Previously: My Impressions of Davos

I thought I’d share my “Davos Moments” with you, when what I witnessed was so powerful I got chills. One session alone spawned three such moments.

The session was headed by Miguel Nicolelis, a professor of neuroprosthetics at Duke. Prior to this session, I didn’t know that neuroprosthetics was even a word. Essentially, it is the ability for your brain to move a prosthetic attached to your body just by thinking about it.

Professor Nicolelis gave us an amazing live demonstration of his work. Via satellite, he showed a monkey named Clementine walking on a treadmill at his lab in Durham. The brainwaves from the monkey were transmitted to a robot in Tokyo. Using mathematical models that replicated electric signals sent by the brain to cause muscles to move, the data were fed to the robot in real time, causing it to walk just like Clementine. In another variation of the experiment, they had the monkey think about walking, which caused the robot, in Tokyo, to walk just as the monkey would. But here’s the clincher—the amount of time it took all of this to occur was 118 milliseconds. That is faster than the time it takes Clementine to send signals from her own brain to her own leg.

Thinking about our soldiers coming home from Iraq who have lost limbs, as well as a 16 year old boy from our hometown who had an accident this summer and is now paralyzed from the neck down and the hope that this research represents for them, literally gave me chills and brought tears to my eyes. Meet Miguel and see a demo on YouTube.

That was my first Davos moment.

There were two other professors from MIT on that same panel who are also doing fascinating research in this area and each had equally gripping presentations. One, Hugh Herr, is a double amputee. While still in high school, he was mountain climbing one day, got caught in a storm and contracted frostbite, resulting in the loss of both his legs from the knee down. Since then, he has become a leading-edge researcher and has what he claims is the “benefit” of being able to test his work on himself. Seeing him walk, you would never guess anything out of the ordinary. But during his presentation, he lifted his pant leg and walked through the audience, inviting us all to closely observe how the prosthetic mirrored the complex movement of the foot and leg. It was amazing, eliciting images of “The Six Million Dollar Man” and “The Bionic Woman.”

Hugh’s future plans are to connect his brain to this amazing prosthetic device. This not only includes information flow from the brain to the limb, but also from the limb to the brain. So, when Clementine is thinking of walking, the robot will be walking, but with this new technology, Clementine will also feel like she’s walking. Hugh told us “This year, I’m happy to tell you I can walk – even run – on the beach. Next year, I hope to be able to tell you that I can also feel the sand on my feet.” He went on to joke that: “the last time my brain was connected to my legs, I was a D student in high school. Then, they became disconnected, and I became an MIT professor. Not sure what will happen when they’re connected again – hope I don’t revert to my high school days. Better get tenure first.” And, yes, he still mountain climbs!

That was another Davos moment.

But there’s more. As I was writing this piece, Miguel Nicolelis himself just happened to sit down next to me! He is as genuine and as down-to-earth a guy as you’ll ever meet. We got to talking, and for the next 45 minutes, he gave me a personalized lesson in neuroprosthetics, including a discussion of the mathematical models that explain the neural signals. (Surprisingly, they are actually linear.)

In addition, I learned of Miguel’s aggressive plans – already underway – to build a string of “science cities” all over his home country of Brazil, the center of which will be in Natal, a remote and impoverished area. The vision is that these will be high-quality schools that specialize in science-related subjects, but provide high quality education, often using scientific concepts for learning in all areas, such as the scientific method. The plan is that, over time, these hubs will attract both high-tech companies and research institutions, a concept that is taking hold in several developing countries, and especially across Asia.

You can read more about this in this month's Scientific American, but the idea is to create an environment in Brazil where accomplished students can work and succeed without emigrating to other countries, thereby slowing the brain drain and improving the socioeconomic conditions, and ultimately, improving the quality of life for the people of the students’ home country. Miguel believes strongly that “you don’t need a Ph.D. to make contributions to science, you just need the right environment.” In the last few years, he’s managed to secure initial funding for this project, and 400 students are currently enrolled. His plan calls for 1 million students to be enrolled in a series of schools all over Brazil two years from now. One million students. Talk about “Thinking Big.”

