Download Slides - Zhangxi Lin`s - Texas Tech University

Zhangxi Lin
ISQS 3358
Texas Tech University
REALTIME BI - ONLINE TARGETED
ADVERTISING
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AGENDA
Internet-based Targeted Marketing
 Targeted Banner Advertising
 Online Recommender Systems
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INTERNET-BASED TARGETED MARKETING
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MARKETING TECHNOLOGY ADOPTION
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In December 2005, Forrester surveyed 371 marketing
technology decision-makers and influencers to
investigate trends in marketing technology adoption
and spending.
Respondents hail from six major industry groups, and
two-thirds work for firms whose annual revenues in
2005 exceeded $1 billion.
Marketing technology adoption is widespread.
 Marketers say they need a more comprehensive
application suite.
 Vendors aren’t delivering yet.

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MARKETING TECHNOLOGY SPENDING

Since 2003, budgets have crept steadily upward and,
on average, 2006 budgets are up 7% over 2005. But
spending varies significantly by company size and
industry. Specifically:
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The largest and smallest firms are scaling back slightly.
Technology followers are putting cash behind their intentions.
As a percentage of revenue, retailers spend the most on
marketing technology.
B2B firms are growing marketing technology spend
aggressively.
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MARKETING TECHNOLOGY SPENDING
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ONLINE MARKETING TECHNOLOGY
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ONLINE ADVERTISING MARKET STATUS
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In 2006, the advertising spending was $16.8 billion an
increase of 34% from that of 2005 (IAB 2007).
According to DoubleClick (2005)

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Limited online advertising publishing resources because of
limited online users’ capability to view growing number of web
pages (DoubleClick Research 2005)
Online targeted advertising is a seller market
Online targeted advertising is emerging as a new trend.


In March 2007, China’s largest advertising company by
advertising revenue, Focus Holding Ltd agreed to buy Chinese
leading online firm Allyes Information Technology Co. Ltd for $225
million.
In April 2007, Google Inc. announced a definitive agreement to
acquire DoubleClick for $3.1 billion.
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INTERNET MARKETING

Users know what they want

Users purchased certain items from certain websites

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Users did not purchase, but click through some links

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Mining the click-through streams of the customers, and figure out the
needs----behavioral targeting
Users do not know what they want---behavioral targeting

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We can apply real-time customized marketing solutions (see the process
map later)
Collecting information online (such as the blogs, discussions boards
in a community)
Segment/target/position strategy
We can potentially build a database profiling the online users
How to design (create) ads to make it appeal to end users
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IMPLICATIONS OF TARGETED MARKETING

For advertisers
 Help
to drive immediate responses (or increased
sales) to their advertisements
 Help to build branding for the advertisers

For publishers
 Maximize
the value of high-quality ad inventory
space (differential services for different site
sectors)
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EFFECTIVENESS OF ONLINE MARKETING
When executed properly, behavioral marketing is a highly
effective means of reaching and converting your target audience.
Network Behavioral Targeting
vs. Non-Targeted Advertising
Behavioral Re-Targeting vs.
Non-Targeting Advertising
Lift in Conversion Rate
Lift in Conversion rate
Advertiser A
90%
Advertiser A
167%
Advertiser B
323%
Advertiser B
2,232%
Advertiser C
105%
Advertiser C
3,130%
Source: Advertising.com, 2005
Source: Advertising.com, 2004
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PRODUCT PURCHASE
This travel advertiser targeted consumers who previously
visited its website in order to drive actual reservations.
Visitors who
had not booked
a reservation
received custom
ads highlighting
guaranteed rates,
seasonal discounts,
new hotel perks
and free gifts
with an online
booking.
Campaign
Results
Behavioral
Targeting
Impressions
99 million
Clicks
92,223
Bookings
52,936
Conversion
Rate
57.4%
A hotel booking
was generated for
every 2,000
impressions served.
1 out of every
2 people who
clicked on the ad
completed a booking.
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DO YOU KNOW THESE BUZZWORDS?

