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Zhangxi Lin ISQS 3358 Texas Tech University. Realtime BI - Online Targeted Advertising . Internet-based Targeted Marketing Targeted Banner Advertising Online Recommender Systems. Agenda. Internet-based Targeted Marketing.
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Zhangxi Lin ISQS 3358 Texas Tech University Realtime BI - Online Targeted Advertising
Internet-based Targeted Marketing Targeted Banner Advertising Online Recommender Systems Agenda
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. Marketing Technology Adoption
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: • 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. Marketing Technology Spending
In 2006, the advertising spending was $16.8 billion an increase of 34% from that of 2005 (IAB 2007). • According to DoubleClick (2005) • 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. Online Advertising Market Status
Users know what they want • Users purchased certain items from certain websites • We can apply real-time customized marketing solutions (see the process map later) • Users did not purchase, but click through some links • Mining the click-through streams of the customers, and figure out the needs----behavioral targeting • Users do not know what they want---behavioral targeting • 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 Internet 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) Implications of Targeted Marketing
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 Source: Advertising.com, 2004 Source: Advertising.com, 2005
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. 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.
Web 2.0 • 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. • Targeted advertising • 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 • 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 Do you know these buzZwords?
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: • 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. Banner ad marketing
Model can be built using • Web log data • Registration data • Vendor data (may not be required) • One model with indicator for banner ad/vendor selected • Multiple models, one for each vendor • 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 Binary Response Model for Click-Through
Banner Advertising Pricing models • 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 Contents Optimum Decision Model Realtime Ads publishing Ads Repository Ads Management OTA Service Provider Advertisers
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 Benefits of BBA Systems
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. NETFLIX CREATES $1 MILLION NETFLIX PRIZE TOPROMOTE PROGRESS IN RECOMMENDATION SYSTEMS
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. Why Recommend?
For customers visiting a retail Web site, use information from previous purchases to recommend • 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 content-based rather than collaborative.) Applications of Recommender Systems continued...
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. Applications of Recommender Systems
