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UW Guest Lecture Deck - MKTG 555

Here is the deck I used for the University of Washington School of Business class  (MKTG 555 - Entrepreneurial Marketing and Management) I guest lectured at yesterday. It's part of their Center for Innovation and Entrepreneurship program, and I spoke about "marketing your small business across the new landscape of the Web -- Online Marketing v2.0".

UW Biz School Lecture - Fall 2009

View more presentations from Jordan Mitchell.

New Challenges for Web Publishers, Reminiscent of Adware/Spyware Market 5 Years Ago

The market for 3rd party audience data continues to grow, but I'm seeing evidence of illicit activities that are somewhat reminiscent of the adware/spyware activities of 2003-2005. It's disconcerting, because the 3rd party data market has developed the right way so far -- for ALL parties involved, and especially for publishers. But we are now at a point where a few bad apples could spoil the whole bunch, and are causing new challenges for premium publishers.

In the last two weeks, I've been in San Francisco and New York, taking part in 3 different online advertising conferences, and meeting with top 3rd party data companies (such as eXelate, BlueKai, AlmondNet, TargusInfo, Rapleaf, etc.), ad networks, and publishers. A few observations ...

First, I'm starting to see more evidence of illicit data collection from publishers. Just as we saw advertising-based applications illicitly installed on consumer's computers 5 years ago, collecting consumer browsing behavior (without knowledge of the publisher or consumer), valuable audience data is being taken from premium publishers and used by 3rd parties without the knowledge nor the remuneration of the publisher. It's being done via ad tags, which if not properly reviewed/screened, may contain Web beacons that pass audience data to ad networks, advertisers and 3rd party data partners for re-targeting, re-use, etc.

As a result, premium publishers need to be on the lookout for unscrupulous ad networks and advertisers that bring short-term revenue lift but then leave with valuable audience data. And as the market for data expands and $ start to really flow, 3rd party data partners will need to be extra careful to control their data sources/channels. When publishers see these 3rd party Web beacons showing up on their pages via ad tags, it casts a negative light on otherwise reputable data companies -- not the advertiser or ad network who passed the data to the data company in exchange for payment.

Secondly, I noticed some 3rd party data providers are offering an API into their data store. Basically, it's a small snippet of JavaScript that, when placed in the ad tag, pings the data service for any user-specific information which is then appended to the ad server request. This is a fine model and service for publishers when they are using it on their pages, but publishers need to look out for 3rd party ad tags that contain these API calls -- every request out to a 3rd party from their site represents potential "audience data leakage".

Lastly, I was discouraged to hear that some unscrupulous advertisers are buying cheap run-of-network inventory via ad exchanges and running the NAI "opt-out" scripts within ad tags. Just as 5 years ago when spyware companies were detecting/uninstalling competing applications as an offensive maneuver, seems now we're seeing companies attempting to reduce the targetable population for their competition, increase their data acquisition costs, etc.

In the online advertising market where "audience" has emerged as king, safeguarding audience data is quickly becoming a core challenge/risk for premium publishers. This makes it doubly important for publishers to control their sales channels, work with trusted partners only, and leverage technology approaches to ad quality -- all hard things to do for publishers already burdened with increasing ad sales and operations challenges. Yet another reason why premium publishers will increasingly turn to sell-side technology platforms like REVV for Publishers. And for those publishers that don't, they not only risk their own brand and core data assets, they also impede the proper development of the market as a whole.

What is the definition of "Audience"?

So much talk this year in the online advertising market about "audience" -- audience insight, audience-centric planning and buying, audience targeting, audience optimization, etc.

But what is "audience"?

Of course there are multiple definitions, but in the context of online advertising I define it as a "self-selected group of people sharing similar attributes". It's not content. It's not context. It's about people, their self-identified attributes, and their attention. Can we agree?

Ads More Effective on Social Networks than Portals

According to this article and eBay Advertising's 2nd survey of European shoppers, 60% of consumers are most receptive to targeted display advertising when they are on an e-commerce site, compared to 5% on portals and 7% on social networks.

