As my former colleague and advisor, Jerry Neumann says - there is no starting gun. Go and start a company now. It’s not as hard to get started as you think, and there is no such thing as failure.

A few books I’ve read recently (and some not so recently) about randomness, probability, human behavior, ALL of which are worth looking at:

Fooled by Randomness by Nicholas Taleb. Instant classic, the followup Black Swan is great too but this is better IMO.

The Drunkard’s Walk: How Randomness Rules Our Lives by Leonard  Mlodinow. Great stuff, some great examples and overall I enjoyed it very much - good lay pieces on probability and misunderstandings around that.

Here are some others I recommend highly:

Predictably Irrational:The Hidden Forces That Shape Our Decisions

Mistakes Were Made (But Not by Me): Why We Justify Foolish Beliefs, Bad Decisions, and Hurtful Acts
Traffic: Why We Drive the Way We Do (and What It Says About Us)

Awesome stuff, all.

Yikes - another newspaper site getting a bit discombobulated. This is what the Washington Post looks like today after Siemens got a hold of it…. this was in IE. Firefox looked similar so not a browser-specific issue.

Great piece by Jay Weintraub borders on rant but makes very good points as he lets rip on Google. Alas it is true but there is a lot to criticize.

Anytime I or any individual criticizes Google, it requires a delicate balance, because a single voice against an established system always struggles not to sound like whiny and scorned. When a system becomes ingrained and accepted, dissenting voices get marginalized and those with dissent often relegated to the same category as conspiracy theorists.

As Jay points out, Google still doesn’t get advertising, despite hype to the contrary and billions in revenue. But that as they say, is a story for another day.

Well someone screwed up. It happens, and goodness knows perhaps this might actually increase the response rates on your ads — but probably not. If anyone at Starwood wants to know why this ad is not working that well, it’s either the fault of:

a) The Chicago Sun-Times team, or

b) Whoever trafficks their ads, or

c) Advertising.com, the ad network who ran this ad on the page, or

d) The agency who Starwood is having run their ads (dunno who that is), or

e) Someone at Starwood trafficked it incorrectly…?

In any event - what you have is a 160×600 showing up in a 728×90 spot, and showing just enough skin for you to know it’s an ad for Westin. The URL it clicks through to (yes that does work) is http://www.starwoodpromos.com/westin-mastercard/&EM=Q3Q4_NAD_MEDIA_WS_EN_MASTERCARD

I don’t have a lot of readers, but I’d love to see the comments about where this actually got screwed up

I just got a message on LinkedIn literally four years to the day after someone I thought I went to high school with joined the high school LinkedIn group we had set up. It was coincidentally during the time I used to work at LinkedIn. His message now says he doesn’t know who I am. He is in the Netherlands and I went to high school in South Africa.

It only took four years for him to reply - I wonder if he would have known me four years ago but doesn’t now? Or if he is totally the wrong person and per chance he applied to join our group? Weird stuff.

I was traveling last week and hadn’t yet had time to respond to the data from this study (note: need to submit info, or see copy of it uploaded at http://bit.ly/adxpose) (here is the press release) put out by Radar Research and Mpire. Mpire runs the AdXpose service which gives companies information about where their ads are running and how many users are engaging with them (mousing over, spending time on the page etc.). I like their service and (full disclosure) we were one of the companies who beta-tested the product and have been paying users, using it as one of several tools we use to check on traffic quality.

Another disclaimer is that I used to work with the analysts at Radar Research (we were colleagues at Jupiter Research) and think they are good - and I would not hesitate to recommend them. In this case, however, even though they did a nice job of putting together the data that there is, I think that the underlying data and the methodology of the study has some problematic issues that are worth discussing.

My company is also being pretty proactive on a number of fronts in helping track down and combat impressions and click fraud in the exchange environment. Because it is an interconnected marketplace and we work with lots of ad networks, publishers and advertisers, we’ve shared data with any networks where we have found issues even if those issues don’t affect a revenue relationship between the two of us, and in some cases they have been able to share data back that has helped us confirm that certain cases that touch several networks come down to a very small number of bad actors. Sometimes pieces like this can blow some of the issues that there are out of proportion in terms of scale. And that is the problem I have with this study.

