This version: 9/17/07

 

Prof. Florian Zettelmeyer

florian@haas.berkeley.edu

http://faculty.haas.berkeley.edu/florian/itbm/
(Please see the Catalyst page for this course for an ID and password for the site)

 

Office Hours: Wednesday 4:30-5:30 p.m. (from September 17 to October 29 in S300T, otherwise in F-698)

                       Wednesday 7:30-8:15 p.m. (for evening section) in class room

 

Lab Sessions: Tuesday 5:00-6:00 p.m. and Wednesday 4:30-5:30 p.m. from September 18 to October 31
                       in S300T (no lab session on October 8)

 

 

Monday, August 27 (day section)

Wednesday, August 29 (evening section)

 

Objectives:

·       To provide an overview of the course topics and requirements.

 

Readings:

·       None

Wednesday, August 29 (day and evening sections)

 

Objectives:

·       To introduce the possibilities that information technology has provided for marketing to individual consumers.

·       To understand in a real-life example how a company used customer information to become customer-centric

 

Readings:

·       HBS Case 9502011: "Harrah's Entertainment Inc."

·       Loveman, Gary: “Diamonds in the Data Mine” HBR OnPoint 3647, 2003

·       Zeithaml, Rust, and Lemon, "The Customer Pyramid: Creating and Serving Profitable Customers," California Management Review, Vol.43 (4), Summer 2001

 

Preparation:

·       Prepare "Harrah's Entertainment Inc." for class discussion

 

Preparation Questions:

·       What are the objectives of the various database marketing programs?

·       Is the New Business Program working? Use the data in exhibits 2b to make the calculation. What about the other programs?

·       Why is it important to use the “customer worth” in the data base marketing efforts rather than the observed level of play?

·       How does Harrah’s integrate the various elements of its marketing strategy to deliver more than the results of database marketing?

 

Plan ahead:

·       For class 6 you will need to bring your laptop to class with Stata installed. If you have not yet installed Stata please do so for class 6.

Wednesday, September 5 (day and evening sections)

 

Objectives:

·       To introduce the notion of the customer lifecycle

·       To understand the concept of customer profitability

·       To understand the basics of lifetime value calculations

·       To explore how lifetime value can be used to guide marketing decisions

 

Readings:

·       Glazer, Rashi, "Winning in Smart Markets," 1999 Sloan Management Review, Summer 1999

·       HBS Case 9503019: "Customer Profitability and Lifetime Value"

·       “The Customer Life Cycle”

·       Optional: Dhar and Glazer, "Hedging Customers," Harvard Business Review, May 2003

Wednesday, September 5 (evening section)

Monday, September 10 (day section)

 

Objectives:

·       To refresh your knowledge of basic statistics (and show how it is useful for addressing marketing questions)

·       To learn how to determine the association between variables

·       To learn how to read and interpret regression output

 

Readings:

·       “Tips For Using Statistics In Information- and Technology-Based Marketing”

·       Review notes from a previous statistics class on hypothesis testing and regression

Wednesday, September 12 (day and evening sections)

 

Objectives:

·       To apply lifetime value calculations

 

Readings:

·       "Home Alarm, Inc.: Assessing Customer Lifetime Value"

 

Preparation (Individual Assignment Due; Accounts for 10% of Class Grade):

·       Prepare "Home Alarm, Inc.: Assessing Customer Lifetime Value" for class discussion and as individual assignment.

·       Please submit the assignment online (please submit only one file and only in pdf format) using Catalyst (select the day of this class in the calendar in Catalyst to access the link for submitting the assignment). Please note that you need to be using Windows XP with IE6 to do this reliably. Please note that Catalyst will no longer accept submissions once the class has started.

 

Preparation Questions:

1.     What is the LTV (looking 6 years out) of a customer who used auto-pay?

2.     What is the LTV (looking 6 years out) of a customer who did not use auto-pay?

3.     What is the maximum amount that Home Alarm could spend on customer and salesperson incentives to convert a residential customer to auto-pay?

4.     List three marketing programs that Home Alarm should consider to sign up new customers with auto-pay.

5.     Is looking 6 years out long enough for a LTV calculation for Home Alarm? If so, why? If not, why not?

 

Write-up Instructions:

·       Page 1: Spreadsheet showing LTV calculations (questions 1 and 2)

·       Pages 2 & 3: Questions 3-5 (with at least 1.5 line spacing).