I take this to mean that e-commerce sites are 12x more effective for targeted display ads than portals (and therefore the eCPM cost of portal advertising has to be 1/12th in order for the ROI to be the same), whereas they're 8.5x more effective than social nets.

More shocking is their conclusion that targeted display ads on social networks are 40% more effective than portals!

Ad Exchanges are NOT Like Financial Exchanges

It seems everyone offering an ad exchange would have you believe that ad exchanges are like stock exchanges.  Right Media initiated the flawed comparison back in 2005, ContextWeb named their exchange ADSDAQ in 2007 (missing “NASDAQ” by one letter), and Google continues the comparison today. Certainly the comparison serves a marketing purpose – it conveys a proven model, market efficiency, standardization of the goods transacted, and fairness for all. But ad exchanges are NOT like stock exchanges.

Long before the concept of the “ad exchange” came around, there were other companies (ad networks, marketplaces, etc.) aggregating publisher inventory and advertiser demand. The biggest difference with exchanges though, hence the comparison to the stock exchange, was that their buy/sell model was based on an auction and a winning bidder – every buyer supposedly competes on the same basis for a given impression, just as buyers compete on the same basis for a given financial commodity. This model for buying and selling however is the only resemblance to a stock exchange – it ends there.

When you buy a share of stock on the NASDAQ or NYSE, you know exactly what you’re getting. You have access to the same standardized information about that share of stock as everyone else, upon which to form your own opinion or analysis, and the attributes of that stock are transparent and standardized. It’s on that basis of standardization that stock exchanges have become truly efficient market places. Any transactions based on non-public and privileged information are considered “insider trading”, illegal and economically detrimental.

In contrast, ad exchanges provide very little transparency or standardized information to what you’re actually buying – they simply offer ad inventory by the tonnage through an auction model and cookie retargeting. As a result, buyers are (by design) required to bring their own data to the table. This basically means ad exchanges as they exist today are built on “insider trading” principles and arbitrage – where the winning bids are by buyers who take advantage of market imbalances. These market imbalances allow them to buy the inventory at a price lower than what it’s truly worth. This of course works well for the buyers, but not so well for the sellers whose inventory is being undervalued. The greater the market imbalance, the greater the opportunity cost for the seller.

The imbalance revolves around DATA – all the attributes of the user and impression that increase market value. The more information available, the more potential value in the market place. As Rob Leathern from CPM Advisors points out in a recent AdExchanger blog post:

Despite people talking about how advertising online is data-driven, there is not a lot of good, clean data for buyers or sellers. Bits and pieces of data about a user and ad inventory are everywhere but publisher practices vary … Advertisers, agencies and buyers need to know more about inventory in a standardized, systematic, scalable way and for that to happen, this information needs to be created at the publisher end and retained throughout the buying process whether that is direct, via a marketplace or through an ad network … The more information that is available about an impression, the greater the chance I can make a good decision whether or not to buy it …”

Rob is speaking of course on behalf of buyers. The fragmentation of data, combined with a lack of standardization, makes his job harder. But data fragmentation also makes the seller’s job harder too, and with greater monetary consequences. Exchanges are in a position to level the informational playing field for all and become truly comparable to stock exchanges, yet they continue to separate information from media. Could it be because the exchanges are owned by the same companies that have the most data about each of us, the greatest number of advertisers, and therefore the most to gain from insider trading?

Until exchanges empower publishers with the tools, data and transparency they need to properly value and leverage their inventory in the market, they’re only encouraging the insider traders and arbitrageurs, further shifting the balance of power away from publishers. If exchanges continue to support the current one-sided model, their cost to publishers will exceed the benefit, and the comparison with stock exchanges will be but continued rhetoric.

How Data is Revolutionizing Advertising

I'm serving on an interesting panel October 29th in NY to discuss how targeting data is revolutionizing the concept of “audience buying” and fueling better performance for advertisers. Really good set of panelists with representatives from ad networks, exchanges, advertisers and optimizers! See below (click for larger version).