Next: Davos Moment #4

With behavioural targeting, the Internet is finally beginning to deliver on some of the promises made to advertisers more than a decade ago. Leading web companies are literally “buying into” behavioural targeting. In 2007, AOL spent around $200 million for Tacoda, Yahoo! plunked down $300 million for Blue Lithium, Google paid $3.1 billion for Double Click and MSN invested $240 million in a 1.6% stake in Facebook (valuing the company at roughly $15 billion).

comScore has been passionate (TV preacher passionate) about the potential of behavioural targeting from the start. We know that it is very helpful for an advertiser to know what a consumer is doing, in addition to their demographic attributes like age or gender. For example, if a consumer spends a significant amount of their time visiting online travel sites or comparing airfares, we may infer that they are planning a trip. By looking at the rest of their online behavior, we can then uncover additional insights about this segment such as where else on the Web they are likely to be found.

comScore collects behavioural data and has performed a lot of custom segmentation work for clients over the years. In 2007, we added behaviorally defined segments to our syndicated Media Metrix product, creating a new online behavioural targeting tool. This tool, comScore Segment Metrix: H/M/L, gives clients the ability to track, analyze and report online activity by consumer segments, to deliver robust behavioral profiles of these groups on demand.

comScore Segment Metrix: H/M/L gives our clients the ability to find the “travel planner” when they are not planning that trip, or the car enthusiast when they are not on auto sites. It lets us know where they search, what email they use and which sites they get their news from.

This behavioral insight will allow our advertising clients (and the agencies that represent them) to better target their activities, improving efficiency and increasing return on online marketing investment. Conversely, media owners looking for ad revenue can identify the advertising categories (e.g. Travel or Autos) for which their sites deliver a high proportion in their audience.

This is exciting stuff and in 2008 our industry will finally get to that ‘promise-d’ land of behavioral targeting! Look here for additional examples of behavioural targeting in the coming weeks.

For good reason, concerns about privacy and data security have become an increasingly visible issue for the marketing industry in recent years – perhaps most notably in the online sector. The unprecedented access to data provides innumerable benefits to both consumers and businesses alike. It also demands a great deal of responsibility regarding how that information is gathered, protected and used. In this context, I think it’s critical to draw specific attention to the discipline of market research, its use of data and the many benefits it provides to corporations, academia, and the overall economy.

For generations, market research professionals have conducted invaluable studies of consumer attitudes and behavior for both the public and private sectors. Surveys and behavioral tracking studies provide the information necessary to ensure sound economic and social policies in the public sector. Information on consumer behavior and preferences helps the private sector develop new and improved products, identify new health care needs, improve the ergonomics of the products we use, spend their marketing dollars more efficiently and create countless products and services that improve the quality of life for everyone. Without market research, corporations would be operating “in the dark”, inefficiencies and error rates would increase, more new products would fail and the resulting increased marketing costs would have to be borne by the consumer. That’s not a pretty picture.

The Internet is a good example of an industry that is critically dependent on credible third party research that provides anonymous information on issues such as e-commerce trends, Web site visitation statistics and audience demographics, search activity, online advertising effectiveness and insight into countless other online behavior patterns. As with traditional media, advertisers demand such independent information in order to confidently invest in advertising-supported Web sites, which depend on advertiser support to offer free services to consumers.

However, the growth of the Internet as a powerful new medium also introduces the need to define specific practices of privacy protection and data security, to create an environment in which market research can continue to play its vital role. At comScore, we adhere to strict tenets that the market research industry has fundamentally observed for decades. As such, we:

• Provide research participants with clear notice of software functionality and data collection practices;
• Obtain consent from participants prior to installation of any data collection software or collection of any behavioral data;
• Collect and use data exclusively for market research purposes, and not for purposes of marketing or advertising products and services to our research participants;
• Neither divulge, nor sell, personally identifiable information (PII) in any fashion to our clients;
• Strictly safeguard the personally identifiable information, privacy and anonymity of panelists through technological means and established security practices;
• Provide an easy method through which participants can cancel participation; and
• Participate in review and certification of our practices by recognized and objective third party authorities

I believe that the relationship between a research participant and all reputable market research companies that adhere to these practices is important, and should be preserved. Market research tracking software (we have dubbed it “researchware”) needs to be differentiated from “adware,” “spyware,” and “malware” and should not be treated in the same way as these intrusive and potentially harmful applications. We must not let the purveyors of spyware – the rotten apples – give market researchers a bad name.

