Information Science of Marketing

Davi Geiger

Graduate Division

Computer Science

This web site is under construction. Please expect it to be updated/improved.

Classes are schedule for Thursdays 7:10 pm to 9:00 pm, *719 Broadway Room 1221*

Office Hours and Location: TBD, at 719 Broadway Room 1225.

Book: "Bayesian Statistics and Marketing" by P.E. Rossi, G.M.Allenby and R. McCulloch. Wiley Series in Probability and Statistics. www.wiley.com/go/bsm

Syllabus by topics. Course dynamic: midterm project and final project. We intend to create a social network among class members and use it as part of the dynamic of the course.

1. First Class: The Tao of Marketing

Introduction.ppt (power point)
Marketing Origin: how and why started
What is the course about: why modelling advertising, why is it necessary, existing market methodologies. Impacts of technological changes in how people relate to media and consume products.

2. Market Evolution: from targeting mode to pinball model

consumer-centric.ppt (power point)
wassup2008.avi (video)
wassup.avi (video)
Bayesian-Inference.ppt (power point)
Major recent market changes (geographic border x globalization, behavioral boundaries between generations decreased, cultural mixture, industries transformed into service providers, consumer information overload, technology everywhere and all the time, too many choices / tyranny of the new, ethical values, consumer power/smart buying). Strategic change: Consumers.
Communication increasingly complex scenario: Internet and digital world (channel-centric to consumer-centric; Targeting model, Bowling Model and Pinball model)
Homework1.doc (word)

3.Branding and Digital Media

Campaign projection showing how different advertising could be. Brand and branding concepts. Why is important to enhance the brand? How not to become a commodity? (Market has too many similar companies, which similar employees, similar education, with similar ideas, which produce similar things, for similar prices and similar quality. Brand is the differential). Present different formats and vehicles of advertising in non-traditional media (web and mobile)

4. Societies without borders: the new media paradigm.

DigitalMedia.ppt (power point)
What is Social Media (virtual reflection of social interactions that people have in the real world without the constraints of time and space; integrated technology, social interaction and construction of words, images and universes)
Social Media Categories:
a. Social Network: Facebook, MySpace, YouTube, Flickr, Twitter, LinKedIn, etc. Formats: Community, Mini-blogging, Branded-Channel, Online Photos, etc.
b. Collaborative Content: TypePad, Podcast.com, Bloglines, Digg, Wikipedia, etc. Formats: Blog e “Casts”, Favorite Management, Wikipedia, internal wikis, etc.
c. Virtual Worlds: SecondLife, SIMS, Warcraft, etc.
d. Graphical interface: widgets, RIA application

5. Inside the insights of the State Diagram.

StateDiagram.ppt (power point)
Marketing management decisions
Regarding the bottom line: purchases/allocation of money resources to advertise items
Describing the state diagram (state description on how people react/behave to advertising)
Artificial Intelligence model of individuals.

6. Information convergence: rethinking media campaigns.

Ten (10) individual campaign presentation, including the Obama election campaign.
Comparative analysis identifying the convergences (midterm project: students will investigate two other adds and describe them within our discussions)

7. Modelling is in. Guessing is out.

Why should we model these things? (the power of modeling)
Explain the modeling process (how to do it? How does it work?)
How can we model these things?
Information Propagation and Information Science.

8.Science and the art of Marketing.

Attempt to model the state diagram and model advertising and branding using "physics" style models and Information theory. Introduction to Bayesian Networks and its relations to Artificial Intelligence.

9. Introduction to Information theory and some algorithms

Concepts of coding (information stored) and decoding (information retrieved)
Spreading information costs and Bayesian Networks.

10. Putting a price on integrated media.

How Google prices their advertising (automatic auction models)

11. Facebook: the new face in mass media.

How Facebook introducing into the network and how we can model it.
How advertising will impact Facebook (develop models and ask students to elaborate as well – final project)