Sponsored by eXelate and moderated by Forrester Research.

Others Online Acquired by the Rubicon Project

On September 15, 2009, the Rubicon Project announced the acquisition of Others Online, a company I founded in 2006, the 3rd company I've founded, and the 4th startup I've built up.

Others Online was founded on the vision of advertisers being able to reach people, not pages. When I had looked at the revenue growth of Internet advertising revenues from 1997-2007, I noticed two clear growth trends. The first growth trend, from 1997 through 2000 (v1.0), was primarily fueled by content targeting -- Web sites and content were the proxy by which advertisers reached people.

The second growth trend, starting in roughly 2002 (v2.0) was primarily fueled by keyword targeting -- search and context keywords were the proxy by which advertisers reached people.

My belief, and the bet we made with Others Online, was that the evolution of the Web would result in a third growth trend (v3.0) -- the ability for advertisers to reach specific audiences directly, thereby supplanting the use of proxies. Indeed, the industry is seeing tremendous growth in the area of audience targeting. However, the ability to correctly identify specific audiences is dependent on two things:

1. Lots of audience attention data, representing what we're devoting our precious attention span to online.
2. Technology to aggregate, process, score and summarize the audience attention data.

Audience attention data is everywhere. Every online media company has a fragment of attention data, and we've seen a number of companies form in the data space, each offering valuable data for sale to advertisers. Not just "behavioral" data either -- contextual, demographic, purchase intent, location, search keywords, etc. But that's the problem; no one has a complete picture, merely fragments. The true market growth opportunity can't be realized unless/until there's an aggregation point for audience data, coupled with media inventory, and the mechanism by which advertisements can be targeted based on the multiple facets that define us as people, at scale.

Others Online built a powerful technology platform to aggregate, process, score and summarize audience attention data, with services that helped publishers better understand, segment and target audiences. In our discussions with the Rubicon Project, we quickly realized the power of combining their global reach and scale (45B monthly impressions to 500M users, across 30K Web sites) with our technology to not only provide incremental value to everyone connected to the Rubicon Project platform, but also to fuel the next growth trend in audience-targeted online advertising.

As with all announcements though, there are bound to be misconceptions. Though future press releases will certainly add clarification, I thought I'd at least try to dispel a few potential misconceptions upfront!

• This acquisition does NOT make the Rubicon Project a "data exchange". We do not resell publisher or 3rd party data, nor will we. We provide a platform through which 3rd party data providers are developing an incremental distribution and sales channel.
• The Rubicon Project (still) does NOT sell media directly to advertisers. We remain 100% focused on providing value to premium Web publishers, helping them make more money, protect their brand and save time.

The Others Online team couldn't be more excited to be a part of the Rubicon Project. But mostly, we look forward to adding value to their publisher partners and in doing so, hopefully realize the market opportunity at hand.

Google Targeting Ads by Credit Score

Neal forwarded me the MediaPost article "Google Tries Hand At Targeting Consumers With Good Credit" which describes how Google has been testing the ability to lay consumer FICO scores on top of its Google Content Network to identify/target people with good credit. Some interesting takeaways:

• will be offered to Google text and display advertisers.
• partnered with Compete.com and their panel of 2M opt-in users, which means it will not be "explicit" FICO score information but rather paneled data (Web sites which index well for high credit scores). Compete's sister company integrated the FICO data with searches done by participating consumers who applied for a credit card between January and March 2009.
• According to their marketing person, "Google's Content Network can reach 70% of credit card applicants with a high FICO score, 87% of mortgage applicants with a high FICO score, and 90% of the people who visit small business sites who have a high FICO score."
• Consumers with high FICO scores use non-branded search terms more than branded -- approximately 60% of high FICO searchers.

Top Search Advertisers on Google

Interesting stats found this morning at AdQuants, a company that does a lot of SEM analysis. They list the top advertisers for Google, Yahoo and Microsoft by number of advertisements, and by average daily ad spend.

