Several popular software solutions will be used to support methods taught in the lecture portion of the course. In a vendor-neutral fashion, the hands-on exercises will demonstrate strengths and limitations of various techniques as well as guidelines for selecting the right tools for your application.

Participants will learn the basics of data collection, variable selection, complex data modeling, dynamic content personalization and CRM methods for the web. If you desire to make your web site an integral part of your organization's customer communications strategy, then this course is for you.

There are no prerequisites to this course. However, those wishing to delve more deeply into the data mining component of this course may consider TMA's "Data Mining: Level I and Level II courses. The data mining courses are highly complimentary and may be attended either before or after this offering.

WHO SHOULD ATTEND

IT/IS EXECUTIVES: CIOs, CKOs, CTOs, Functional Officers, Technical Directors and Project Managers

MARKETING MANAGERS: Customer Acquisitions and Customer Relationship Managers, Product Managers and Direct Marketing Managers

LINE-OF-BUSINESS EXECUTIVES AND FUNCTIONAL MANAGERS: eCommerce Directors, Business Forecasters, Inventory Flow Analysts, Financial Forecasters

TECHNOLOGY PLANNERS: Who survey emerging technologies in order to prioritize corporate investment

CONSULTANTS: Whose success requires competency with web mining, CRM and related emerging information technologies and whose competitive environment is intensifying
 

• Gain a competitive edge by leveraging your web site with CRM initiatives
• Plan and manage your web mining projects effectively from the start
• Optimize web communication strategies for personalized interactions
• Obtain a comprehensive view of your on-line customers
• Learn how to maneuver the double-edged personalization sword
• Raise response while reducing contact frequency
• Develop confidence in web mining concepts, jargon and methods
• Leave with resources, contacts and actionable plans to substantially reduce your project preparation time, costs and risks

When it comes to Internet marketing, many businesses are now learning from the expression, “Be careful of what you wish for.” While a few businesses were previously able to obtain a rich, behavior-based data on their customers, that is no longer the case. On the contrary, many businesses are drowning in a sea of web-generated data, and missing out on the benefits that information can produce.

This course focuses on taming and leveraging that data: turning it into competitive advantages. This three-day course ranges from the basics of how to discover unseen business opportunities through preparing the data, enhancing and analyzing it using state-of-the-art data mining techniques. Participants will learn advanced techniques for maximizing the true value of their web data.

These insights will allow organizations to dramatically improve CRM initiatives, operational effectiveness, and overall business profitability. The course will focus on getting the most from what organizations already have. Additionally, a wide variety of vendor solutions will be compared and contrasted using hands-on exercises.

• How to get started
• How web mining is being used and why
• Web mining and eCRM principles, methods, tools and business issues
• Where web data resources are; then how to filter, prioritize and leverage
• What are common project pitfalls and how to avoid them
• Project deployment, performance and maintenance issues
• When to enhance web mining with advanced data modeling techniques
• The importance of integrating web activity into your global CRM plan

WHAT MAKES THIS COURSE UNIQUE

This course is a vendor-neutral, hands-on presentation of evolving web mining topics and its role in innovative customer communications. The instructor's background in data mining technologies and tools, leadership in CRM projects and marketing communications, as well as diligence in recent eCommerce communication strategies provides a truly unique blend of experience to share with participants.

Leading tools will be used to illustrate and compare methods. Results will be drawn from actual web mining applications and interpreted in the context of business impact. Attendees will depart with a binder of course notes, direct hands-on experience and a valuable index of data mining resources.