There is clear precedent for such differentiation in the U.S. Federal Trade Commission’s creation of the Do Not Call (DNC) Registry and the Telemarketing Sales Rule (TSR). Following a comprehensive review process, the FTC clearly differentiated survey research from telemarketing calls, thereby excluding market research from TSR and DNC prohibitions.

comScore will continue to safeguard the future of online market research as a crucial source of information and insights for industry, government and academia. I urge other market research and marketing firms, universities, industry and consumer associations – and the media – to join us in supporting the researchware initiative, thereby ensuring the continuation of legitimate forms of research that benefit society and the global economy.

Previously: My First Impressions of Davos and Davos Moments 1-3.

My fourth Davos moment came when Magid and I participated in a three-hour exercise where we were essentially tasked with finding a formula for peace in the Middle East. Upon entering the meeting room, we were each assigned to random groups. Each group was given a set of facts about the fictional country, which loosely resembled Iran, Iraq, the UAE and “Dominania,” aka the United States. A fifth group consisted of private sector investors, presumably Sovereign Wealth Funds. The session was moderated by a well-known journalist from Al Jazeera. Most of the participants were high ranking officials from Middle Eastern countries. Interestingly, I believe that one U.S. government official and I were the only American-born team members.

As it happened, I was assigned to the “Dominania” group, and was selected by my team to be our ambassador to the other countries. We were given instructions to come up with a plan to achieve peace and stability in the region, while furthering the economic interests of our people. Our team had members from Saudi Arabia, Lebanon and Egypt, and I have to say, they were all bright, articulate, and eager to devise a plan that achieved these objectives. We each embraced our roles.

Together, we managed to devise some very interesting proposals. And I suddenly developed a newfound appreciation for the difficulty of Condi Rice’s job.

One thing that was clear to me from the exercise is that if we’re ever going to make progress toward stability in the Middle East, all sides are going to have to learn how to communicate, negotiate and collaborate in ways they have not before.

So, there you have it: just a few of my many, many Davos Moments. Oh, and one other magical thing about Davos: it is the only place in the world where my husband will drag ME onto the dance floor at 2:00 am in the morning. Those of you who know us understand the significance of that. For those who don’t, you’ll have to trust me when I say that was also a Davos Moment – one of the best kind.

This blog post originally appeared as my column in MediaPost's Online Metrics Insider on February 5.

Last week I was meeting with a client (Hi, Marlene!) when we started talking about the demographic composition of an entity's audience for Unique Visitors (UVs), as opposed to Page Views (PVs). As you can imagine, when you're chief research officer at comScore, you go to a lot of meetings where clients want to talk about... how can I put this delicately... let's just say, when they love their numbers, they seldom call.

Sometimes when talking with clients, I hear the concern that their site targets a specific demographic niche, and yet that niche comprises a disappointingly small portion of their UVs. Invariably I'll hear something like this: "But 85% of our registered users are left-handed Irish backgammon players aged 45-54!" The implication being, the profile of their UVs skews somewhat less targeted.

But here's the thing. The UV metric is democratic to a fault. Every visitor -- the accidental tourist who hits the site once for thirty seconds ever, and the core user who spends an hour a day there -- counts once and only once in the UV. There are a lot of things that can affect a site's UV demographic composition; one of them is search. Suppose that essence.com, which targets African-Americans, runs an article about Tiger Woods. It is possible that many golf fans who do not happen to be African-Americans will end up at essence.com that month because they searched for "Tiger Woods." This search-generated traffic will contribute to the UV metric, even as it dilutes the demographic target.

A better gauge of a Web entity's user profile would be to look at the composition of PVs, because heavy users will drive PVs and tend to counteract the diluting impact on the core target that a UV metric can have. In December 2007, for example, Media Metrix reported that 62% of Unique Visitors to aarp.org were age 50+ (eligibility for AARP kicking in at age 50); but 77% of their Page Views were accounted for by persons 50+, and 79% of their total minutes.

But there is another important reason to think in terms of pages when assessing a web entity's audience make-up. Ads are distributed across pages, not UVs. The more pages one consumes, the more ads one is exposed to, and the more likely that consumer is to see your ad. If an advertiser runs a campaign on a site, the audience profile of the exposures to that campaign will tend to mirror the profile of the Page Views, not the Unique Visitors. In the AARP example above, then, let's restate thusly: 62% of the aarp.com unique audience is comprised of persons 50+, but these persons see almost 80% of the ads.

