ExposingInfinite quantities of digital ads can be created on real or fake sites Unlike real...

April 2019 / Page 1marketing.scienceconsulting group, inc.

linkedin.com/in/augustinefou

Exposing Digital Ad Tech

April 2019

Augustine Fou, PhD.

acfou [at] mktsci.com

212. 203 .7239



What is Ad Fraud?



What is digital ad fraud ?

Ad Fraud = ad impressions caused by bots, not seen by humans

Impression Fraud(CPM) Fraud

(includes mobile display, video ads)

Click Fraud(CPC) Fraud

(includes mobile search ads)



Why? Largest buckets of spendLeads

(CPL)

Sales(CPA)

Lead Gen$2.0B

Other$5.0B

• classifieds• sponsorship• rich media

Impressions(CPM/CPV)

Clicks(CPC)

Search 46%Display 31%

Video 14%

91% digital ad spend Source: IAB FY 2017 ReportEstimated >$300B in 2018

9% spend



How bad guys commit ad fraud1. set up

FAKE SITES2. buy

FAKE TRAFFIC3. sell

FAKE ADS



Why is ad fraud bad?

Advertisers Publishers

Bad Guys

1/3

2/3Ads are not shown to humans, wasted

ad dollars

Ad revenue declines because dollars are stolen by bad guys.

Steal money using fake ads; siphon dollars out

of ecosystem.



How Big is Ad Fraud?



(2013) Fake Traffic, Fake Impressions

Source: Adweek, October 2013

https://www.adweek.com/digital/amount-questionable-online-traffic-will-blow-your-mind-153083/



(2015) Fake display ads …Increased CPM prices

by 800%Decreased impression

volume by 92%

Source: http://adexchanger.com/ad-exchange-news/6-months-after-fraud-cleanup-appnexus-shares-effect-on-its-exchange/

260 billion

20 billion

> $1.60

< 20 cents



Methbot, Hyphbot … now 3veVast botnets targeting high-value video ads, disguising/hiding



(2017) Mobile app install fraudSource: October 2018, Tune

average 20% fraud

100% fraud

50% fraud24 billion clicks on 700 mobile networks

https://www.tune.com/blog/mobile-ad-fraud-24-billion-clicks-700-ad-networks-reveals/



(2018) Mobile app, video fraud

Source: Buzzfeed News, Oct 2018 Source: Buzzfeed News, Nov 2018

Source: Buzzfeed News, March 2019

https://www.buzzfeednews.com/article/craigsilverman/how-a-massive-ad-fraud-scheme-exploited-android-phones-to

https://www.buzzfeednews.com/article/craigsilverman/android-apps-cheetah-mobile-kika-kochava-ad-fraud

https://www.buzzfeednews.com/article/craigsilverman/in-banner-video-ad-fraud



Ad fraud is at all-time highsThere’s $100B in digital ad spend to steal from, year after year

U.S. Digital Ad Spend($ billions)

Actuals Projected

Digital Ad Fraud($ billions)

($300B worldwide)



Why isn’t it detected?



Bad guys easily avoid detectionBlocking of tags, altering measurement to avoid detection

Detection Tag Blocking — analytics tags/fraud detection tags are accidentally blocked or maliciously stripped out

“malicious code manipulated data to ensure that otherwise unviewable ads showed up in measurement systems as valid impressions, which resulted in payment being made for the ad.”

Source: Buzzfeed, March 2018

https://www.buzzfeed.com/craigsilverman/newsweek-ibt-malicious-code-ad-fraud



Traffic sellers’ “high quality traffic”Many sources to buy “traffic,” tune “quality” level, host bots

Google “buy real human traffic”

Select vendor and“traffic quality level”

Host your own bots(cost $3.99/mo)



(2017) Pop-Unders / RedirectsThese forms of fraud typically get by current fraud detection tech

a.k.a. “zero-click” “pop-under” “forced-view” “auto-nav”

Source: https://www.buzzfeed.com/craigsilverman/remember-tom

https://www.buzzfeed.com/craigsilverman/remember-tom



Fraud type: Apps load webpages“fraud sites’ traffic comes from apps that load hidden webpages”

Openly selling on LinkedIn



Just because you can’t measure it…

… doesn’t mean it’s not there.



