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IN THE SEPTEMBER ISSUE...
MICROSOFT, FACEBOOK INK AD DEAL
Red Herring, C. Medford, 08/23/2006
Microsoft and Facebook reached an agreement Wednesday that would make the software giant’s recently launched advertising portal the exclusive provider of banner ads and sponsored links to the social networking web site.
The deal is a significant victory for Microsoft, which has been a laggard in the online ad portal business. Microsoft, which until last year sold ads on MSN through Yahoo’s ad portal, introduced its online ad platform, adCenter, earlier this year (see Redmond Grabs Ad Biz).
Beating Google and Yahoo to Facebook’s 9 million registered users is a meaningful milestone for Microsoft.
Facebook cited Microsoft’s tardiness as a strength because its adCenter program incorporates the most recent advances in ad portal technology. Microsoft does not have to retrofit its program to incorporate new technology.
“We chose Microsoft because it, like Facebook, is a technology company at its core and is committed to taking a fresh approach to targeting advertising to social media,” said Owen Van Natta, chief operating officer of Facebook. “We’re committed to providing a great user and advertiser experience together.”
Shares of Microsoft rose $0.02 to $25.64 in recent trading.
Google, Microsoft Shootout
The deal was put together quickly as the two companies said they began talks about the relationship only last week. Both companies expect the new advertising experiences to appear in the early fall.
The deal comes less than three weeks after the leading social networking site, News Corp.’s MySpace, came to terms with Google for the search giant to provide text-based advertising and keyword-targeted ads to a number of News Corp. properties through its AdSense program.
The agreement is worth at least $900 million (see Google, MySpace Ink $900M Deal).
MySpace generated an estimated 30.2 billion page views in the three months ending in June, according to comScore, making it the most highly trafficked portal in total page views, not including emails.
Palo Alto, California-based Facebook, which primarily targets college students, ranks as the seventh-most heavily trafficked site in the United States, according to comScore.
The Microsoft/Facebook deal will include text-based and graphical ads targeted initially to content, and over time to aggregate user behavior.
“We believe that the combination of Microsoft and Facebook strengths will be incredibly attractive to advertisers as they forge more meaningful connections with one of the largest, most engaged audiences on the Internet,” said Steve Berkowitz, senior vice president of the online services group at Microsoft.
THE INTERACTIVE INDUSTRY COMMITS TO THE DEVELOPMENT OF CLICK MEASUREMENT GUIDELINES
Interactive Advertising Bureau Press Release, August 2006
The Interactive Advertising Bureau (IAB) today announced that they are forming an industry-wide Click Measurement Working Group to create a set of Click Measurement Guidelines. These Guidelines, a joint effort with the Media Rating Council (MRC), will provide the detailed definition of a "click" and the standard against which clicks are measured and counted including the identification of invalid clicks and/or fraudulent clicks.
Member companies who have confirmed their participation in this Working Group thus far include: Ask.com, Google, LookSmart, Microsoft Corp., Yahoo!, and others.
The IAB is steadfast in its commitment to the principles of transparency and industry oversight for the measurement of any aspect of Interactive media. The Click Measurement Guidelines will also outline an industry driven auditing and certification recommendation for any organization involved in performance based marketing like search engines, ad networks, third party ad servers or any company that counts clicks as a part of the media currency. These guidelines are part of the broader Global Ad Impression Guidelines that were launched in 2004 and follow the recent release of the Broadband Measurement Guidelines.
"I applaud the IAB for continuing to take a leadership role in the creation of Measurement Guidelines across all platforms of the Interactive medium," said George Ivie, Executive Director and CEO, Media Rating Council. "Agencies and marketers should feel assured that the Interactive industry is striving for increased reliability and consistency through the guideline-setting process and through their support for audits."
The establishment of these guidelines will provide marketers with a standard for the consistent and reliable measurement of their performance based marketing. Independent auditing against the complete guidelines should provide advertisers with added security for their internet advertising investment and further solidify the increased level of accountability and transparency already established by this medium.
"Click Measurement is the next phase of the Interactive industry's groundbreaking Global Measurement Guidelines initiative," says Greg Stuart CEO of the IAB. "These guidelines demonstrate our continued commitment to being the most accountable advertising medium and providing marketers with the highest possible level of transparency."
The Click Measurement Working Group is open to all IAB Members. For additional information, email Erica@iab.net. A full copy of the already completed Global Measurement Ad Impression Guidelines can be found at www.iab.net/standards/measurement.asp.
MSN OFFERS BEHAVIORAL TARGETING
ClickZ, Kevin Newcomb, 09/06/2006
Microsoft has begun implementing behavioral targeting of display ads on MSN sites.
The behavioral targeting technology will place Web customers into one of 18 segments as dictated by a combination of their online search habits and Web pages visited. Based on their segment, customers will be served display ads that are relevant to their interests.