The problems mostly come about from the way I infer the traffic was run in the campaigns (infer since the full details are not provided, and I have an email in to the Mpire team and the Radar folks to get some more information and will update here if there is anything new to add).

My eye was caught by the sensational headline that “more than half of the impressions delivered and 95% of clicks came from suspected fraudulent sources”. Here is why that is not true (or at least, not representative):

CPC and CPA-targeted campaigns - attracting the worst traffic: This is the biggest and fatal flaw. At first we had assumed that this study had been done by running exchange campaigns that were CPM in nature, that would give the broadest overview of the traffic among the various sources. If we assume an average CPM of $0.50 for the traffic, that would be about $10,000 for a test. Apparently that cost is a bit too much. While the methodology in the report is a little hard to pin down, we did notice in the report where it stated (bold added by me):

Mpire also conducted a test directly on a top ten ad network, with the goal of proving the power of referrer and fraud data to unlock the hidden value of horizontal networks. The impressions were bought on a CPM-basis, rather than on a CPC or CPA basis. The results were revealing. While a large percentage (50%) of the impressions were never within view of a user, the click/impression fraud volume, while substantial, was significantly lower than on the exchange based buys.

So this seems to imply that the exchange buys mentioned above it in the report were NOT done on a CPM basis, but were done on a CPC or CPA basis. Why is this important? Well firstly while they don’t mention the Right Media exchange as the source it is probably fair to believe that it is. The optimization system that RMX uses helps campaigns seek out the sites and areas that will best meet their goals. If you create campaigns that have CPC targets, you are essentially telling the system to seek out the sites that have the highest clickthrough rates. If you are looking for but not getting conversions, the system will guess (usually correctly) that sites that have higher CTRs have a higher chance of generating conversions for you. For the publisher side, if they have inventory that is getting a high CTR and running a CPC campaign, it will have a higher effective CPM and thus get more of a share of it’s traffic. On the other hand a CPM or dynamic (ceiling bid) CPM campaign may be optimized towards a CPA but will not reward sites excessively based on CTRs if those clicks fail to deliver conversions.

The message here - your campaign setup may lead you to create a “click magnet” that has no countervailing balance that is created by seeking conversions. Especially if your campaign is small and tuned to clicks only (see next point), you will end up not seeking out conversions and exacerbating the effect of any bad sites in the mix since the system will seek those out and “optimize” based on them! Smart buyers in exchanges understand these effects and steer clear of campaign setups that will seek out these issues. Certainly, you shouldn’t create an experiment and call it representative of the marketplace when your experiment by design will seek out the very thing you are looking to measure. Unless you set up a campaign in a completely typical manner (which would probably be dynamic CPM with a CPA target, of a large enough size to actually get some conversions). A better but less sensational headline might be “Beware of setting up CPC-targeted campaigns because they find lower CPCs which may not be 100% valid clicks”, but jeez that’s way too clunky.

Finally on this point, note that in creating a CPC or CPA targeted campaign you are perforce likely getting the worst/bottom of the barrel traffic, including very high-frequency impressions (20+ impressions in a user session). Anything that could be sold at a higher CPM rate has been, and whatever is left is the stuff that the network/exchange has deemed to have a fairly low value. This is the other half of the self-fulfilling prophecy of seeking out the worst possible traffic imaginable and then calling it bad. It’s like gluing together the leftover wood scraps that have fallen on the furniture-maker’s floor then getting upset when the thing you made looks like it was made out of leftover wood scraps.