Ad Tech Gave Rise to Ad Fraud



Adtech middlemen maximizing profits

PublishersAdvertisersHuman

Audience

AdvertisersPublishers

HumanAudience

Fake UsersFake Sites

1995

2015



Adtech Tax: 60-70% extracted

Source: WFA, April 2017

Source: ANA, May 2017

https://www.wfanet.org/app/uploads/2017/04/WFA_Compendium_Of_Ad_Fraud_Knowledge.pdf

http://www.ana.net/miccontent/show/id/ii-programmatic-financial-fog



Case examples of this …Publisher only gets 30-60c on the dollar after middlemen fees

https://mediatel.co.uk/newsline/2016/10/04/where-did-the-money-go-guardian-buys-its-own-ad-inventory

2016 The Guardian

“for every pound an advertiser spends programmatically on the Guardian only 30 pence actually goes to the publisher.”

2017 BusinessInsider

“$40,000 worth of ad inventory through the open exchanges, the publication only saw $97.”

http://adage.com/article/digital/business-insider-york-times-shed-details-ad-industry-s-biggest-problem/311081/



Scarcity … vs unlimited fake sites/adsInfinite quantities of digital ads can be created on real or fake sites

Unlike real billboards that people actually drive by in the physical world …

Limitless quantities of digital ads can be created on fake sites that humans never visit.



Myth of the long tailMost people visit sites they know most; occasionally long tail ones

“There are numerous pieces of research on how even as people accumulate hundreds of TV channels, they only watch seven. It's rather commonly accepted that in a sea of millions of mobile apps, most people stick to half a dozen.” http://www.businessinsider.com/the-advertising-industry-has-been-living-a-lie-2017-10



Myth of HypertargetingAfter 3 parameters, the matching audience gets really tiny

Female Male

18-25 13-17 25-34 35-49 50+

1. gender

2. age range

3. geographic location

50%

10%

2%

100 params?

300 params?

Starting Audience 100%

?

?

% of AudienceTargeting parameters



Myth of behavioral targetingAd tech sold the idea of deriving intent from web history

Outdoor enthusiast?Male? Female?

“This works on simplistic examples, like the above. But when the list of sites grows longer and more diverse, the assumptions used to derive data points, even gender, are going to be less and less accurate. In fact, a recent study of online identifiers determined that over 80% of the records were designated as BOTH male and female.”

Source: Yeah, Your Data’s Screwed

https://www.linkedin.com/pulse/yeah-your-data-screwed-cybersecurity-ad-fraud-researcher/



Some think ad fraud is already solved



We only pay for viewable and fraud freeBad guys used malicious code or nefarious techniques to trick viewability measurements

“malicious code manipulated data to ensure that otherwise unviewable ads showed up in measurement systems as valid impressions, which resulted in payment being made for the ad.”

Source: Buzzfeed, March 2018

AD

Bad guys cheat by stacking all ads above the fold to fake 100% viewability

https://www.buzzfeed.com/craigsilverman/newsweek-ibt-malicious-code-ad-fraud



We optimize for engagement, click ratesDetailed reports by domain reveal obvious fraud – 100% click through rates on ads

Where to find this?Your campaign reports, with details by domain.

What to look for?If click-thru rates are 100%, something is wrong; be sure to ignore low volume rows.

What to do?Identify the sites that exhibit these abnormal click-thru rates and turn them off in the campaign interface – don’t buy the fraud any more.



We only pay for performance, leads, salesLarge data breaches aggregated data on millions of individuals; used to create fake leads

Fake leads

• Previously filled out by hand

• Now, fully automated with bots using databases of real postal addresses, etc. (that trick verification engines)



Chase: -99% reach, no impact

“JPMorgan had already decided last year to oversee its own programmatic buying operation.

Advertisements for JPMorgan Chase were appearing on about 400,000 websites a month. [But] only 12,000, or 3 percent, led to activity beyond an impression.

