ADEC754001 Marketing Analytics for Economists
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ADEC754001 Marketing Analytics for Economists
Boston College Mission Statement
Strengthened by more than a century and a half of dedication to academic excellence, Boston College commits itself to the highest standards of teaching and research in undergraduate, graduate and professional programs and to the pursuit of a just society through its own accomplishments, the work of its faculty and staff, and the achievements of its graduates. It seeks both to advance its place among the nation's finest universities and to bring to the company of its distinguished peers and to contemporary society the richness of the Catholic intellectual ideal of a mutually illuminating relationship between religious faith and free intellectual inquiry.
Boston College draws inspiration for its academic societal mission from its distinctive religious tradition. As a Catholic and Jesuit university, it is rooted in a world view that encounters God in all creation and through all human activity, especially in the search for truth in every discipline, in the desire to learn, and in the call to live justly together. In this spirit, the University regards the contribution of different religious traditions and value systems as essential to the fullness of its intellectual life and to the continuous development of its distinctive intellectual heritage.
Course Description
While companies are now wrestling with information that comes in varieties and volumes never encountered before and enthusiasm for big data is increasing, data scientists’ greatest opportunity to add value is not in creating reports or presentations for senior executives but in innovating with customer-facing products and processes.
Specifically designed for Economists, this course will enable students to use analytics to improve marketing performance and lead marketing efforts. Students will be able to answer key questions such as:
1. How I design the appropriate metrics and analytics to monitor/improve marketing efforts?
2. How can I measure my various marketing programs’ impact on revenue and profit?
3. How can I communicate insights, not just facts?
4. Which tool, of the many available, is best for which problem?
5. How can I use AI technology to add accurate, actionable and timely intelligence to unstructured data to produce insights and solve business problems?
6. How can I measure customer experience (CX), and optimize customer journey?
In studying a range of firms across several contexts and industries, the course, featured by a highly experiential and interactive approach, builds on recent advances to make more data-informed business decisions and drive strategic advantage. We use a number of cases and real life examples/simulations to discuss each of the points presented in the course. Based on the number of enrolled students, business partners will engage them in one or more real life projects. While the course format is online asynchronous, three synchronous meetings will be planned during week 2,4,6. Participation is optional but highly recommended.
PRE-REQUISITES: ADEC7310 Data Analysis, ADEC 7320 Econometrics (can be taken concurrently)
The course requires an undergraduate knowledge of statistics, (descriptive statistics, regression, sampling distributions, hypothesis testing, interval estimation etc.) linear algebra and probability. Familiarity with Python or any programming language is not required.
Cases & Readings (Required)
Readings: Readings are provided in Canvas via link or .pdf file the majority of your readings are found in the course pack.
Instructor Lecture Notes: For convenience, there are instructor lecture notes (PowerPoint slides) provided for your review.
Case Analysis: I have selected cases for each topic, and you must analyze them according to the class schedule. The selection of cases are available in the following course pack link: https://hbsp.harvard.edu/import/882266
Students are also expected to scan newspapers and business periodicals to keep up with current Marketing analytics events of relevance to this course. (The New York Times, The Wall Street Journal, Financial Times, Fortune, Business Week, The Economist, Advertising Age, etc.)
N.B. As this syllabus is subject to change at the instructor’s discretion, it is advisable to buy the entire course pack ONLY after the first couple of weeks from the course start.
Textbooks & Readings (Recommended)
1. Competing on Analytics: Updated, with a New Introduction: The New Science of Winning by Thomas H. Davenport; Jeanne G. Harris, Harvard Business Press, Product #: 10157-HBK-ENG Pub Date: Sep 19, 2017
2. Keeping Up with the Quants: Your Guide to Understanding and Using Analytics by Thomas H. Davenport, Jinho Kim, Harvard Business Press, Product #: 11177-HBK-ENG Pub Date: Jun 10, 2013
3. The Analytical Marketer: How to Transform Your Marketing Organization, Adele Sweetwood and Thomas H. Davenport, Harvard Business Press, Product #: 14251-HBK-ENG Pub Date: Oct 4, 2016
4. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, Eric Siegel, Wiley, 2016
5. Good Charts Workbook: Tips, Tools, and Exercises for Making Better Data Visualizations, Scott Berinato, HBS Press, Product #: 10209-PDF-ENG Pub Date: Jan 21, 2019
6. Regression Analysis readings/exercises course pack (optional): I have made a selection of readings and exercises
which you can purchase by accessing he following dedicated link:https://hbsp.harvard.edu/import/882267 Please findherethe instructions to access the coursepack material.
"All required and recommended materials for this course are available at the BC Bookstore, and online at www.bcbookstore.com."
Canvas
Canvas is the Learning Management System (LMS) at Boston College, designed to help faculty and students share ideas, collaborate on assignments, discuss course readings and materials, submit assignments, and much more - all
online. As a Boston College student, you shouldfamiliarize yourself with this important tool. For more information and training resources for using Canvas, clickhere. In the case of any technical difficulties or concerns, please contact [email protected]or 617-552-HELP (4357) for immediate assistance.