Campaign sizes matter, unless you’re not tracking conversions anyway:  The exact split per campaign is not there in the report, but 20 million impressions over 53 different advertisers is not that much per campaign/advertiser. Again, depending on how the campaigns were set up, there may not be enough data for individual advertiser campaigns to be able to optimize on conversions (in fact I’d go out on a limb and say there seems not to be much if any discussion about conversions and it doesn’t really appear that these were even being tracked for this test - setting up 53 conversion pixels is time-consuming, even tougher if you are running affiliate campaigns which would most often be the case in a test of traffic quality for someone to not offend an advertiser). Another potential bias that means the conditions are unlikely to reflect a real-world campaign at all.

(Begging the question just a bit) What counts as fraud?: Many media buyers look for high clickthrough rates with little or no conversions as indicative of fraud. We have, however, seen sites that are able to sustain high clickthrough rates that are not fraud. Recently we saw a site we had flagged that had a 3.3% clickthrough rate. Turns out upon investigation, they were smartly using interstitials and ad overlays on top of content and actually had a lowish but okay conversion rate on conversion campaigns. A few good sites we have worked with have 2%+ CTRs routinely and generate $6+ CPMs running CPA campaigns based on actual conversions they are getting on campaigns. It might be a good idea here to normalize the data (e.g use a median and not an average) so that the data are not overly skewed by sites that have excessively-high CTRs.  I directionally agree that high CTRs are indicative of fraud, but to wrap a headline around 95% of clicks coming from suspected fraudulent sources given this and the above points is a bit disingenuous.

So, a lot of flaws (more but I have not more time). Adxpose (Mpire) should be applauded for working on these issues. That’s a reason we support the product and we are happy to offer it to our clients as well if they want to test our media buys for them or any other ones they are doing. But to claim that this still-somewhat-murkily-setup study offers a representative blueprint of the state of the online ad network or exchange business and the prevalence of clickfraud or impressions fraud is ludicrous and may upon further study actually hurt the efforts many of us are working on to improve the industry. We should NOT, however, let this knock us off the target of stopping fraud, and making improvements for advertisers. That is our entire mission at CPM Advisors after all. But also, I feel that over-sensationalizing something that has a questionable methodology is not the way to go either.

I was a bit surprised to see this ad on the New York Times.

It leads to a page on something called WebAnswersBeta.com - looks like a fake answers site (note the fake breadcrumbs). Electronic cigarettes are something fairly new that is now getting a fair bit of promotion online. Was just odd to see this on NY Times.

I run a startup that has been building online ad optimization tools, a self-service ad buying system, integrating with various exchanges etc. etc. – there’s a lot going on! But amidst all of the excitement and goings on in the display advertising industry, it does appear that one particular constituency is taking a back seat and is little-discussed: the consumer.

I’ll spend some time on this blog talking about what the user wants, but in the meantime let’s see what the “ad industry” thinks the government thinks the user wants…

The AAAA, IAB, ANA, DMA and BBB (whew!) all came together and in July announced

“self-regulatory principles to protect consumer privacy in ad-supported interactive media that will require advertisers and Web sites to clearly inform consumers about data collection practices and enable them to exercise control over that information.”

So they came up with some principles; the implementation of which I don’t believe has really been delved into much detail just yet. Here they are (descriptions paraphrased):

• Education Principle: educate individuals and businesses about online behavioral advertising. Intention to run 500 million impressions over 18 months to explain this stuff to consumers.
• Transparency Principle: clearer, more accessible disclosures to consumers about data collection and use practices of behavioral advertising. New, enhanced notice “on the page where data is collected through links embedded in or around
• Consumer Control Principle: provides expanded ability to choose whether data is collected and used for online behavioral advertising purposes. This choice will be available through a link from the notice provided on the Web page where data is collected. Requires “service providers”, (includes Internet access service providers and providers of desktop applications software such as Web browser “tool bars” to obtain the consent of users before engaging in online behavioral advertising), and take steps to de-identify the data used for such purposes.
• Data Security Principle: reasonable security and limited retention of data, collected and used for online behavioral advertising purposes.
• The Material Changes Principle calls on organizations to obtain consent for any material change to their online behavioral advertising data collection and use policies and practices to data collected prior to such change.
• The Sensitive Data Principle requires parental consent for behavioral advertising to children and heightened protections to certain attributable health and financial data.
• The Accountability Principle calls for development of programs to further advance these Principles, report uncorrected non-compliance with these Principles to appropriate government agencies. The CBBB and DMA have been asked and agreed to work cooperatively to establish accountability mechanisms under the Principles.

