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    Academically-Practical and Practically-AcademicLearnings in Interactive Media

    Wharton Interactive Media Initiative

    www.whartoninteractive.com

    Steve EnnenManaging Director,

    Wharton Interactive Media Initiative &Wharton Lab for Innovation in Publishing,

    Lecturer in Marketing

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    WI MI O VERVIEW

    Brings a passionate data-driven perspective to media businesses (content distribution and

    information acquisition) in a way that no other business school in the world can match.

    Distinguishes itself with a tight focus on the interaction between content provider and user,capitalizing on the wealth of individual-level data that is exploding at the crossroads of

    commerce, technology, and entertainment.

    Is dedicated to bringing world-class research rigorto better understand these complex

    interactions in order to drive new business strategies and tactics that will reshape the

    media landscape.

    W H A R T O N I N T E R A C T I V E M E D I A I N I T I A T I V E

    WIMI is a global research center

    working with leading companies and researchers

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    WI MI G LO BAL I NF RAST RUCTURE

    Global network of research partners

    W H A R T O N I N T E R A C T I V E M E D I A I N I T I A T I V E

    Wharton Lab for

    Publishing Innovation WIMIResearch,Student Placement

    Interns,Partners

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    ACADEMICALLY PRACTICAL INTERACTIVE MEDIA 2009-10

    Social Networking: Jan 2009Impact and Emergence of UGC:

    Dec 2009

    Cross-Platform Data: Dec 2010Mobile Marketing: 2011

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    C O MI N G I N D E C E M E B E R 2 0 1 0

    Modeling Consumer Behavior in Social Media: Analyzing the Role ofGeographical Location and Multichannel Usage in Microblogging Platforms

    AnindyaGhose and Sang Pil Han

    ***

    Seller Strategy in B2B Multichannels: Auctions, Buy-Now Pricing, and PriceDiscovery

    ErnanHaruvy, Sandy D. Jap, and RobertZeithammer

    ***

    Multichannel Customer Behavior in Customer Support ServicesKinshukJerath, AnujKumar, and SergueiNetessine

    ***

    How TV Advertising Affects Online SearchMingyuJoo, Kenneth C. Wilbur, and Yi Zhu

    ***

    Investigating the Impact of Multiple Communication and Marketing Mix

    Elements in a Multichannel EnvironmentAshish Kumar, Ram Bezawada, andMinakshiTrivedi***

    Modeling Multichannel Media Consumption: Multiplexing, Consumption &Evolution

    Chen Lin and Douglas Bowman

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    A Few Company Participants

    Interface seems pretty practical

    ACADEMICALLY PRACTICAL INTERACTIVE MEDIA 2009-10

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    DOES TH E GREAT DIVIDE R EALLY EXIST?

    Academics Practice

    Academically-Practical Practically-Academic

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    Improved Predictionso Social network data helps to improve predictions of behavior above and beyond just

    behavior

    Popularity and Activity correlated across relationshipso More popular social networkers are also more active

    Online popularity is a more important correlate of online behavior than offlineo Online predicts online better than offline predicts online

    >

    + >

    WHARTON , SOCIAL NET WORKING DATA , 2009:

    Ansari, Koenigsberg& Stahl Modeling Connectivity in Online Networks

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    Give Lower Price to A to Exploit BMaximize Total Dollars not Myopic Dollars

    -1 -0.5 0 0.5 1 1.5 2 2.50

    20

    40

    60

    80

    100

    120

    ax imum

    ocial Interaction Effect in the

    roup

    LowestPrice

    Charged

    to

    a

    em

    berofthe

    roup

    -1 -0.5 0 0.5 1 1.5 2 2.550

    100

    150

    200

    250

    300

    350

    400

    450

    500

    ax imum

    ocial Interaction Effect in the

    roup

    reatestPrice

    Charged

    to

    a

    em

    bero

    fthe

    roup

    A BSocial Influence

    Social Multiplier

    Hartmann

    Econometric Modeling ofSocial Interactions (Golf Data)

    WHARTON , SOCIAL NET WORKI NG DATA , 2009

    Community Building

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    Free Gets You

    Up The Charts

    But, Free is Free!

