANL 309 Business Analytics Applications Introduction Concept of customer value Recency-Frequency-Monetary y y Value (RFM) approach to calculate customer value Customer
More informationRetail Sales BEST PRACTICES. A Collection of Best Practices for: Includes Detailed Best Practices for:
BEST PRACTICES A Collection of Best Practices for: Retail Sales Includes Detailed Best Practices for: - Merchandising - Store Planning - E-Commerce - Inventory Management - Store Operations www.opsdog.com
More informationCUSTOMER RELATIONSHIP MANAGEMENT
CUSTOMER RELATIONSHIP MANAGEMENT 1 Strouse, Karen G.(2004). Customer-Centered Telecommunication Services Marketing. Artech House. London Chapter 12 2 INTRODUCTION CRM general process of managing the various
More informationCase studies in Data Mining & Knowledge Discovery
Case studies in Data Mining & Knowledge Discovery Knowledge Discovery is a process Data Mining is just a step of a (potentially) complex sequence of tasks KDD Process Data Mining & Knowledge Discovery
More informationSurvey of Behavioral Segmentation Methods
Survey of Behavioral Segmentation Methods Written by Rhonda Carraway Petty Marketing Insights Data Scientist rpetty@mathnetix.com There is no magic rule or formula for deciding how to classify customers
More informationDrive More Revenue by Measuring and Managing Customer Lifecycle Value
Drive More Revenue by Measuring and Managing Customer Lifecycle Value The customer is at the center of every business transaction, and keeping the customer engaged has never been more vital than it is
More informationIM S5028. IMS Customer Relationship Management. What Is CRM? Ilona Jagielska 1
IMS5028 - Customer Relationship Management CRM Concepts and Definitions What Is CRM? CRM is a strategy for acquiring and retaining profitable customers CRM is a strategy for optimising the lifetime value
More informationBig Data Anwendungsfälle aus dem Bereich der digitalen Medien
Presented by Kate Tickner Date 12 th October 2012 Big Data Anwendungsfälle aus dem Bereich der digitalen Medien Using Big Data and Smarter Analytics to Increase Consumer Engagement Dramatic forces affecting
More informationKnowledge Solution for Credit Scoring
Knowledge Solution for Credit Scoring Hendrik Wagner Product Manager Data Mining Solutions SAS EMEA Agenda What is and why do Credit Scoring Enterprise Miner Case Study Project Delivery Enterprise Miner
More informationAcknowledgments... iii. Part 1: Marketing in Banking... 1
CONTENTS Acknowledgments... iii Part 1: Marketing in Banking... 1 Introduction... 1 Objectives... 1 Chapter 1: The Structure and Function of Marketing... 3 What is Marketing?... 3 Key Elements of the Definition...
More informationA Study on CRM and Its Customer Segmentation Outsourcing Approach for Small and Medium Businesses
A Study on CRM and Its Customer Segmentation Outsourcing Approach for Small and Medium Businesses Feng Qian Institute of Management Science & Information Engineering, Hangzhou Dianzi University, Hangzhou
More informationMIS Applications. Industry Specific - To input, capture, process, store, generate output and control business functions with IIPM information
MIS Applications Industry Specific - To input, capture, process, store, generate output and control business functions with IIPM information MIS in CRM 2 Strategic Relationships with Existing customers
More informationPredicting Customer Churn Using CLV in Insurance Industry
Shiraz Journal of System Management Vol. 2, No. 1, Ser. 5, (2014), 39-49 Predicting Customer Churn Using CLV in Insurance Industry Vahid Dust Mohammadi Department of Industrial Engineering, Tarbit Modares
More informationTop intelligent tools that every sales rep should have in 2017
Top intelligent tools that every sales rep should have in 2017 Key findings: Why artificial intelligence (AI) is a game-changer for organizations from various industries How sales reps can streamline their
More informationAdobe and Hadoop Integration
Predictive Behavioral Analytics Adobe and Hadoop Integration DECEMBER 2016 SYNTASA Copyright 1.0 Introduction For many years large enterprises have relied on the Adobe Marketing Cloud for capturing and
More information