With a behavioral targeting as opposed to demographic targeting construct, the difference can become even more pronounced. A specific automotive shopping site (here I've chosen to mask the property) had 4.2 million UVs in December 2007. 12% of these UVs (roughly 500,000) came from among the 5.3 million online users who were among the 20% heaviest visitors to automotive manufacturer websites in that month (and who are thus logically highly likely to be in-market for a new vehicle.) But 24% of their PVs, and 25% of their total minutes, came from these "auto intenders." One in four ads at this site will be seen by someone who is in the heaviest 20% of users of automotive manufacturer sites in the same month. When we expand our behavioral target to include the heavy and moderate users of automotive manufacturer sites, then about half the ads on this site will be seen by automotive intenders.

Two final points. One, when I talk about looking at the composition by Page Views here, I really mean, look at composition based on a measure of total consumption as opposed to the total UV (or "cume") audience. If you are concerned about the impact of AJAX on the efficacy of the PV as a metric, the same principle applies with respect to minutes as with pages. In radio, for example, the 36% of a station's cume who comprise the station's core audience consume 72% of that station's quarter-hours of listening.

And two: How about those Giants?

Many of the readers of this blog will probably remember the firestorm caused by comScore’s release of statistics regarding Radiohead’s unique online offer to “pay what you want” to download their new album, “In Rainbows.” comScore’s data showed that about 62% of the people who had initiated a download of the album did so without being willing to pay anything. Radiohead claimed that our data were “wholly inaccurate,” but refused to provide any of their own statistics.

Recently, in an interview Radiohead’s Thom Yorke let slip that the free download percentage they were seeing was actually “about 50%,” which is, in fact, not very different from comScore’s estimate of 62%.

Rather than leading to the band’s conclusion that the comScore data are wrong, I think Thom Yorke’s acknowledgment that the free download percentage was “about 50%” confirms that comScore’s statistics were probably very much in the ballpark. In fact, when taking into consideration the fact that Radiohead is probably counting the percent of completed downloads that were free, whereas comScore counted the percent of initiated downloads that were free, I believe the numbers are very consistent. I say that because we need to bear in mind that when Radiohead’s offer was announced, traffic to the download site was too heavy for the site’s server to handle and it wasn’t unusual to be put into a downloading queue. No doubt, a greater proportion of the people who didn’t pay anything were likely to abandon the download attempt if they had to wait in the queue than were people who had already used their credit card to pay something. This would lead to the band seeing a slightly lower percentage of completed downloads being free (~50%) than comScore’s 62% estimate of initiated free downloads.

That said, the inescapable conclusion – from comScore data as well as from Radiohead’s own comments – is that anywhere from 50 to 62% of the people who initiated a download of the “In Rainbow’s” album did so without being willing to pay anything.

While that may sound like a disappointing result, it’s certainly better than the experience of hip-hop artist Saul Williams, whose album “The Inevitable Rise and Liberation of Niggy Tardust” was released online in two versions (with the help of Nine Inch Nails frontman Trent Reznor, who financed and produced the album). One version could be downloaded free, while another higher-quality digital version could be downloaded for $5. CNET news.com reported recently that 82% of the people who downloaded the album chose to do so for free.

I think these results confirm that the majority of consumers – when offered the choice to download music free or to pay for it – will choose the free option. However, this doesn’t mean that this distribution method is economically a failure for the musicians. The fact that they get to pocket most of the cash could well mean that they end up making more profit than if they had distributed through a record label. Of course, we’ll never know for certain until someone discloses some detailed financial data, including profits. I wonder who will be first to do that?

I was recently interviewed by Eric Enge at Stone Temple Consulting about the search industry. We cover a lot of issues focused around the evolution of search as a marketing vehicle. You can read the full interview at http://www.stonetemple.com/articles/interview-james-lamberti.shtml

Like many of you, I’ve been following the 2008 presidential primary season with great interest. And while the first non-incumbent election in decades has made the early races even more intriguing than usual, it’s especially exciting for me to see the very important role the Internet has played in shaping the course of the primaries.