    Popularity begets

    popularity; but

    how do you get it?

    PRICING DIGITAL CONTENT(IYENGAR,ABHISHEK, BRADLOW 2007)

    Freemium

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    SOCIAL NETWORKS AND MASS MARKETING

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    vs

    Network Intervention In each city, the physician withthe highest in-degree is targeted and is persuaded to

    increase his/her prescription by 10 units

    Detailing Intervention Each physician is given an

    additional detail.

    Managerial Calculus

    Higher Effectiveness

    Influencers work locally!

    WHARTON , SOCIAL NET WORKI NG DATA , 2009

    Iyengar, Van den Bulte, Valente

    Opinion Leadership and Social Contagion in New Product Diffusion

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    C U T T H R O U G H T H E C L U TT ER

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    Customer

    equity(NPV A)

    Social equity of

    community

    No community $436.97

    A has a

    community

    $515.32 $78.5 (18%)

    A technique for complex system modeling, which simulates global

    phenomena based on local interactions between units.

    A technique for complex system modeling, which simulates global

    phenomena based on local interactions between units.

    Each unit represents an individual member in the social networkEach unit represents an individual member in the social network

    Each linkrepresents a communication tie between membersEach linkrepresents a communication tie between members

    At each point in time members can decidewhether to adopt a new product or to

    remain non-adopters

    At each point in time members can decidewhether to adopt a new product or to

    remain non-adopters

    WHARTON , SOCIAL NET WORKI NG DATA , 2009

    Libai, Muller, and Peres

    Untangling CustomerSocial Equity via Agent Based Models

    Monetizing Your

    Community

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    W HY IS IT IMPORTANT TO LEARN FROM UGC?

    Public

    Free

    Spontaneous

    Passionate Evolving and live

    Temporally disaggregate

    Consumers self-select

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    Bayus

    Crowdsourcing New Product Ideas

    The goal is for you, the customer, to tell Dell what new products or services

    youd like to see Delldevelop.

    Daily: Feb 2007 Feb (June) 2009

    7,100+ ideas

    4,300+ ideators

    170 ideas implemented (outcome)

    Variables Model

    Prior Experience

    # prior good ideas

    # prior reviewed ideas

    # prior ideas

    # prior comments

    NS

    NS

    NS

    NS

    New product ideas and their

    ideators are not easily predictable

    W H ARTON R ES EA RC H O NU GC, 2009

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    Text mine consumer postings

    Use network analysis framework

    and other co-occurrence

    methods of analysis to reveal theunderlying market structure

    compact sport old

    Audi A6 67 345 56

    HondaCivic

    1384 539 245

    ToyotaCorolla

    451 128 211

    Is classic Marketing

    Research dead?

    W HA RTO N R ES EA RC H ON UGC , 2009

    Feldman, Goldenberg, Netzer

    Mine YourOwn Business: Market Structure Surveillance

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    Stock Price (adjusted)

    UGC Chatter

    ChatterConsumer

    Opinion

    Negative

    Chatter

    Negative

    Expressions

    Short

    Term

    Cum Short

    Term

    Cum Short

    Term

    Cum Short

    Term

    Cum

    Stock Returns ** 3.8 4.8 -2.1 -3.6 -2.9 -3.9 -3.7 -4.7

    You can take UGC to the Bank

    W HARTON RESEARCH ON U GC, 2009

    Tirunillai and Tellis

    Does Chatter Really Matter? Dynamics of User-Generated Content and Stock

    Performance

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    Soft metrics meaningless or close to meaningless

    Faux metrics fabricated by technology

    Data deluge

    Confusion

    CHALLENG ES T O MEASUREMENT

    Impact is clear, but measurement can be challenged by

    noise

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    Engagement

    (noun, verb, not a single metric)

    Seriously though, I am surprised that your analysis pegs me as one

    of the most engaged users to your site. I subscribe to your RSS feed

    via Yahoo, and eventually get around to reading each new posting,

    but my access is very occasional. Your email to me was the first that I