NOTE: Canvas requiresparticular computer specificationsand Wi-Fi access. It is important that you plan accordingly, particularly for courses that have online components.
Course Outcomes
1. Apply analytics in decision making through interactive lectures, online case discussions.
2. Frame problems analytically through interactive lectures, and real-life business cases.
3. Develop the ability to analyze, model and interpret data to be used to make better marketing decisions through interactive lectures, online case discussions and real-life business cases.
4. Acquire a methodical and logical approach through online case discussions and real-life business cases.
5. Practice business and empathy skills for customers through interactive lectures, online case discussions and real- life business cases.
Grading
Final grades for the course will be based upon the following weights:
Mid-term exam 25%
Individual final exam 30%
Collaborative Annotations 10%
Discussions 15%
Assignments 20%
The graduate grading system for Woods College is as follows:
Quality of Performance |
Letter Grade |
Range % |
GPA |
Excellent – work is of exceptional quality |
A |
93 - 100 |
4.0 |
- |
90 – 92.9 |
3.67 |
|
Good – work is above average |
B+ |
87 – 89.9 |
3.33 |
Satisfactory |
B |
83 – 86.9 |
3.00 |
Below Average – passing but does not count toward degree |
- |
80 – 82.9 |
2.67 |
Poor – passing but not for degree credit |
C |
70 – 79.9 |
2.00 |
Failure – not passing |
F |
<70 |
0.00 |
All students can access final grades through Agora after the grading deadline each semester. Students who complete course evaluations can access grades earlier, as they are posted.
Partnership Project weekly grading (based on the project timeline):
Max points
Week 3 Framing the Problem 20
Week 4 Solving the Problem 25
Week 5 Draft 20
Week 6 Communicating /Acting 25
Week 7 Final presentation 10
TOTAL POINTS POSSIBLE: 100
Criteria for Evaluation of Written Assignments
An “excellent” paper should prove:
a thorough analysis of the key issues with the ability to apply and integrate the course’s concepts;
appropriate structure with a logic flow of ideas; and
relevant presentation and style with an excellent usage of the English language.
Case Analyses
The case analyses will take several formats. Initially, you are expected to individually review and analyze the case making two posts to the discussion forum PRIOR to the Wednesday synchronous session. In the synchronous session we will discuss the case and then by the end of the week you are expected to post two more times to the discussion forum. The next week, you will work in a group to accomplish a case analysis assignment. The following week you will complete a “group process” evaluation of the group as a whole in completing the assigned work. Please read Appendix A for guidelines and details for preparing case analyses.
Case studies and readings for which a link is not provided will be found either in the Learning content in Canvas or purchased online by accessing the following course pack link.
https://hbsp.harvard.edu/import/882266
Please read Appendix B for guidelines and details of discussing the cases in online forums.
Synchronous Sessions
While the course format is online asynchronous, three synchronous meetings are planned during week 2,4,6 on Saturdays from 11 am - 1 pm EST. Participation is optional but highly recommended based on students' feedback from past courses.
For each synchronous session, case studies will be discussed/de-briefed as a class and a selection of topics from the week’s materials (i.e. readings, videos, instructor’s notes) will be discussed interactively.
Annotations
There are several key articles that have been assigned for annotation using the Perusall tool.
Students will create aPerusallaccount and enter your instructor course code AFFINITO-VMH3F upon registration to enroll in the course.
Read the assigned reading and take part to the discussion by posting your annotations inPerusall.
Key Takeaways
Each week in the Wrap Up section you will summarize three takeaways from the readings, discussions, case studies, videos, and assignments.
MIDTERM AND FINAL EXAM
MIDTERM EXAM - Marketing Analytics Challenge (MAC): Individual presentations
Analyze and present your points and recommendations about a selected case.
Create a multimedia PPT presentation (should take me 5-8 minutes to watch).
Submit your multimedia PPT presentation in a dedicated assignment page in Canvas.
FINAL EXAM: the final exam will be either an assignment to upload or a quiz to take in Canvas. Further details will be provided after midterm.
Presentations
There are several methods of recording your videos or presentations. One tool is Zoom, either as a group meeting that is recorded as a presentation or an individual meeting that is recording while sharing your screen to provide the slides to others. For the midterm you will submit a video of your presentation. In addition, Panopto and Screencast- O-Matic also work very well. Presentations should be rehearsed and provide clear visual representations of your analysis.
Deadlines and Late Work
Any work submitted after the due date outlined within the Course Schedule will be assessed a 10 pt. grade reduction penalty if no more than 6 days late. Work submitted later than 6 days after due date will be assessed a 20 pt. grade reduction penalty if submitted before the close of the semester.
Course Work
It is expected that you will spend 6-8 hours per week on out-of-class assignments and exercises. These are listed below. Please note that some weeks will require more time and some weeks less time, but the average is approximately 7 hours per week over the semester.
Response time
I will respond to your questions and emails within 24 hours (except if I am on vacation at any point during this class and if so, I will let you know). I grade once the week has ended and post grades by the following week.
2022-01-21