Back in 2004, former Vermont Governor Howard Dean’s campaign really woke everyone up to the power of the Internet in politics. The Washington establishment had become accustomed to the way elections had been won over the course of the past several decades –TV ads, newspaper media coverage, direct mail, and good old fashioned machine politics. But Dean, the firebrand Washington outsider who was never supposed to stand a shot at the nomination, managed to stir up a strong grassroots movement using the Internet and raised enormous sums of money online, propelling him to his unlikely status as the Democratic frontrunner. Though Dean’s campaign ultimately fizzled, it left an indelible imprint on American politics. The Internet was quickly changing the political landscape and candidates realized that they ignored it at their own peril.

Fast forward to the 2008 primaries. Every political candidate learned the lessons of Howard Dean and now has a well-organized Internet strategy, including high-powered, multimedia websites, personal profiles on MySpace and Facebook, and their own YouTube channels, as a starting point. But it’s not just about having a presence online -- the real significance of the Internet lies in its ability to cultivate a movement.

I’ve heard a few people call it “the Facebook election” in reference to the way this election -- and Barack Obama’s candidacy, in particular -- has excited young voters in a way that hasn’t been seen since the 1960s. The primaries have seen younger voters turn out in record numbers and take an active role in contributing their time, energy, and even money. The Internet is lowering barriers to entry and making it easier for many people to get involved and stay informed. It is also making it much easier for average folks to open their wallets and contribute with a few clicks of the mouse.

Money has played a more significant role than ever before, as candidates continue to set records for fundraising. In the past, raising money meant sending out mailers and making thousands of phone calls, which required a considerable investment in resources which typically yielded a slow trickle of contributions. Not anymore. Now the candidates can blast an email to the millions of people on their email list for a fundraising drive, and get them to contribute online in a matter of seconds. In the hours and days after Super Tuesday, both the Obama campaign and Clinton campaign parlayed their respective victories into massive online donor drives. Obama raised more than $7 million in just one day after Super Tuesday, while Clinton reportedly raised $10 million within just a few days. To date, both campaigns have raised well in excess of $100 million since the beginning of 2007.

Though the fundraising on behalf of both campaigns has been unprecedented, Obama has had a distinct advantage in online fundraising. This was apparent in the comScore data, which showed Obama with a 3:2 advantage versus Clinton in the number of visitors to his donation page in January (256,000 vs. 171,000). Interestingly though, if we assume that each visitor to the donation page was indeed a donor, Hillary’s website had a higher conversion rate (15% vs. 12%).

Looking at the traffic trends to the two candidates’ websites, there are a few interesting things to note. For most of 2007, visitation to their websites ran pretty much neck-and-neck even though Hillary was generally running much higher in the national polls and was considered by many the presumptive Democratic nominee. But as Obama’s campaign has seen a momentum surge in January and into February, we’ve actually seen visitation to his website display separation from Hillary’s, nearly doubling the number of visitors in January (2.2 million vs. 1.1 million).

The relative surge in activity at Obama’s site may be a function of a couple factors. In part, it reflects the overwhelming enthusiasm among his base of supporters. However, it probably also reflects the fact that he’s a newcomer to the national political scene, and many primary voters are seeking to find out more information on him. These lurkers are almost certainly less likely to contribute money right away.

With money of increasing importance at the latter stages of a campaign – especially to compete in the remaining big states like Texas, Ohio and Pennsylvania -- it will be interesting to see if Obama’s campaign can succeed in converting a large number of the newer visitors to his website into a significant fundraising advantage in February. If he’s able to out-raise Hillary by a wide margin, it just may be enough to put him over the top and pull off what once seemed like a highly unlikely upset. And while the pundits will pontificate about race and gender and low-income voter segments, it will be hard to ignore that the Internet will have played a substantial role in determining the outcome of this race.

But no matter who wins in the end, it’s clear we are witnessing a new paradigm quickly take shape. The Internet just may be giving television a run for its money as the most powerful medium in American politics.

Juice Analytics, a comScore vendor, recently prepared an intriguing treemap of the Internet using our data to showcase their abilities. For the full interactive treemap and an explanation of how the data are displayed, click here.

Hello. As a member of the comScore team, I manage the pharmaceutical industry comScore Marketing solutions.

At the recent ePharma Summit in Philadelphia, Evolution Road’s Paul Ivans and I presented our consumer e-marketing effectiveness benchmarks for the pharmaceutical industry.

