MKT 543: MARKET DEMAND AND SALES FORECASTING COURSE SYLLABUS SPRING 2014

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1 MKT 543: MARKET DEMAND AND SALES FORECASTING COURSE SYLLABUS SPRING 2014 Instructor: Dr. S. Siddarth Hoffman Hall (HOH) 613 Phone: (213) Fax: (213) Schedule: MW, 2-3:20 pm, HOH 415 Office Hours: Required Text: Monday and Wednesday: 12:00-1:00 pm, or by appointment None Reasons to Take This Course This course is designed to introduce you to a number of quantitative techniques and analytical tools that provide insight into the nature of consumer demand and its response to changes in the marketing mix. The use of these techniques can improve a manager s forecasting ability, provide a better understanding of market behavior and, ultimately, form the basis for making more effective and efficient marketing decisions. Course Goals The specific objectives of the course are: 1. To familiarize you with several advanced, quantitatively oriented marketing tools that enhance demand forecasting ability and marketing decision-making. 2. Provide extensive experience in using these tools through computer exercises (i.e., dirtying your hands with the data). 3. Develop an ability to critically assess the strengths and weaknesses of these modeling approaches when applied to specific marketing problems (via case and discussion). 1

2 CLASS MATERIALS 1. Readings All required readings are included in the course packet available for purchase from the Campus Bookstore. 2. Lecture Notes Copies of the PowerPoint slides used in class will be made available on the course Blackboard page. 3. Computer Exercises The course requires statistical of a variety of datasets and hands on use of the computer in every topic area. These datasets will also be posted on Blackboard. While most of the will require you to use spreadsheet based statistical tools, some sessions may require you to use specialized statistical software such as SAS or JMP. ASSESSMENT Your final grade in the course will be based on the following criteria. A. Class participation 10% B. Two group assignments (9% each) 18% C. Two individual assignments (7% (#1) and 10% (#2)) 17% D. Group project 18% E. Final exam 37% Please note that no late assignments will be accepted. All written work is due at the beginning of class on the due date. Also note that final exams are scheduled by the Registrar, not the instructor, and cannot be changed under any circumstances. A. CLASS PARTICIPATION (10%) Every session of the course will involve interaction in the form of class discussion. I expect each class member to be prepared at all times to contribute to any class session. To reinforce this expectation, I will randomly select (i.e., cold call) students at the beginning of the session to open the class and throughout the ensuing discussion whether or not the student s hand is raised. However, self-motivated participation is preferred and encouraged: don t wait to be called upon. A necessary, but not sufficient, condition for class participation is that you come to class. In order to obtain a grade for class participation you must attend the class sessions (please let me know in advance if you cannot attend a session). 1 1 Missing more than 10% of the sessions will seriously affect your participation grade. 2

3 B. GROUP ASSIGNMENTS (18%) I ask that you form groups of four or five people to work on the group assignments and the forecasting project. Please submit the names of the teams by the second week of classes. The group assignments will either be related to a case that will be discussed in the class or will be an independent exercise. All exercises are designed to provide you with a better understanding of the research techniques discussed in class and to dirty your hands with the data. C. INDIVIDUAL ASSIGNMENTS (17%) These assignments will be similar in scope to the group assignments discussed above but must be completed on your own. Collaboration of any kind is unacceptable and will be penalized. D. GROUP PROJECT (18%) Each team will take on a real-world marketing situation that requires you to perform some forecasting/ market response. The purpose of this project is to apply one or more of the concepts and methods of the course to the marketing decisions problems faced by a company that you are familiar with. The output of the research will include an in-class presentation and a summary report. Each group will submit a proposal for approval in the week before Spring Break. Project presentations are scheduled for the last week of the term and completed project reports are due on the last day of class. Further guidelines for this project will be provided in class. E. FINAL EXAM (37%) The final exam will test students on their understanding of the concepts and theory covered in the class as well as their mastery of data skills. POLICY ON TECHNOLOGY USE Please note that communication devices such as cell phones, blackberries, iphones, etc. capable of sending and or receiving electronic communication and all entertainment devices such as ipods, or other Mp3 players must be turned off and kept off throughout the class session. Receiving or sending communication or entertainment during class disrupts the learning environment and is rude to those around you. IMPORTANT INFORMATION FOR STUDENTS WITH DISABILITIES Any student requesting academic accommodations based on a disability is required to register with Disability Services and Programs (DSP) each semester. A letter of verification for approved accommodations can be obtained from DSP. Please be sure that the letter is delivered to me as early in the semester as possible. DSP is located in STU 301 and is open 8:30 am 5:00 pm, Monday through Friday. The phone number for DSP is (213)

4 CLASS SCHEDULE Session Topic Reading Case Discussion 1/13 Course introduction 1/15 Overview of forecasting tools and techniques 1/22 Sales forecasting for new products 1. Note on Marketing Mix Models: Evaluating Bang for the Buck 2. Lehmann, Gupta & Steckel, chapter 13, Regression Analysis Davenport & Harris, The Nature of Analytical Competition 1. Ofek, Forecasting the Adoption of a New Product In Class Exercise / Example Regression Analysis of MBA Rankings with Excel Assignment Due 1/27 Sales forecasting for new products 1/29 Sales forecasting for established products 2/3 Sales forecasting approaches for new products 2/5 Measuring consumer preferences: Introduction to conjoint 1. Lilien, Kotler, and Moorthy, Repeat Purchase Models for New Products 1. Dolan, Conjoint Analysis 2. Wilcox, A Practical Guide to Conjoint Analysis E-books demand forecasting Estimation of the Bass diffusion model for different datasets Form groups and turn in group member names Individual Assignment 1 E-book Bass Model Forecasting 2/10 Conjoint Analysis Estimation 2/12 Further applications of conjoint In-class conjoint exercise 4

5 Session Topic Reading Case Discussion 2/19 Analysis of aggregate scanner data 2/24 Analysis of aggregate scanner data (contd.) 2/26 Promotion profitability 3/3 Promotion profitability (contd.) 3/5 Analysis of disaggregate data 3/10 Analysis of disaggregate data 3/12 Decision Calculus: Salesforce Response 3/24 Decision Calculus: Salesforce Response 3/26 GUEST LECTURE 1. Material from Humby, Hunt and Phillips, Scoring Points, How Tesco is Winning Customer Loyalty 1. Lodish, Building Marketing Models that Make Money In Class Exercise / Example Elasticity in the laundry detergent market Application of exception and regression approaches to evaluation Assignment Due Group Assignment 1 Conjoint Analysis Group project description due Group Assignment 2 Price Response and Promotion Profitability 5

6 Session Topic Reading Case Discussion 3/31 Sales Force Allocation Case Syntex Labs In Class Exercise / Example Assignment Due 4/2 Customer Analysis 4/7 Customer Case 1 4/9 Customer Case 2 4/14 Advertising budget decisions 1. Ofek, Customer Profitabilty and CLV 2. Davenport & Harris Competing on Analytics with External Processes Freeport Studio Harrah s Entertainment Inc. 4/16 Customer Case 3 Project Review 4/21 Advertising budgeting case 4/23 Course Review 4/28 Project Presentations 4/30 Project Presentations Hilton HHonors Tang Individual Assignment 2 Hilton HHonors 5/12 FINAL EXAM 2 4:30 pm As specified in the USC Schedule of Classes See 6