How to gain customer insight to implement a successful profit-driven database marketing strategy

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'THE NEW DIRECT MARKETING' - NEW THIRD EDITION

The ultimate handbook for companies who use direct marketing as a marketing channel, marketing statisticians and for every user or developer of database and direct marketing methods.  

Good customers are too valuable - and hard to find - for you to risk losing them, especially by being passive, indifferent, or indistinguishable from your competitors. 'The New Direct Marketing, Third Edition', shows you how to combine database technology and statistical analysis with innovative direct marketing methods to first identify, and then profit from, your customers' all-important needs, desires, likes, and dislikes.

The unique, authoritative reference work on database management theory and practice for over a decade, now exclusively revised and updated to encompass today's new technology, 'The New Direct Marketing, Third Edition', is your key to developing customised, customer-focused marketing programs and strategies. Detailed concepts are explained and supported with easy-to-understand graphs, charts, and case studies, giving you the tools you need to:

• Offset sky-rocketing marketing costs by customising the sequence and flow of your communications 

• Target promotions and bonus offers based on your customers' previous purchases, buying patterns and stated preferences. 

• Create ongoing customer dialogues, giving you a constant incoming stream of valuable demographic, psychographic, and lifestyle data

All customers are not created equal. Updated knowledge and strategies you learn from 'The New Direct Marketing, Third Edition', will help you expand the boundaries of database marketing applications, and deploy your marketing spend more efficiently in today's take-no-prisoners direct marketing battleground.

After analysing past sampling results, a major health and beauty aids company immediately stops mailing to under-performing segments. As a result, they significantly improve their cost efficiencies produce valuable store traffic, and are able to negotiate better in-store displays and shelf space. A leading package goods marketer, employing a combination of usage and demographic data, develops markedly different strategies for different segments - optimising and acting upon their strengths and weaknesses.

Marketing has changed - dramatically. Once focused on products and the need to identify and exploit product-specific 'gaps' and advantages, successful marketers now must focus on customers, positioning products, and customising services to reach and satisfy widely disparate market niches. 'The New Direct Marketing', Third Edition, is the only single source that covers all the interconnecting components of direct marketing, showing you through up-to-date research and examples like those above how to cut through the clutter and sell your products to today's increasingly wary and jaded consumer.

This classic text is more that just a surface treatment of successful direct marketing methods or a data-heavy, mathematical treatise on statistics and probabilities. The joint product of many knowledgeable authors, 'The New Direct Marketing', Third Edition, explains statistics and economics as they relate to efficient direct marketing applications, in effect showing you how to make it all work. The only text to approach direct marketing statistics and predictive and segmentation modelling from a uniquely non-mathematical perspective, it uses cutting-edge research plus real-world examples and case histories drawn from today's business pages to:

• Explain direct marketing's interrelationship with a complete range of distinct disciplines - marketing, technology, statistics and modelling tools, and economics

• Help you establish ongoing consumer dialogues that will benefit both your customers (actively indicating what they want or need) and your company (more timely and accurate information on usage and buying habits will invariably lead to increased sales)

• Explore direct marketing's numerous technological changes in recent years, giving you the latest information and analysis on new developments including data mining, modelling, statistical analysis, data warehouses, CHAID (AnswerTree) and profitable use of the Internet     

As we swing into the 21st century, attention has shifted from 'mass' marketing, designed to reach large segments of the buying public, to 'individual' marketing, designed to focus on, reach, and satisfy each potential customer. At the same time, the scope and technical complexity of the tools used to reach and gather information on this fragmented market have increased exponentially. 

Let 'The New Direct Marketing', Third Edition - the best-selling reference guide to database marketing's more advanced technical aspects - show how to locate and capture the detailed customer information you need, precisely identify who is buying what (and why), and beat your competition to new marketing opportunities with more speed and accuracy than ever before.

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Contents...

OVERVIEW OF THE NEW DIRECT MARKETING

• Introduction

• The New Direct Marketing - What Is It?; The Premise of the New Direct Marketing; An Overview of Some of the Advantages and Practices of the New Direct Marketing; Lead Grading; Customised Targeting at the Right Time; New Information and Past Results Help Formulate Strategies; Information Can Drive New Program and Fuel New Revenue Sources; Information Can Foster New Services and Generate Repeat Orders; Ongoing Communications Efforts Can Increase Customer Loyalty; Summary

• Contact Strategy Introduction

• Contact Strategy - What Is It?; RFM: The Workhorse Variables of Both the New and the Old Direct Marketing; Using Purchase History Information to Develop Contact Strategies; Using Promotion History to Define Contact Eligibility and Propensity to Respond; Using Demographic Data to Create Actionable Market Segments for the Purpose of Contact Strategy; Combining Both Purchase History and Demographic Data Can Lead to New Opportunities; Using Attitudinal Data to Create Actionable Market Segments for the Purpose of Contact Strategy; Specific Examples of the Role of Contact Strategy; Summary; Marketing Program Strategy Guideline Checklist