We’ve done this presentation for the past two years, and the feedback we continue to receive is that this information is really beneficial in helping pharma marketers better understand the landscape so they can better plan their e-marketing initiatives.

For those of you who weren’t able to see the presentation and are interested in learning more, I’ll be participating in a FREE, live podcast with John Mack at Pharma Marketing News THIS Thursday, February 21 from 1-1:30 p.m. EST (followed by a Q&A session).

We’ll be talking about the benchmarks and their implications, specifically discussing which marketing tactics – whether online banner ads, search marketing or branded and unbranded websites – have the biggest impact on:

• brand awareness
• brand favorability
• incremental new patient starts
• incremental current patient adherence/next fill

To learn more about the podcast or to tune in, please visit http://www.talk.pharma-mkting.com/show043.htm or dial in to the live podcast at 347-996-5894. And, if you can’t make the live show, the podcast will be archived on the ePharma Marketing Web site.

I’m looking forward to a great discussion and hope you are able to join us…

Kevin Mannion’s January 25 blog about engagement metrics on MediaPost’s Online Metrics Insider raises some interesting issues about online measurement, but fails to address the inability of site server data to provide any of the key people-based metrics that are needed for online media planning and analysis. In the world of online media, I never cease to be amazed at how easy it is for some to forget or ignore that basic reality of advertising. Earlier in my career, I spent 14 years at Leo Burnett and can assure you that we didn’t plan our media efforts around advertising to TV sets. No, we advertised to the people watching the TVs. And so it is with the Internet. Online media planners, just like their offline counterparts, fundamentally need to know how many unique people are visiting a particular site, with what frequency per person, and they need to know this by demographic segment. I have yet to see server log data that comes anywhere close to providing this people-based information.

It’s left up to the comment by John Grono of GAP Research in Australia posted on Mannion’s blog to set the record straight by highlighting some of the key problems with site server data and revealing the ugly reality of what happened in Australia, where the use of server data resulted in an estimate of that country’s online population that was more than twice the size of the entire Australian population! As John notes, the Australian experience has unequivocally shown that site server data grossly overstate the true number of site visitors.

The most deleterious problem with site server data is caused by cookie deletion. An important comScore study published last year showed -- beyond a shadow of a doubt -- that 31% of Internet users delete their cookies in a month and that the average cookie deleter does so four times per month, resulting in the placing of five different cookies for a single site on a deleter’s computer in the course of a month. Every time an Internet user returns to the same site after deleting their cookies, they will be counted as a new user. This can result in a dramatic exaggeration of the size of a site’s audience by as much as 2.5 times when using site server data. To make the problem even more acute, there is such a large variation across sites in the rate of cookie deletion among their visitors and their frequency of visitation to the sites that it is essentially impossible to build a model to predict the degree of exaggeration for individual sites based on site server data.

Beyond the cookie deletion problem, there are other problems with server data:

1. Cookies (or page tagging / beacon approaches) are incapable of accurately counting the true number of individual users:
   1. The same person may use different computers (e.g. a work and home machine) to visit the same site in a day and will be counted as two individual visitors
   2. Different people using the same computer and visiting the same site will be counted as one visitor
2. Server data cannot reliably determine if the visitor is a real person or a computer. In fact, some industry observers have estimated that “bot” traffic at a wide variety of sites now accounts for more than 30% of all traffic to those sites.
3. Using server data, there is often no way to reliably identify the geographical location of a visitor. For may U.S. sites with large numbers of International visitors, this can create massive exaggeration in server-based estimates of U.S. audiences by as much as 4.5X, which is incremental to the overstatement caused by cookie deletion.
4. Last, but by no means least, server data provide no information on the demographic characteristics of site visitors.

It is challenging for publishers to reconcile the conflicting data they get from multiple metrics sources, and understandable in today’s competitive environment that there is a desire to tout the highest audience count possible to both advertisers and investors. However, as comScore and other industry bodies have been working to educate users on the fundamental differences between server data from web analytics providers, and panel data from audience measurement companies, it is encouraging that publishers are increasingly relying on the audience measurement data to tout audience size. This is as it should be.

