digital ad fraud - bia advisory services...2. 100% of impressions generated between 4a –5a local...

September 2018 / Page 0marketing.scienceconsulting group, inc.

linkedin.com/in/augustinefou

Digital Ad FraudImpact on Local Ad Spend

September 2018Augustine Fou, PhD.acfou [at] mktsci.com 212. 203 .7239

Agenda• What is Ad Fraud?

• How big is the problem?

• Why is it not caught?

• How it affects Local Markets

• What local publishers can do

• What marketers can do

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)

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

1/2Ads 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.

The most profitable criminal activity

2,500 - 4,100% returns

11% returns1% interest

digital ad fraud

stock marketbank interest

“where else can I get multi-thousands percent returns on my money? Right. Nowhere.”

Economics of botnets explained

Source: MIT Tech Review, May 2018

“distributed denial-of-service attacks using a network of 30,000 bots can generate around $26,000 a month. Spam advertising with 10,000 bots generates around $300,000 a month, and bank fraud with 30,000 bots can generate over $18 million per month. But the most profitable undertaking is click fraud, which generates well over $20 million a month of profit.”

Botnets can be used for a variety of things

How Big is Ad Fraud?

Everyone has an opinion…

Ads fraud is “non-existent” – IAB Australia

“Ad fraud is $6.5 billion or 9% of

display ad spend”-- ANA/WhiteOps

“88% - 98% of clicks are generated by

bots”- Oxford Biochron

(2015) 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

(2016) Video ads …

Source: Dec 2016 WhiteOps Discloses Methbot Research

“Methbot, steals $2 billion annualized;

and it avoided detection for years.”

1. Targeted video ad inventory$13 average CPM, 10X higher than display ads

2. Disguised as good publishersPretending to be good publishers to cover tracks

3. Simulated human actionsActively faked clicks, mouse movements, page scrolling

4. Obfuscated data center originsData center bots pretended to be from residential IP addresses

1 botnet eats 15% of video inventory

(2017) mobile app install fraudSource: June 2017, Tune

average 20% fraud

100% fraud

> 50% fraud

Examples of fake sites/apps1221e236c3f8703.com62b70ac32d4614b.coma6f845e6c37b2833148.comda60995df247712.comd869381a42af33b.coma1b1ea8f418ca02ad4e.com1de10ecf04779.com2c0dad36bdb9eb859f0.coma6be07586bc4a7.comfe95a992e6afb.com42eed1a0d9c129.comda6fda11b2b0ba.comafa9bdfa63bf7.com739c49a8c68917.combaa2e174884c9c0460e.comd602196786e42d.com153105c2f9564.com8761f9f83613.com20a840a14a0ef7d6.com31a5610ce3a8a2.com5726303d87522d05.com3ac901bf5793b0fccff.comb014381c95cb.com2137dc12f9d8.com

06f09b1008ae993a5a.comfbfd396918c60838.com97ff623306ff4c26996.comb1f6fe5e3f0c3c8ba6.com23205523023daea6.com6068a17eed25.comb1fe8a95ae27823.comf4906b7c15ba.comeac0823ca94e3c07.com1f7de8569ea97f0614.com21c9a53484951.com24ad89fc2690ed9369.comefd3b86a5fbddda.com34c2f22e9503ace.com0926a687679d337e9d.com6a40194bef976cc.com33ae985c0ea917.com02aa19117f396e9.comf8260adbf8558d6.com9376ec23d50b1.compushedwebnews.coma0675c1160de6c6.com0f461325bf56c3e1b9.com850a54dbd2398a2.com

com.dxnxbgj.mkridqxviiqaogwcom.obugniljhe.fptvznqwhmcjmcom.bpo.ksuhpsdkgvbtlswcom.rlcznwgouw.vvtexstbfttngccom.kasbgf.sbzwtgpcbjexicom.bprlgbl.vbzecom.zka.lzhsoueilocom.alxsavx.mizzucnlbcom.jxknvk.lrwfdfirdzpswcom.tvwvqbt.wbshaguqycom.iwnxtpahcu.leyuehdwdbbcom.okf.rhvemtykfibzpxjcom.obpmirzste.ldsjpvcom.zmm.shmxvjxnsagnduicom.nqzwr.leusrmpmsqcom.rced.zcdsglptpdlwpucom.kerms.ehlsgnccom.cmia.iabhheltmcom.skggynmtx.tyyjnwpefvqtllcom.kgdtltnuv.hayvfhobcom.ztzsiqg.dyojlxdscxwscom.xlwuqe.ddrdhsuosbncom.rkrhmzee.wjcoznxucom.ebhzb.hbzvomzpcctovj

Fake sites Fake sites Fake apps

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)

How do we know it’s fraud / useless?