• Buzzwords

• A Word About Buzzwords; Buzzword 1: Generation of Languages, Procedural Languages; Buzzword 2: SQL; Buzzword 3: Flat Files and VSAM File Structures; Buzzword 4: Indexes, How Indexes Are Used; Buzzword 5: Productivity Tools; Buzzword 6: Logical and Physical Design; Buzzword 7: CPU, Channel, Channel Contention, Direct Access Storage Device (DASD), Seek Time; Buzzword 9: Types of Database Products, Hierarchical, Inverted File, Relational, Proprietary Database Systems, Other Database-Related Topics; Buzzword 10: Internet Buzzwords

• Sources and Uses of Marketing Data Customer and Prospect Data

• Customer Data, Prospect Data, Non-transactional Data Sources; Examples of the Type of Data Collected from Three Types of Direct Marketing Business: Financial Services Marketers, Examples of Questions Asked by Financial Services Marketers, Negative Options and Continuity Marketers, Examples of Questions Asked by Book and Music Clubs, Insurance Marketers, Using Questionnaires to Gather Data, Using Survey Data to Assign Customers and Prospects to Segments; Data Purchased from Third-Party Sources: National Databases as Sources of Data for File Enhancement, National Databases as Sources of Names, Using Acquired Data to Predict Segment Membership

• Relationship Marketing and How It Relates to the New Direct Marketing

• Some Background and Attempts at Definitions; Mass Markets; Today's Markets - The Impact of Technology; Today's Markets - The Impact of Demographic Trends; Relationship Marketing = Customer Retention and Share of Customer; Developing Relationship Marketing Capabilities; Customer Information; Customer Information; Customisation and Added Value; Two-Way Communication and Increased 'Bandwidth'; Relationship Marketing and Marketing Objectives

• The Role of Direct Marketing in Building Brands Conventional Wisdom

• What Does It Mean to Build Brand Equity?; Building Awareness Through Direct Marketing: Communicating Quality; Building Other Associations Through Direct marketing; Building Loyalty Through Direct Marketing; Conclusions and Summary

• Customer Service and Direct Marketing Required Customer Services Capabilities

• Information Needed by Customer Service; Marketing Information can be collected by Customer Service; Capturing Survey Data; Marketing Information to be provided to Customer Service; Customer Service and the Internet
  

DATA AND MARKETING DATABASES

• What Do You Want Your Database To Do and Why Do You Think It Will Do It? 

• Introduction; Key Issues to Consider Before Starting a Marketing Database Project: One Size Does Not Fit All, Cost-Justifying the Investment in a Marketing Database, How a Marketing Database Will Affect the Organisation, Data: Learning to Live with Imperfect Data, Managing Expectations - Everybody's Expectations, Objectives, Processes and Requirements, Marketing Tools, Business Needs and Functional Requirements, User-Friendly Environments, Turnaround Times

• Building a Marketing Database A Framework for Implementing a Database Project 

• Will the Database Be Created and Maintained In-House or at an Outside Service Bureau?: Cost, Control, Customisation, External Vendors, A Combined Approach; What Data Is Needed to Perform the Required Functions?: Identify the Files to Be Included in the Database, review the Data Elements Contained in Each Contributing File; Define Data Elements That Must Be Created During the Update Process; How Will Data Get Into the Marketing Database?: In-House Processing Implications, Service Bureau Processing Implications; decide Which, If Any, Data Enhancements Files Will Be Used; Consolidating Records: Duplicate Identification, Address Standardisation, Matching Issues, Scrubbing, House-holding; Develop a Preliminary Database Design; Frequency of Update or Replacement: Creating Separate Databases for Marketing to Avoid Conflict, Levels of Detail of Data; Will the Database Be Updated or Replaced?; Return to the Business Needs and Determine the Adequacy of the Plan for Meeting Those Needs

• Using Data Hygiene to Identify Individuals and Households Real World Issues

• Data Hygiene: Other Benefits of Data Hygiene; Applying Hygiene; Name Standardisation; Address Standardisation: Postal Address Standards; File Scrubbing; Determining Deliverability; Comparison Among Files: Duplicate Identification, House-holding, Other Uses of Duplicate Information; Merge/Purge Techniques and Software; Using Address Hygiene for Marketing Databases: The Consolidation Process, Establishing More complex Relationships

• Campaign Management Campaign Phases

• Management Processes; The Campaign Planning Phase; The Campaign Development Phase; The Campaign Execution Phase; The Campaign Analysis Phase: Profile Analysis, Response Analysis; Campaign Content and Structure Data; Actuals Data; Conclusion
  