Intriguing though the concept may appear, the claim that server data can be integrated with panel data in order to obtain accurate online audience data is fundamentally flawed. No amount of “black box” manipulation can correct for the fact that server data are incapable of knowing who is on the computer visiting the site. You simply can’t make a silk purse out of a sow’s ear.

I fail to see how Quantcast can make the claim that panels aren’t capable of measuring the mid to long tail of the Internet (“the fragmentation of the Web kills the utility of the panel”) while at the same time saying that they start with panel data to adjust the server data. You can’t have it both ways. If the panel data’s sample sizes are too small to be able to measure these sites, how on earth can one possibly say it can be used to adjust for all the errors inherent in server data when it comes to counting people. No, the simple fact is that this methodology will end up relying on the server data and exaggerating the size of the sites’ visitor base.

As a final point, I think it’s important to reiterate the observation made by John Grono in his comment that some of the largest and most important sites in Australia decided to not provide their server data to third parties. This would appear to be a “deal killer” for any integration initiative before it even gets started. If many of the most popular Web sites in Australia decided to “not play ball”, I think we can take it for granted that the U.S. market will see many more sites deciding that their competitive position will NOT be enhanced by sharing their data with third parties.

I think it was H. L. Mencken or Albert Einstein (a quick search showed me that they are both cited as authors) who said: “For every complex problem, there is one simple – but wrong – solution.”

I was reminded of this quote when I read a blog posting on the Adify site where the discussion focused on how to measure the effectiveness of online display advertising.

For me, the quote sums up the challenge. While it’s alluring to believe that there is one simple, easily-obtainable metric that will accurately and reliably predict advertising success, I believe this is a siren’s song. And, I suspect that most experienced researchers who have spent decades searching unsuccessfully for advertising’s Simple Holy Grail have also come to the conclusion that, while there certainly are simple metrics that can give you some insight, they’re far, far from foolproof as a measure of advertising’s impact on sales. And sales, I would argue, is the one undeniably relevant metric for evaluating ad effectiveness. Unfortunately, however, measuring advertising’s sales impact is something that’s often difficult to do – especially since it’s often vital to measure advertising’s cumulative impact on sales across time and channels and to cleanly separate this from the impact of everything else that’s going on in a brand’s marketing mix.

This brings me to the validity of the click as a measure of advertising effectiveness. For many years, the click was used as a supposedly accurate measure of the effectiveness of display advertising. Now, I would be the first to agree that – for some direct response ad campaigns – the click remains a relevant metric. However, when it comes to measuring the impact of brand building advertising, the idea that consumers’ immediate response via a click is hard proof of the effectiveness of display advertising is just plain wrong. Perhaps, in the early days of online advertising when click through rates were running at levels of 5% or so, it was easy to believe otherwise. But, as click rates have dropped to a fraction of one percent it has become clear that some other metric is urgently needed. To believe otherwise today would be to acknowledge that display advertising has no impact at all. Perish that thought!

comScore’s objective in conducting the click study with Tacoda and Starcom was to prove – once and for all – the limitations of the click as a relevant metric to use to measure display advertising effectiveness. I believe this is a critical step in the evolution of online advertising because if our industry is to continue its torrid growth, we have to look beyond direct response advertising dollars. We have to convince the brand-building advertisers that they should move more of their ad dollars from traditional media to the Internet. Rest assured, we’re not going to be able to do that using clicks as the metric of choice. Instead, we have to be able to show that display advertising increases brand sales over time and across both online and offline sales channels. I think that Einstein would agree.

James Lamberti, SVP of Search and Media at comScore, is a co-author of this post.

Earlier this week, comScore released its January 2008 qSearch paid click report, which showed a 7% sequential decline vs. December ‘07, and a flat annual growth in paid clicks for Google. Moreover, the number of paid clicks per Google search query declined by 8% from December to January, suggesting that consumers are clicking less on search ads, possibly reflecting a weaker buying appetite. The information triggered a flurry of reactions in the media and the financial community that centered on two concerns: 1) a potentially weak first quarter outlook for Google, and 2) an indication that a soft U.S. economy is beginning to drag down the online advertising market.