OVERVIEW OF THE BASICS, PART I

• What Data is Captured From Web Sites and How
• Solve Operational Issues
  • Broken links
  • Server issues
  • Capacity planning failures
  • Timeliness issues
  • Inventory management
• Discover Customer Groupings
  • Responders
  • Non-responders
  • High profit potential
  • "Trojan Horse" customers
• Target Product Offerings
  • High Sellers
  • Stagnant products
  • Inventory
  • Potential product packages
• Target Pricing Offerings
  • Pricing sensitivity
  • Price testing
  • Promotional testing
   

OVERVIEW OF THE BASICS, PART II

• Increase Click-Through Rates
  • Finding "Path of Profit"
  • Identify roadblocks
  • Where to focus attention
  • Eliminating "page distraction"
• Increase Customer Satisfaction
  • Identifying largest issues
  • Tracking returns and paths
  • Eliminating phantom communication
• Personalize Communication with Customers
  • Personalization pros and cons
  • The privacy issue
  • Communication preference
• Reduce Costs
  • Reducing time per visit
  • Maximizing marketing dollars
  • Managing server capacity
  • Reducing service cost
   

DATA EXPLORATION AND PREPARATION

• What Format is the Data In?
  • Continuous vs. discrete variables
  • Flat files versus tables
  • Packed versus unpacked
  • Fixed length versus variable length records
• How Can the Data be Enhanced?
  • Real-time enhancement
  • Batch enhancement
  • External sources versus internal sources
  • When to change a data element
• Should the Data be Stored in its Original Format?
   

DEFINING THE PROBLEM

• Why This is Isn’t as Easy as it Sounds
  • Response myopia
  • LTV analysis
  • Beware of what you wish for
• Problem Category Considerations
  • Discrete versus continuous outcomes
  • Degree
  • Pitfalls and temptations
• Variable Considerations
  • Discrete versus continuous
  • Sources
  • Age of data
• Iteration Considerations
  • How many iterations are appropriate?
  • Signals to stop
  • Meta-model factors
  • Concerns of over-fitting
• Examples of "Problematic Problems"
  • Who are my best customers?
  • Tell me everything about my customers / operations, etc.
  • Differences between modeling and magic
• Examples of Appropriate Problems
  • What is the most frequent buying path?
  • How do I know who is likely to buy?
  • To whom should I mail for my next solicitation?
   

DATA MODELING TECHNIQUE SELECTIONS

• Walk Before You Run
  • Cross-tabs
  • Other reporting options
  • Bar charts
  • Other visualization techniques
• Data Mining and Modeling
  • Why Data Mining?
  • Capabilities, limitations & pitfalls
  • Clustering techniques
  • Continuous outcome techniques
  • Discrete outcome techniques
  • Translating results into actions
   

KEY APPLICATIONS

• Operations
• CRM
• Profitability
   

HANDS-ON LAB EXERCISES

• Interspersed throughout to support the lectures

• Preparing web data for CRM applications
• Response modeling & campaign management
• Cross-selling and targeted content presentation
• Web-based personalization methods
 

WHERE TO GO FROM HERE

• Resources
  • Web
  • Software
  • Journals
   

CONCLUDING REMARKS
 

T. SCOTT CLENDANIEL is a senior-level consultant with 16 years experience in CRM, eCRM, data mining, database marketing and strategic planning for such companies as Citigroup, Bristol-Myers Squibb, and The Royal Bank of Canada. Scott served as a Senior Staff Scientist at Maryland-based Neuristics, an artificial intelligence applications company. He was the Vice President of Consumer Strategic Planning and Analysis at the Bank of Hawaii and Vice President / Director of Credit Card acquisitions at CoreStates Bank of Delaware.

Scott has been developing and deploying data mining solutions since 1994 when he worked on the first custom predictive model for MBNA’s credit card acquisition efforts. Since then, he has been a practitioner, trainer, and national lecturer on the topic. He has combined that data mining experience with several web-based marketing efforts, most notably for Bristol-Myers Squibb, where he was responsible for designing and implementing the database aspects of web marketing for national pharmaceutical campaigns. Scott is a member of Baylor University's CRM Corp of Experts.

Scott obtained his MBA from the University of Baltimore in 1990, and his BS from the same institution in 1996. Scott has become well-known for his unique combination of technical knowledge, “real-world” application experience, and a unique and colorful presentation style.
 
  

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