WHAT DIRECT MARKETERS NEED TO KNOW ABOUT TECHNOLOGY 

• Operations and Decision Support Systems

• A Very Brief History of Computer Applications in Business; Operating Support Systems for Day-to Day Processing; Decision Support Applications Can Be a Drain on Mainframe Resources; Decision Support System: Need for Flexibility and Quick Response, DSS Technology; Integrating Operations Support Systems and Decision Support Systems

• The Unique Requirements Direct Marketers Place on Their Decision Support Systems Direct Marketing's Functional Requirements

• Hardware and Software Fundamentals Hardware: Mainframes, Midframes, Workstations, Microcomputers. All Database Management Systems Require a Great Deal of Computer Capacity; Software; File Structures

• Trends in Technology Improvements in Price Performance

• Multiple CPU's; Open Systems Architecture: Standard Interfaces, Evolution of Relational DBMS's, Salient Characteristics of Relational DBMS's, Capabilities and Performance of SQL, Post-SQL Processing for Direct Marketing, The Performance Dilemma, Solutions to the Database Performance Problem; Data Warehouses and Data Marts: Enterprise Data Warehouses, Data Marts, OLAP/EIS, On-Line Analytical Processing, Executive Information System, The Marketing Operations System

• Client Server Systems Client-Server Technology 

• Benefits of Client-Server Configurations; Different Kind of Clients; Different Kinds of Servers; Different Types of Networks; Examples: Happy Combination of Old and New Technologies, All New Technology, Multi-location Installation Using All New Technology; Revisiting the Wish List and Outlining Future Steps
  

BASIC STATISTICS AND MODELLING 

• The Basics of Statistical Analysis The Process of Data Analysis

• Pictures of Data: Stem and Leaf; Numerical Summaries: Centre of Data, Variation Within the Data; Confidence Intervals: Theorem 1, Theorem 2; Confidence Intervals and Tests of Significance for Response Rates: Theorem 3; Tests of Significance - Two Types of Errors and Power

• Relationships Between Variables Correlation Coefficient

• Correlation Coefficient for Scalar Variables, Correlation Coefficient in Practice; Simple Regression: The Regression Line, Simple Regression in Practice; Straightening Out the Data: Explanatory Power, Predictive Power

• Multiple Regression Multiple Regression Statistics

• How to Read Them: Quick and Dirty Regression, More Quick and Dirty Regression; Regression Built With Care: Step 1 - Examination of the Correlation Matrix, Step 2 - Normalisation of All Variables, Step 3 - Checking for Linearity; Rerunning the Model; Validation - Choosing the Best Model; Multiple Regression - Some Odds and Ends: Interaction, Multi-collinearity, Selection of Variables

• Response Analysis Introduction

• Logistic Regression: Concepts and Definition, Logistic Regression Model, Logistic Equation, Summary Variables, Logistic Coefficients; Discriminant Analysis; Automatic Interaction Detection - AID/CHAID; The SI-CHAID Analysis of the Same Data; Using CHAID in Regression Analysis; Multiple Regression: Guidelines for Building a Model

• Segmentation Analysis Data Needed for Segmentation Modelling

• Factor Analysis: What It Is and When You Should Use It; How Factor Analysis Works; Running and Interpreting Factor Analysis; Cluster Analysis: What It Is and When You Should Use It; How Cluster Analysis Works; Running and Interpreting Cluster Analysis; Using Small-Sample Survey Data to Segment a Much Bigger File; Concluding Example and Review

• A Closer Look Back A Closer Look at r, the Correlation Coefficient

• Review of r; Re-matching: Rematch Example, Re-matching Phi; Implication of Re-matching; A Closer Look at Model's Own Power: An Example; A Closer Look at Straightening Data; Ladder of Powers; Bulging Rule: An Example of the Bulging Rule; A Closer Look at Re-expressions for Many Variables: A Simple Principle Components Analysis (PCA) Example; Algebraic Properties of PCA; Model Building with PCA - Two Case Studies: A Continuity Example, A Packaged Goods Example

• Artificial Neural Networks Introduction

• When Are ANN's Used: Classification, Prediction; What Are ANN's?: Definition, Basic Structure, Basic ANN, Basic Architecture; How ANN's Are Trained: Supervised Training Method; Designing an Optimal Multi-layer Feed-forward ANN; The Black Box ANN; Proof of the Pudding: ANN Model; Logistic Regression Model: Reruns, Discussion
  

ADVANCED MODELLING 

• Assessment of Direct Marketing Response Models Accuracy; Decile Analysis; Precision; Separability; All Together Now (Discussion)

• Direct Marketing Models Using Genetic Algorithms What Is Optimisation? 