[Then, Chase] limited its display ads to about 5,000 websites. We haven’t seen any deterioration on our performance metrics,” Ms. Lemkau said.”

“99% reduction in ‘reach’ … Same Results.”

Source: NYTimes, March 29, 2017

(because it wasn’t real, human reach)

https://www.nytimes.com/2017/03/29/business/chase-ads-youtube-fake-news-offensive-videos.html



P&G: cut $200M, no impact

“Once we got transparency, it illuminated what reality was,” said Mr. Pritchard. P&G then took matters into its owns hands and voted with its dollars, he said.”

“As we all chased the Holy Grail of digital, self-included, we were relinquishing too much control—blinded by shiny objects, overwhelmed by big data, and ceding power to algorithms,” Mr. Pritchard said.

Source: WSJ, March 2018

https://www.wsj.com/articles/p-g-slashed-digital-ad-spending-by-another-100-million-1519915621



How marketers are fighting ad fraud



Ad serving volume by hourWith hourly detail, you see most ads are blown out before 4 am



Abnormal consistency in analyticsWhen analytics are TOO consistent, something is suspicious

top 4 referring sites – exact same pattern



Zero conversion sourcesZero conversions, no change when turned off; not worth spending

102,231 sessions

0 sessions

goal event – no change



Progressively clean campaignsObvious fraud still gets through; analyze and turn off the fraud

Launch Week 3 and beyondWeek 2

Initial baseline measurement

Measurement after first optimization

After turning off more “sites that cheat”

30% bots

15% bots3% bots



Shift budgets to higher qualitySome channels have more humans, shift budget to these

• Blue means humans• Red means bots

Where to find this?Your own bots versus humans measurement, with detailed and complete supporting data.

What to look for?Be sure to measure for both bots and humans; rank order channels, sources, or sites by highest humans first.

What to do?Some channels have more humans (blue) and others have more bots (red); shift budgets during campaign to more human channels.



Better media = better outcomesMeasure

AdsMeasure

ArrivalsMeasure

Conversions

346

1743

5

156

A

B

30X more human conversion events

• More arrivals• Better quality

more humans (blue)good publishers

low-cost media, ad exchanges



Low CPMs - “You get what you pay for”

Low CPM sources result in higher cost per human –like 11X the cost.

Sources of different quality send widely different amounts of humans to landing pages.



“Humans visit Montana, bots don’t!”



UTAH TRIP SAMPLE 1 – DRIVING FROM NEVADA



When should you have media in flight?

• Target all U.S., heavy up reach & frequency

vs.• Target NY 90 days out

and Nevada 7 days out

80 – 90days

7 – 10days

Days-to-Arrival = Marketing Window



Miami Hotel – Visitation DashboardWhere did they come from? How long did they stay?

In-StateAvg. Length

of Stay In Miami Out-of-State

10.8% 89.2% 2 days, 23 hours

Visitation by State

6.4%

7.7%

13.8%

6.0%

11.3%2 days, 21

hours

2 days, 23 hours

3 days, 9 hours

1 day, 22 hours

3 days, 8 hours

GA

TX

NJ

FL

NY

Avg. Time spent

Average 3 Nights Average 1 Night



Recap

• Better to assume that digital ad fraud is impacting your campaigns, than not

• Ask for detailed reports; look at your own analytics, so you can investigate anything that looks suspicious

• Avoid quantity metrics that are easily faked; choose conversion metrics that are reliable and not faked by bots



About the Author

Augustine Fou, PhD.

acfou [@] mktsci.com

212. 203 .7239

mailto:[email protected]



Dr. Augustine Fou – Researcher

2013

2014

Published slide decks and posts:http://www.slideshare.net/augustinefou/presentationshttps://www.linkedin.com/today/author/augustinefou

2016

2015

2017

20192018

http://www.slideshare.net/augustinefou/presentations

https://www.linkedin.com/today/author/augustinefou

ExposingInfinite quantities of digital ads can be created on real or fake sites Unlike real...

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