A few thoughts here:

Education: It’s hard to explain behavioral targeting to people in the online marketing industry. At a recent conference I spoke at, I had the same conversation explaining retargeting to smart marketers who all did a lot of search and not so much display. What are we going to say to consumers to explain how this stuff works? How will saying what it is affect what consumers do about it? In my past life as an analyst for Jupiter and Nielsen NetRatings, I’ve seen the wide disparity between what people say they will do and what they actually do. 500 million impressions over 18 months? Average clickthrough rates on display ads are around 0.1 percent – let’s be generous and say that 10 times that number pay any kind of attention to these impressions and click on them (though I’m guessing these will be late-session impressions of lower value than the average). We’ll end up with 5 million users learning more about what is going on, over 18 months – or about 3.333 million users per year. Better than nothing? Yes, but not by much.

Transparency: This is a big one. Enhanced disclosure on the page where the data is gathered. Let’s look at the major sources of where data comes from:

• Publishers: A person lands on a web site and perhaps does something and is put into a behavioral bucket. There are more in-depth uses of data that occur when some sites take user registration information and use that to put a user into an audience bucket. The PII data doesn’t persist in the network per se, but it is there.

• Advertising campaigns: a user clicks on an ad and the ad network often flags that as interest of a user in a particular category. The data gathering happens within the entity who is serving the ad, and there is typically no communication channel between the entity and the consumer since they are directing the ad click to an advertiser’s page

• Advertisers: retargeting, typically for other advertiser campaigns. Really a subset of publishers, above.

Putting notice on the page where the data gathering is happening is going to be very difficult. It’s going to be much easier to enforce and to provide a fair trade-off to the user to ask them at the point at which the data is used…. So for example, I visit a site about baseball as I do every day (I don’t like baseball at all, for anyone keeping score at home BTW) and at some point later on I see an advertisement for baseball tickets for an upcoming game in my area. I would also see a little moniker attached on the bottom right corner of the ad with a question mark that I could click on to expand and see why this ad had targeted me specifically. It would then have an easy link for me to 1) opt-out of this instance of data use, 2) opt-out from the provider(s) involved and/or to 3) opt-out completely from the whole damn lot assuming I hadn’t already in which case I would not have seen this ad in the first place.

If we really want change we should have incremental steps. Data notice and choice at the point of use in the online display world, when combined with better policing of how and where data goes to in the middle in an industry-managed solution is the cheapest, least innovation-stifling and most effective way to get past the “of course I care about privacy” nonsense (everyone cares about it, but it’s not an interesting question unless you get specific) where someone has absolutely no context for knowing if that data is going to be of help to them.

I’ve been stuck in this world before as a research analyst trying to reconcile what consumers say they want vs. what they do (I spoke at an FTC workshop about this back in 2002 – here is some data that I presented then that is still quite relevant I think.

I encourage further discussion here as this market changes and develops, and hope to outline more of the consumer angle in coming posts.

It’s a sick thing to call a hobby, I guess it’s really more of a pastime that I can’t stop doing even when I’m surfing the Web not for work (online advertising). And that’s to be on the look out for PSA’s, or public service ads, or any other type of advertising anomaly.

For the uninitiated, a PSA is something that is served typically when an adserver has nothing else to show - usually it is a mistake since the person who is called on to serve the ad impression has typically paid for that ad and having to show a PSA means they are wasting money since PSAs are, by definition, free and unpaid.

I saw this on IMDB (owned by Amazon) - it looks like not only are they showing a PSA in this ad spot, but it’s showing the wrong size ad in this spot. Double mistake - and looks like the network serving it is Turn due to the image call being from http://img.turn.com/img/server/ads/ps/300×250.jpg (click to expand)