·       I strongly encourage you to label your calculations, footnote any assumptions, etc. It is in your best interest that I not have to struggle to unravel where your numbers came from

 

Hints:

1.     When calculating the LCV, you should apply the discount rate to revenues and cost incurred already in the first year of servive.

Wednesday, September 12 (evening section)

Monday, September 17 (day section)

 

Objectives:

·       To master basic analysis with the statistics program “Stata”

 

Readings:

·       “Stata Primer”

·       “The BookBinders Book Club: Basic Customer Analysis”

·       “Stata Cheat Sheet”

·       Please bring paper copies of the readings to class, you will need them!

Preparation:

·       Read “The BookBinders Book Club: Basic Customer Analysis”

·       We will devote most of this class to hands-on exercise with Stata, answering the questions posed at the end of the BookBinders case. We will use the dataset “BBB.dta” and “PCsUnlimited.dta” which is located in the “Datasets” section of the course website.

·       Bring laptop to class with Stata installed and the two datasets loaded onto the laptop

Wednesday, September 19 (day and evening sections)

 

Objectives:

·       To introduce customer profitability and its determinants

·       To consider different types of analytic methods

·       To practice your new-found Stata skills with data on profitability and other variables for a set of bank customers.

 

Readings:

·       HBS Case 9602104: "Pilgrim Bank (A)"

·       “Pilgrim Bank (A): Using STATA to Answer the Case Questions”

·       Marketing Analytics to the Rescue: The Next Big Thing? DM Review, 2003
http://www.dmreview.com/master.cfm?NavID=198&EdID=6346

 

Preparation:

·       Prepare “Pilgrim Bank (A): Customer Profitability” for class discussion.

·       Dataset: “PilgrimA.dta”. The dataset is in the “Datasets” section of the course website.

·       Detailed instructions about how to answer the preparation questions with STATA are contained in “Pilgrim Bank (A): Using STATA to Answer the Case Questions”

Preparation Questions:

1.     How much do profits vary across customers?

2.     How does Pilgrim Bank make money from their customers and how can this explain the variation in customer profitability?

3.     Are online customers more profitable than offline customers?

4.     What is the role of customer demographics in comparing online and offline profitability?

5.     What is your recommendation to the senior management team in terms of Pilgrim Bank’s online channel pricing strategy? Should the bank charge fees, offer rebates, or do nothing in regards to pricing for online channel use?

Wednesday, September 19 (evening section)

Monday, September 24 (day section)

 

Objectives:

·       To understand the premise behind RFM analysis

·       To introduce how to implement an RFM campaign

 

Readings:

·       “Recency, Frequency and Monetary (RFM) Analysis”

·       Quick Profits with RFM Analysis
http://www.dbmarketing.com/articles/Art149.htm

·       Optional but encouraged: I have created a Stata program (i.e. a ".do file") that will allow you to replicate the RFM analysis in the reading with STATA step-by-step. This will get you some practice before having to do the Tuscan RFM assignment. The document is “RFM_BBB_stata.do” which is in the “Datasets” section of the course website.
(Since this is a text file your browser might display this instead of downloading it when you click on it. If so, right-click in the file and choose to download it as a file.)
This do-file automatically loads the dataset “BBB.dta” which is in the “Datasets” section of the course website.

Wednesday, September 26 (day and evening sections)

 

Objectives:

·       To introduce a key model for predicting choices: logistic regression

·       To understand how to interpret logistic regression results

 

Readings:

·       “Applied Logistic Regression”

 

Plan ahead:

·       Obtain a license of the neural network software ModelMax from ASA Corp. This software is important for the upcoming “Intuit: Quickbooks Upgrade” assignment.  

·       Details on how to download the software and obtain a license can be found in “Instructions for Obtaining a Student Copy of ModelMAX Software” (see the materials for the “Intuit: Quickbooks Upgrade” class)

Wednesday, September 26 (evening section)

Monday, October 1 (day section)

 

Objectives:

·       To apply RFM analysis

·       To demonstrate the application of RFM for targeting direct mail offers

·       To explore variations of RFM

·       Evaluating RFM (and other) models

 

Readings:

·       “Tuscan Lifes