Web 2.0

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Targeted advertising
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Targeted advertising is a type of advertising whereby ads are placed so as to
reach consumers based on various traits such as demographics, purchase
history, or observed behavior. Two principal forms of targeted interactive
advertising are behavioral targeting and contextual advertising.
Massive customization

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Aims to facilitate communication, secure information sharing, interoperability, and
collaboration on the World Wide Web. Web 2.0 concepts have led to the development
and evolution of web-based communities, hosted services, and applications; such as
social-networking sites, video-sharing sites, wikis, blogs, and folksonomies.
Delivering diversified and customized services online to a large population of
consumers with different preferences
User driven services

A kind of Web 2.0 business model for delivering online services generated by
consumers
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TARGETED BANNER ADS
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BANNER AD MARKETING

Targeting the ads to a shadowy Internet population and
measuring the success of ads is challenging because failure of
a banner ad has many overlapping causes. Sources of failure
are:

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poor design, poor placement on Web page, poor choice of Web site for
placement, poor choice of Web pages within a Web site for placement,
poor dynamic qualities with respect to repeated page views, poor
customization tying banner ad to Web site where placement occurs, and
inadequate oversight by the hosting Web site.
Seasoned Web surfers grow weary of banner ads that disguise
themselves as interactive components of a Web page, for
example, offering multiple-choice answers to a question, only to
have an interactive click result in being transported to another
Web site.
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BINARY RESPONSE MODEL FOR CLICKTHROUGH

Model can be built using
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One model with indicator for banner ad/vendor selected
Multiple models, one for each vendor

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Web log data
Registration data
Vendor data (may not be required)
Overlapping data if page sequences are included, because
“did not click” entries will have common elements in all
models
Model scores the propensity to click on a vendor’s
banner ad
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BANNER ADVERTISING PRICING MODELS

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Cost per thousand impression (CPM)
Cost-per-Action (CPA)
Cost-per-Sale (CPS)
Cost-per-Lead (CPL), and
Hybrid-Cost-per-Action (HCPA).


The HCPA model uses two or more different pricing models with
compound pricing schemes.
Many common pricing models are based on cost per
click (CPC) while non targeted advertising model is
based on cost per thousand impression (CPM).
BROKERED BANNER ADS (BBA)
Ads
Publishing
Banners
Web Users
Ads
Publisher
Log
Data
Ads
Repository
OTA Service
Provider
Optimum
Decision Model
Ads Management
Realtime
Ads publishing
Ads
Contents
Advertisers
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BENEFITS OF BBA SYSTEMS
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Publishers have the opportunity to maintain their
business CPM pricing model.
Advertisers are in charge of CPC/CPA pricing model
With the help of OSP, advertisers are able to locate
effective publishers.
The OSP provides valuable information to advertisers
about publishers reliability.
OSP’s database records online visitors click-through flow
so as to construct an optimal decision model to select
appropriate advertisements for online visitors
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ONLINE RECOMMENDER SYSTEMS
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NETFLIX CREATES $1 MILLION NETFLIX PRIZE TO
PROMOTE PROGRESS IN RECOMMENDATION SYSTEMS
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LOS GATOS, Calif., October 2, 2006 – Netflix, Inc. (Nasdaq: NFLX), the
world's largest online movie rental service, today announced the creation of
the Netflix Prize, an award of one million dollars to the first person who can
achieve certain accuracy goals in recommending movies based on personal
preferences. The company also made available to contestants 100 million
anonymous movie ratings ranging from one to five stars, the largest such
data set ever released.
The threshold required to win the Netflix Prize is a 10 percent improvement
in accuracy over the current Netflix recommendation system. If no one wins
the grand prize this year, the company said it will award a $50,000 progress
prize to whoever makes the most significant advancement toward the goal
and will award a progress prize annually until someone wins the grand prize.
Complete details for registering and competing for the Netflix Prize are
available at www.netflixprize.com.
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NETFLIX™MOVIE RATING
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WHY RECOMMEND?
 As
a customer service
 Customers
looking for products in the book, movie, or
music categories are often looking for entertainment.
Most would view recommendations as a plus.
 Customers presented with appealing recommendations
do not have to resort to tedious searches.
 As
a cross-sell opportunity
 Customers
who intend to only buy one movie may find
the recommended choices too hard to resist.
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APPLICATIONS OF RECOMMENDER SYSTEMS
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For customers visiting a retail Web site, use
information from previous purchases to recommend
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Books, Music CDs, Movies
An “intelligent” music player: plays music specifically
selected by user, when music has finished and user
has not made a selection in over L seconds, the player
makes a selection for the user based on previous
selections the user has made.
A news service that provides a personalized custom
virtual newspaper to the subscriber based on past
news article preferences. (These are usually contentbased rather than collaborative.)
continued...
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APPLICATIONS OF RECOMMENDER SYSTEMS
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Personalize a user’s home page with “interesting” links,
with links based on a recommender system algorithm that
recommends links that should be interesting to the user.
Send a robot out looking for specific information, score
each Web page using a recommender algorithm, and then
return the K most interesting Web pages sorted by
descending score (search engine applications).
Index a library of information based on recommender
system scores.
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CASE - AMAZON
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