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Overview
This course emphasizes strategic and analytical approaches to customer relationship management including identifying good prospects and customer
acquisition; customer development via up-selling, cross-selling and personalization; customer attrition and retention; and customer lifetime value. The course will introduce issues, techniques and terminology
associated with database marketing and data mining.
The course emphasizes the strategic and analytical aspects of CRM.
Specific topics will address: assessing lifetime valuation (LTV) of customers and identifying 'high potential' customers; estimating return on marketing investment; and building predictive models to estimate the probability of response to a marketing campaign.
Tools and techniques covered include customer lifetime value analysis, decile analysis, RFM (reach/frequency/monetary) analyses, and predictive models
using logistic regression and 'machine learning algorithms' (decision trees such as CHAID in particular).
The course addresses three broad themes: 1) Customer-centric marketing, customer lifecycles and customer economics, 2) Marketing analytics including
predictive modeling, and 3) Strategic Initiatives in customer relationship management. The first theme explores what customer-centric marketing, customer relationship management and one-to-one marketing mean.
The customer lifecycle is introduced as in integrating framework. The importance of customer profitability and lifetime value as a criterion in CRM decisions is emphasized. The second theme emphasizes
the analysis of customer data including different types of predictive models.
We are often interested in predicting something - whether a customer will respond to a particular marketing offer, whether a customer will attrite or leave, or which of our other products a customer would be most likely to purchase next. There are different methods for building predictive models ranging from simple to very sophisticated. The third theme focuses on strategic marketing applications of CRM including customer acquisition, customer development and customer retention - as well as metrics to measure and monitor results.
Goals
The principal objectives of the course are:
- To build your knowledge of a rapidly emerging marketing arena - customer-centric marketing - which some claim is the beginning of a new business
paradigm.
- To emphasize the importance of the customer lifecycle and customer value in CRM decision
- To emphasize how analytical CRM can help accomplish strategic marketing initiatives and improve firm profitability
- To recognize that there are often two sides to customer-centric marketing or customer relationship management (CRM) - what is good for the firm
may not always be good for the customer.
- To expose you to several commonly used advanced modeling techniques
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Course Format, Readings and Resources
The course focuses on analytical CRM (in contrast to operational CRM which focuses on managing customer touchpoints) and its applications for strategic
marketing initiatives. Course topics center around three main themes: 1) Customer-centric marketing, customer lifecycles and customer economics, 2) Marketing Analytics, and 3) Strategic Initiatives
in customer relationship management. We begin by exploring what 'customer-centric marketing,' customer relationship marketing, and one-to-one marketing mean. The customer lifecycle is introduced as an
integrating framework and you will learn how to estimate customer profitability and lifetime value.
The marketing analytics component includes tools of varying sophistication. Often we are interested in predicting something – whether a customer will
respond to a particular marketing offer, whether a customer will attrite or leave, or which of our other products a customer would be most likely to purchase next. There are different methods for building
predictive models ranging from simple to very complex. RFM (recency/frequency/monetary) analysis is a relatively simple – but powerful – technique that has long been used by direct marketers and is
still widely used in various forms. Statistical models such as regression are also widely used and recently there has been growing interest in and use of data-mining techniques.
The strategic initiatives component of the course focuses on how customer data combined with marketing analytics can be applied to strategic marketing
applications including customer acquisition, customer development, and customer retention.
CRM is an emerging and evolving topic. Thus we will rely fairly heavily on course notes and cases that I have written plus an assortment of
articles from the business and trade press as well as some cases from Harvard and Darden.
You will find that the course website is quite extensive. On it you will find numerous links to relevant websites and white papers. I have
also tried to include a sentence or two for each of the course readings to help explain why I think them important.
Readings
All of the course materials are available electronically. Most of the readings are found in the course materials section of the BlackBoard
site. The Harvard cases and readings are also available through a link on the BlackBoard site. Finally there are a few readings which you can download from the course website
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Assignments and Grading
Individual Assignments
There are 4 written individual assignments. These all focus on analytical tools: (1) lifetime value analysis, (2) RFM analysis, interpreting (3)
logistic regression and (4) decision trees.
Team Paper
In teams of 3 or 4, you will complete a 6-8 page paper (1.5 spaced) on a topic directly related to some aspect of Customer-Centric Marketing. My
goal is to give you plenty of freedomto select a topic of interest to you. We will talk more about this when we meet in May.
Options include:
i) focusing on the use of CRM within an industry or
ii) focusing on a CRM-related topic
For example, you may complete a paper on CRM in a specific industry - such as telecom, pharmaceuticals, financial services, or retail. Alternatively you might
focus on a topic such as privacy issues, personalization, customer lifetime value, or loyalty programs.
Final Exam
There is a final exam which will include a mixture of objective (True/False and Multiple Choice) and short answer questions. It will be posted
toward the end of the course.
Grades will be based on the following course requirements:
Assignment: Tuscan Lifestyles: Lifetime Value 10 %
Assignment: Assessing RFM at Tuscan Lifestyles 10 %
Assignment: Predicting Response at BookBinders: Logistic Regression 10 %
Assignment: Predicting Response at BookBinders: Decision Trees 10 %
Team Paper 25 %
Participation 10 %
Final Exam 25 %
Total 100 %
Final Thoughts
I am excited about this 'quasi-distance' course.
I believe the course material is a good fit for this learning model. I encourage you to 'block' out several time slots each week to work through the material. I have tried to incorporate a mix of readings, links, puzzles, 'test your knowledge' quizzes, and assignments that are interesting and relevant. At the end of the road - I hope that you will look back on the journey as a fun and valuable learning experience!
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