What's most interesting to me is the volume of ad arbitrage revenues Google takes in. I looked at the top 100 advertisers on Google (by daily ad spend) and did a quick SWAG on how much is pure ad arbitrage (they advertise to get traffic, which they monetize thru ads themselves) or affiliate arbitrage (they advertise to get traffic, which they monetize thru affiliate relationships), versus real businesses (United, Nordstrom, HomeDepot, Chase, etc.). Based on this rough analysis, appears that:

• >19% of Google's ad revenues are based on pure ad arbitrage.
• >39% of Google's ad revs are based on affiliate arbitrage.
• Which would mean that the majority of Google's ad revenues are based on arbitrage! For instance, AOL, Yahoo and Ask.com are all in the top 12 advertisers.

Full lists below. And if you click on the links, AdQuants gives you more info.

Current State of Web Privacy, Data Collection, and Information Sharing

Very interesting research report at KnowPrivacy.org on the current state of web privacy, data collection, and information sharing. The project was to compare users' expectations of privacy online and the data collection practices of web sites, identify specific practices that may be harmful or deceptive and attract the attention of government regulators, and to produce recommendations for policymakers.

The key takeaways for me were:

• Users are concerned about data collection online (duh!), want greater control over their personal information, yet lack the awareness or initiative to do anything about it. (I found it interesting that the report seemed to focus on personally-identifiable information (PII) and not distinguish that from non-PII.)
• Web bugs/beacons are ubiquitous.  All of the top 50 websites contained at least one web bug at some point in a one month time period. Some had as many as 100.
• Google is the dominant player in the tracking market; it operates the top three trackers and four of the top 10. Among the top 100 websites this project focused on, Google Analytics appeared on 81 of them. When combined with the other trackers it operates (AdSense, DoubleClick, FriendConnect, etc.), Google was on 92 of the top 100 websites and 348,059 of 393,829 distinct domains reviewed -- that's 88.4% reach across the Web!!
• Most of the top 50 websites collect information about users and use it for customized advertising.

Other various data points and comments I noted:

• The number of user complaints made to the various organizations is extremely low relative to the number of Internet users. The FTC had only 6,713 for five years (in the General Privacy category), the PRC had 2,202 for the same period and the COPP had 1,152. TRUSTe had 7,041 that it categorized as privacy related. The largest numbers of complaints at all four of the institutions we received data from were concerned with public displays of personally-identifiable information.
• Only 23 of the top 50 affirmatively stated that users could have access to some portion of the information the website had collected about them. The remaining 27 policies lacked mention of access or their statements about access were unclear. None of them explicitly offered users the ability to view or delete click stream data.
• The Network Advertising Initiative (NAI) currently has an opt-out mechanism that requires users to download a cookie, which will let direct advertisers know not to install any third-party tracking cookies on the user‘s computer. This method of opt-out is unacceptable. First, it only governs members of the NAI; tracking companies that are not members will still be able to use cookies and web bugs to collect data about users. Second, users that delete cookies on their machine may delete the NAI cookie inadvertently and open up their machine to third-party tracking again.
• Only 27 of the top 100 Web sites provided a P3P policy, and only a subset of those were valid according to the P3P standard.

The final recommendations as a result of the research?

• Regulation by which both websites and third-party trackers must allow users to see all the data that has been collected about them, not just user-provided information. Additionally, users should also be allowed to see with whom their data has been shared.
• That companies request permission from users before sharing data about them with any outside party, regardless of affiliation.
• Privacy policies should be readable for average users.
• Users be given clear and proper notice as to whom the data will be passed, regardless of affiliation or method of sharing.
• That the practice of third-party tracking be made more transparent.
• That the FTC create an opt-in standard for enhancement -- the practice of buying information about users from outside sources.
• That all browser developers provide a Ghostery-like function in their browsers that alerts users to the presence of third-party trackers.