Some of the segments available for targeting include parents, new/expecting moms, mobile users, power users, gamers and movie watchers. In addition to an auto buyers category, Microsoft breaks out researchers of luxury cars, sports cars, pick-up trucks, SUVs and passenger cars. For travel-related categories, there are segments for hotel, cruise, and airfare seekers. Financial categories include home buyers, credit card shoppers and personal investors.
An advertiser could, for example, choose to show ads to new mothers and parents, and MSN would show the ads to those visitors to any Microsoft sites that have been identified as members of that segment, while showing other ads on the same page for visitors from other segments.
"The benefit is two-fold: Consumers benefit from ads that are relevant to their interests; and advertisers benefit by reaching relevant audiences and increasing ROI," said a Microsoft spokesperson.
Microsoft first previewed the targeting capabilities to select advertisers at its Strategic Accounts Summit in May. Although these display ads are not yet being served through Microsoft's adCenter platform, they eventually will be. Improved targeting, including behavioral, has been at the core of adCenter since it was first previewed to advertisers last year. The company revealed some of its targeting tools in June, through the adCenter Labs project.
Yahoo has offered behavioral targeting across its network for a few years, first with its Fusion and Impulse offerings, and more recently with new targeting capabilities with segments for "Engagers" and "Shoppers." More behavioral targeting tools are also expected in Yahoo's upcoming Panama search ad platform, expected later this year. For its part, Google has said that it has no plans for behavioral targeting this year, but it's likely to be offered at some point, especially in light of some of its patent applications that reference it.
WHAT'S THE BIG DEAL WITH SOCIAL SEARCH?
Search Engine Watch, Chris Sherman, 08/15/2006
Social search is garnering a lot of attention these days, but despite all the hoopla it's not likely to displace traditional algorithmic search any time soon.
What is social search? There isn't even a good definition, because just about everyone who's doing some form of social search is trying a different approach. Simply put, social search tools are internet wayfinding services informed by human judgment.
Wayfinding, because they're not strictly search engines in the sense that most people know them. And human judgment means that at least one, but more likely dozens, hundreds or more people have "consumed" the content and have decided it's worthy enough to recommend to others.
But that word "informed" can mean many things. In its broadest sense in this context, informed means "influenced," and in the best of all possible worlds this influence is helpful, thoughtful and wholesome. Unfortunately, some "informed" influences on search results come from egregiously uninformed people and downright idiots.
Social search takes many forms, ranging from simple shared bookmarks or tagging of content with descriptive labels to more sophisticated approaches that combine human intelligence with computer algorithms. And despite all of the recent attention, social search isn't really new. So why is it such a hot topic? To understand, it's helpful to know a bit of history of human mediated search efforts.
A brief history of social search
We've always had social search, even from the early days of the internet. Before the emergence of the first search engines in 1993 or thereabouts, people relied on pages with links to their favorite sites. One of the first was created by web inventor Tim Berners-Lee, and it's still online—though most of the links on the page have been long broken.
Yahoo, one of the first directories of web sites, was created by a team of human editors who surfed the web and wrote up brief descriptions of the sites they found. The Open Directory Project, the Librarians' Index of the Internet and the U.K. based Resource Discovery Network are all directories of web sites created by people, and all have been around since the early days of the web.
You can argue that even algorithmic search engines, which rely on automated software based crawlers and indexing systems, are social search systems to a degree—after all, the software is written by people and incorporates judgments about quality, relevance and importance of web sites.
Indeed, Google's famous PageRank algorithm, which analyzes the link structure of the web and assigns more importance to pages with many "high quality" links pointing to them, is fundamentally a form of social search. Why? Because PageRank is relying on the collective judgment of webmasters linking to other content on the web. Links, in essence, are positive votes by the webmaster community for their favorite sites.
Social search as it's evolving today incorporates both automated software as well as human judgments about the nature of web content. That's what makes social search intriguing—and fundamentally flawed, at least at this point.
Why? Several reasons.
Fundamentally, no matter how many people get involved with bookmarking, tagging, voting or otherwise highlighting web content, the scale and scope of the web means that most content will be unheralded by social search efforts. The web is simply growing too quickly for humans to keep up with it.
That doesn't mean that social search efforts aren't useful—in most cases, they are. It simply means that people-mediated search will never be as comprehensive as algorithmic search.
Another problem arises with tagging. Despite the popularity of tagging, especially with the web 2.0 mob, tags are not a panacea for categorizing and organizing the web. When used properly, tags can be very helpful in describing web content.
But problems arise with the inherent ambiguity of language—words often have multiple meanings, and people can have different interpretations of the same word.
The web lacks what librarians call a "controlled vocabulary," a set of terms that have specific, unambiguous meanings that can be used in a uniform, consistent fashion by everyone tagging web content. Without this controlled vocabulary, tagging ultimately remains a chaotic, messy process.
Another factor is human laziness. Even if a controlled vocabulary were available, not everyone would take advantage of it. We've always had the ability to add tags and other metadata to our Microsoft office documents, and yet how many people do this?