• What Is a Genetic Algorithm?; Illustration of a Simple GA: Reproduction, Crossover, Mutation; GA's Today; GA's: Strengths and Limitations; The Genetic Algorithm DMAX Model: DMAX Fitness Function, DMAX Response Model, Powerful Response Model, DMAX Discrete Profit Model, DMAX Regression, DMAX Improvement Over Ordinary Regression, DMAX Guarantee

• Bootstrapping in Direct Marketing Traditional Response Model Validation

• Illustration; Three Questions; The Bootstrap; How to Bootstrap; Simple Illustration; Bootstrap Performance; Bootstrap Decile Analysis Validation; One More Question; Bootstrap Computation; Summary

• What Do My Customers Look Like? 

• Look at the Stars! Star Graph Basics; Illustration; Star Graphs for Single Variables; Star Graphs for Many Variables; Conclusion

• Alternative Direct Marketing Response Models

• Linear Probability, Logit and Probit Models Linear probability Model; Logit and Probit Models; Illustration; Discussion of Table 28-5; Conclusion

• CHAID for Interpreting a Logistic Regression Model Logistic Regression Model; Direct Marketing Response Model (Real Study); CHAID; CHAID Trees; CHAID Tree Graphs; Summary

• Market Classification Modelling with Logistic Regression Binary Logistic Regression

• Some Notation; Polychotomous Logistic Regression; Model Building with PLR; Market Segmentation Classification Model: Survey of Cellular Phone Users, Data, CHAID Analysis, CHAID Tree Graphs, Market Segment Classification Model; Summary

• Modern Methods of Testing in Direct Marketing Introduction 

• Common Direct Marketing Testing Rules: Test One Thing at a Time, Test all Things; Statistical Experimental Design: Designed Experiments, Experimental Designs, Analyses of Experimental Designs, Blocking; Efficiency of Experimental Designs; Multifactor Experiments: Factorial Experiments: Factorial Experiments; Statistical Experimental Design Rules
  

ECONOMICS, LIFETIME VALUE, AND THE ROLE OF MODELLING IN THE NEW DIRECT MARKETING

• An Introduction to the Economics of the New Direct Marketing Implied versus Contractual Relationships

• Classical Direct Marketing versus Database Marketing; The Search for the Perfect Control; Once the Customer I on the File' Some Assumptions About the Economics of Multi-divisional Databases

• Back to Basics: The Economics of Classical Direct Marketing Solo Promotions 

• Multi-step Promotions Leading to a Sale; Catalogue Sales; Continuity Sales; Negative Option Clubs; Newsletter; Magazines; Performance Measurement: Front End versus Back End performance, Calculating CPM for Different Direct Response Media; Measuring Response: One Step Promotions, Two Step Promotions; Calculating Cost per Response: One Step Promotions; Tracking Back End Performance: Measuring Back End Performance, Attributing and Measuring Lifetime Value in a Financial Services Environment, The Return of the Chick or the Egg Problem; Measuring Profitability: Combining Front End and Back End Measurements; ROP and the Infamous 2 Percent Response Rate; The Present Value Concept

• The Role of Modelling in New Direct Marketing

• The Difference between Scoring Models and Forecasts: Obtaining Forecasts of Response, Applying Scoring Models to Forecasts, Implementing Scoring Models to Forecasts, Implementing Scoring Models at the Individual Level; Response Modelling: RFM versus Regression: Eliminating Arbitrary Decisions from RFM, Tree Analyses Compared with RFM Analyses, A Quick Review of Interaction Variables, Trees as a Benchmark Against Regression, CHAID, the Great Equaliser; Using Principal Components to Model Product Usage Patterns; Regression Models: Reminder About Ordinary versus Logistic Regression Models, How to Determine the Right Number of Variables to Include in Your Model; Typical Response Model results; ZIP Code Models: Adjusting for ZIP Code Size, Modelling Variables Other Than Response; Combining Models Modelling Profit: A Word of Caution: Regarding Combined Models, Lead-conversion Models, Attrition Models; Adding Household-level Overlay Data to Prospect Models; Adding Household-Level overlay Data to Internal Customer Models; Enhancing Your Database with Internal Survey Data; Implementing Models; Modelling, Managing and Marketing to Unique Customer Segments

• Applications of the New Direct Marketing 

• Moving from the Old to the New Direct Marketing; General Applications of the New Direct Marketing: Respond to Events, Create Market Segments - One Customer at a Time, Predict Customer/Prospect Behaviour, Create, Test and Evaluate Marketing Strategies; Specific Direct Marketing Applications: Marketing Direct Marketing Applications: Marketing to Current Customers, New Customer Acquisition

• Financial Models Negative Option Clubs

• Calculating Lifetime Value, "What If" Scenarios; Building Catalogue Models: Calculating Lifetime Value...

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