COURSE NUMBER: MBA263.1
COURSE TITLE: Marketing Analytics
UNITS OF CREDIT: 3 Units
INSTRUCTOR: Przemek Jeziorski
E-MAIL ADDRESS: przemekj@haas.berkeley.edu
CLASS WEB PAGE LOCATION: http://bspace.berkeley.edu
MEETING DAY(S)/TIME: Tuesday and Thursday, 9:30 –
11:00AM
PREREQUISITE(S): MBA 206
CLASS FORMAT: Mixture between lectures, cases,
projects, and exercises
REQUIRED READINGS: Cases, course reader
BASIS FOR FINAL GRADE: Mixture between exercises,
project, and class participation
ABSTRACT OF COURSE'S CONTENT AND OBJECTIVES:
Marketing Analytics addresses how to use customer
information and the technology to process it (i.e. databases, analytics,
computing systems) in order to learn about and market to individual customers.
Advances in the technology to process individual-level
customer information have had major effects for Marketing. Many firms now possess much more information about
consumers' choices and reactions to marketing campaigns than ever before.
However, few firms have the expertise to intelligently act on such information.
The goal of this course is to help students develop this expertise.
Specifically, the course will teach what it takes to collect, analyze, and act
on customer information. For example, we will use sophisticated targeting
models to increase marketing ROI in direct marketing campaigns. While we will
use many quantitative methods in the course, the goal is *not* to produce
experts in statistics. Instead, the goal is to train students to be able to
comfortably interact with and manage a marketing analytics team.
Marketing is going through an evolution from having
been primarily an art to becoming a science. This course teaches students a
crucial part of the "science" approach to marketing. We will use a
combination of lectures, cases, projects, and exercises to learn the material.
This course takes a very hands-on approach and equips students with tools which
can be used immediately on the job.
Frequently Asked Questions:
Q: "How does “Marketing Analytics” differ from
"High-Tech Marketing"?"
A: The courses have no overlap. 'High-Tech Marketing'
is about marketing high-technology products. "Marketing Analytics" is
about using customer information and "technology" (i.e. databases,
analytics, computing systems) to market to consumers.
Q: "How does "Marketing Analytics"
differ from "Marketing Research"?"
A: "Marketing Research" is a broad course
that introduces students to a variety of research methods, such as
psychological measurement, research design, survey methods, experimentation,
etc. In doing so, Marketing Research focuses strongly on collecting data about
consumers to understand their overall preferences. In contrast, "Marketing
Analytics" starts with the idea that you have a (potentially huge)
database containing each individual customer and teaches you how to market to
these customers using sophisticated techniques. The two courses complement each
other very well. However, you don't need one to take the other.
Q: "Do I have to know a lot of statistics to
succeed?"
A: Absolutely not. While we will use statistics to
analyze customer information and many of the assignments require you to use
statistical techniques, all you need will be
introduced in class with plenty of opportunity to get familiar with it.
BIOGRAPHICAL
SKETCH:
Professor Jeziorski is an
empirical economist specializing in industrial organization, regulation and
quantitative marketing. His work spans across variety of topics including:
mergers and acquisitions, on-line advertising, mobile banking systems and
cancer prevention. Recently, Professor Jeziorski has
been working with Gates Foundation to establish the impact of transaction cost
and vendor lock-in on diffusion of mobile peer-to-peer payment systems in
Africa.
In another project, Jeziorski
works with Microsoft Research to describe an interaction between conventional
branding and the efficacy of on-line sponsored search advertising. In
particular, he describes that strong conventional brands do not experience
so-called position effect, that is, ads of strong brands do not benefit
from top advertising slots as much as ads of weak brands. As a consequence,
strongly branded advertisers should have similar willingness to pay for top ad
slots and for inferior ad slots, whereas weak brands should strongly prefer top
slots.
Going beyond business applications of marketing
analytics, Professor Jeziorski has been working with
the cancer registry in Singapore to establish a causal impact of early breast
cancer screening on cancer mortality rates.