We also have a problem with idiots and spammers. Some people, no matter how well intentioned, will simply do a poor job of labeling content. Others will deliberately mislabel content to attempt to fool search engines. In both cases, it's difficult for software to recognize this spuriously labeled content. In social search, it's difficult to filter the noise from the signal.
Despite these problems, social search still holds promise for improving our overall information seeking and consuming activities on the web. Ultimately, it's likely that a combination of algorithmic search and the various types of social search systems will fuse into a hybrid that will work really well for a satisfying wide variety of information needs.
We're not there yet, but I'd expect to see real progress sometime over the next couple of years.
Who's Who in Social Search (08/16/06)
Many players, big and small, are working in the social search space. Here's a look at who's doing what to harness the power of human beings in improving search.
In yesterday's SearchDay, What's the Big Deal With Social Search?, I offered an overview of social search, touching on the pros and cons of injecting human judgment into what has traditionally been a heavily algorithmic process. Today I'll map out the various approaches to social search and some of the key players in each area.
Most of the major web search services are dabbling with social search. Other, smaller companies are creating social search tools as the core foundation of their business. Most social search services have some distinguishing technology or approach. What follows isn't a comprehensive overview of what's out there. Rather, it's a sampler of what's going on in the space.
While all of these services can surface interesting content, they tend to reflect the biases and interests of their most avid users. And since even people with a lot in common can also have widely divergent interests, they often contain "noisy" results that may not be relevant.
Shared bookmarks and web pages
One of the first types of social search services to emerge sought to leverage the power of shared bookmarks. The idea here is that if people save a particular page as a bookmark or favorite, they're effectively voting for the page—fundamentally the same idea behind Google's PageRank, but counting the "votes" of web users rather than webmasters.
There are literally hundreds of these types of shared favorites services. Among the more popular are Del.icio.us, Shadows, Yahoo's MyWeb, Furl and newly launched Diigo.
Collaborative directories
In the early days of the web, directories were the most popular information finding tools. Directories are compilations of pointers to web sites created by humans, who typically write descriptions of entire web sites distilled into pithy one or two sentence descriptions.
As the web exploded in size, labor-intensive directories fell out of favor in relation to algorithmic search engines which could easily scale to catalog many billions of individual pages. But the "open source" model of allowing numerous volunteers to collaborate has saved the directory model.
All of these collaborative directories have a limited scope compared to algorithmic search engines such as Google, Ask and MSN. But limited scope also means that most of the entries in these directories are high quality and you needn't worry too much about spam creeping into search results.
The Open Directory Project is the original collaborative directory. The ODP is a great resource, but has suffered from years or neglect by its owner, AOL. Newer collaborative directories with fresher, and often potentially better results include Prefound and Zimbio. Wikipedia, even though it's ostensibly an encyclopedia, contains so many links to authoritative web pages that it should also be considered as a collaborative directory to the web.
Taggregators
Taggregators, or tag engines, for want of a better word, tend to focus on blog and feed-based content on the web. These services cluster content based on the labels that users have created to describe the content. While tags can be useful, especially for things like photos, music, video, and other content that doesn't have text that can be indexed by search engines, tags can also be easily misused, with inaccurate, ambiguous or even misleading words.
Popular taggregators include Technorati and Bloglines.
Personalized verticals
Personalized verticals are a relatively new approach to social search. These services make it easy for anyone to create a specialized search engine focusing on a relatively narrow topic. All you need to do is define the topic area that you'd like the search engine to focus on and then do a bit of tuning once the search engine has built the specialized index for you.
You can also include your own ads in search results for your personalized search engine, allowing you to monetize your efforts and compete, at least on a small scale, with the major search services.
Eurekster and Rollyo are good examples of this relatively new breed of services that let you create your own vertical search engine.
Social Q&A sites
Question and answer sites are yet another category of social search sites that have been around forever. Most public library sites offer "aska" services, which allow you to post questions to librarians and get answers, by email, instant message or SMS. Online forums and bulletin boards have also served the purpose of allowing people to post questions and get answers.
Google started its Answers service several years ago. Want an answer to just about any question you may have? Simply post the question and offer a bounty from $2 - $200, and you'll get consideration from an army of Google-qualified volunteers who will research the question for you.
Other Q&A services, which are free, include Yahoo Answers, Answerbag, Wondir and others. MSN also has its Live QnA service in early prototype.
Collaborative harvesters
Tagging allows content creators to create descriptive labels for their material, but as I mentioned earlier, tags aren't always accurate or even helpful for users. Sometimes you want recommendations from people who've already consumed the content and have found it interesting, useful or entertaining.
Collaborative harvesters are a relatively new breed of tools that tap into the collective wisdom of their users. When a user of one of these services finds something interesting on the web, they nominate it for consideration from other users. People then "vote" on the content, and any content that garners enough votes gets pushed forward as a recommended source for the rest of the community.
Among the more popular of these collaborative harvesting services are Digg, Netscape, Reddit and Tailrank. If you really like the idea here, a site called popurls.com aggregates all of the top recommendations from these and other web sites including Flickr photos, YouTube videos and others, all on a single page.