While we do not claim that these concerns are unwarranted, we believe a careful analysis of our search data does not lend them direct support. More specifically, the evidence suggests that the softness in Google’s paid click metrics is primarily a result of Google’s own quality initiatives that result in a reduction in the number of paid listings and, therefore, the opportunity for paid clicks to occur. In addition, the reduction in the incidence of paid listings existed progressively throughout 2007 and was successfully offset by improved revenue per click. It is entirely possible, if not likely, that the improved revenue yield will continue to deliver strong revenue growth in the first quarter. Separately, there is no evidence of a slowdown in consumers clicking on paid search ads for rest of the US search market, which comprises 40% of all searches.

The most puzzling data element is that Google’s U.S. paid clicks dropped sequentially by 7%, while, at the same time, its total number of search queries grew by 9%. At the same time, Google’s market share of all search queries grew slightly from December, and its annual query growth remains very strong. All indicators point to the company continuing to do very well as far as consumer usage and competitive position. The drop in paid clicks becomes even more puzzling when it is normalized on a per query basis: The number of paid clicks per search query drops by 16% in one month! The corresponding metric for the rest of the market drops by 4%. What accounts for this dramatic difference?

We must remember that a paid click does not happen on a search results page unless there is an ad on that page. Since not all pages have ads on them, it is important to look at an ad coverage index, defined as the percent of all queries that have at least one paid ad. This index dropped by 8% for Google, going from 52% to 48%. In addition, even when a query result page contained at least one paid ad link, the paid click rate, defined as the average number of clicks per such an ad supported query, declined by another 8%, going from .24 to .22. Figure 1 shows the trend in these two metrics over a one year period. The graph illustrates two time periods where both measures declined together: first from January ‘07 to May ‘07, and then from December ‘07 to January ‘08. The remainder of the year was essentially flat.

Evidently, January ‘08 is not the first time this decline has happened. The compounded impact on paid clicks per search query (whether or not ad supported) for the entire year, is a whopping 33% decline in 2007. The decline in the first half of 2007 clearly cannot be traced to a weak economy. And, despite this decline, Google managed to grow its worldwide search revenue by 68% in 2007. (The company does not separately report U.S. search revenues.) The revenue growth was achieved through a 21% increase in revenue per paid click.

Why and how is this happening? It is common knowledge in the industry that Google has been targeting what it deems to be low quality ads. It has introduced a ‘quality score’ that it uses to prioritize placement of ads or to decide to suppress an ad altogether. A suppressed, or ‘non active’ ad, can be reinstated by raising the bid above a quality-based minimum bid. In addition, the real estate available for ads is being reduced, squeezing the supply of available spots to bid on. The reduced supply, as well as the higher minimum bids, contributes to an increase in the price per paid click, which is what helps counteract the slowdown in the absolute number of paid clicks. Therefore, Google’s revenue will not necessarily suffer from this. In fact, Google wins by providing more relevant ads for consumers and a less cluttered ad environment for marketers.

This policy is explained by Google on their website at https://adwords.google.com/select/qbb.html.

But wait! If this improved quality is real, should we not expect an increase in the paid click rates? Not necessarily. If the ads are more relevant, consumers would need fewer clicks to get what they are looking for. Perversely, a high number of clicks means that the ads are not delivering what the user is looking for on the first try, which induces additional clicks on the second or third try. The benefits to marketers are real, but also counterintuitive. If the users get to what they want with fewer clicks, it means those clicks have a higher conversion rate, or deliver higher quality leads. Hence, a lower number of clicks will likely generate more revenues or better leads for the marketer, justifying the higher average cost per click. Naturally, the changes will not benefit everyone. Rightly or wrongly, some marketers win and some lose, venting their frustration in the blogosphere. The users, on the other hand, will mostly win with improved relevancy and user experience, which helps explain Google’s continued overall query growth and share dominance.

What about the impact of the economy? One might argue that the lower number of paid clicks per ad-supported query indicates that consumers are less interested in buying what is being advertised and lends credence to a worsened economic situation. The trouble is that the pattern does not hold for the rest of the search market. As Figure 2 shows, the paid click rate for the other search engines actually increases slightly. There is no obvious reason why the economy would negatively impact Google’s users and not those of Yahoo!, MSN, AOL, Ask and others. Furthermore, we don’t need a weak economy rationale to explain the recent decline -- since a similar decline occurred earlier in 2007 when a weak economy wasn’t an issue.

In summary, the evidence points to a counterintuitive trend caused by Google’s own program for improving the quality of paid listings.