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)

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

Gross Failures ofFraud Detection Tech

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

Despite fraud detection tech… Obvious fraud still gets through; analyze and fight fraud yourself

Launch Week 3 and beyondWeek 2

Initial baseline measurement

Measurement after first optimization

After turning off more “sites that cheat”

Obvious fraud still gets through

After all flavors of“fraud filters”Obvious fraud still gets through; but we turned off manually early in the campaign

They miss popunders/redirectsThese forms of fraud typically get by current fraud detection tech

Vendor openly selling 125 billion page redirects (pageviews) per month, at low CPMs)

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

They miss mobile app fraud“fraud sites’ traffic comes from apps that load hidden webpages”

Openly selling on LinkedIn

Overall ad fraud > bot %Fraud detection looks for IVT(bots); may miss other forms of fraud

% bot + % site + % mobile fraud

% overall fraud = 23%, not 5%

5% 11% 7%

How Ad Fraud Will Impact Local Ad Spend

Local Media Ad SpendLocal media ad spend to exceed $150 billion in 2018

The digital portion of local ad spend will reach $76 billion in 2021; most of it will be bought and placed programmatically.

Source: BIA/Kelsey

Budgets go to geotargeted ads

Not Normal – in both campaigns1. 100% mobile apps; 100% Android; same top 15 apps in both markets2. 100% of impressions generated between 4a – 5a local time3. 100% fake devices; 15 unique devices generated top 95% impressions4. 100% data center traffic, randomized through residential proxies

How? Mobile emulatorsMobile emulators can simulate actions pass fake sensor data (GPS)

install, launch, interact

Programmatic GeotargetingStudy on programmatic geotargeting shows low quality

Sources: BIA/Kelsey, Marketing Science Consulting Group, September 2017

Local Media – real humansIn contrast, there is a lot more “confirmed humans” in local media

Seattle, WA

San Francisco, CA

Los Angeles, CA

Las Vegas, NV

Bozeman, MT

Denver, CO

Dallas, TX

Houston, TX

Atlanta, GA

Chicago, IL

Miami, FL

Washington, DC

New York, NY

Philadelphia, PA

Boston, MA

Bangor, ME

Consumers Trust Local MediaConsumers who live there trust local media, distrust “any website”

Source: http://www.newsmediaworks.com.au/adtrust/

Local Media vs GeotargetingValue of local media significantly outweighs programmatic

Local Media Geotargeted Programmatic

AudienceLocal human residents

Device-reported location• Fake devices• Fake location• Fake users (bots)

Trust Consumers trust Consumers DIStrust

Fraud Risk Low High

ROI High Low

Ad fraud in OTT?Of course, where there is ad spend, there will be con artists

Real OTT Fake OTT

Real humans watching content

Fake devices generating fake ad inventory

Real ESPN inventory, authenticated devices

Fake Roku inventoryFake Hulu inventoryFake Netflix inventory

Fraud risk - low Fraud risk - high

What Local Publishers should do …

Don’t “source traffic”Sourcing traffic (not digital marketing) exposes you to fraud

Choose Your “Traffic Quality Level”

“Valid traffic” costs more

Local TV websitesGreat consistency in the data over long periods of time

Local radio websitesGreat consistency in the data over long periods of time

Magazine websitesGreat consistency in the data over long periods of time

Filter data centers and botsOn-Site measurement, bots are still coming

In-Ad measurement, bots and data centers filtered

10% red

-7% (filter data

centers, bots)

3% red

What Local Buyers should do …

Measure your campaigns

In-Ad(ad tag)

On-Site(embed code)

Measure

AdsMeasure

ArrivalsMeasure

Conversions

1743 156

more humans (blue)good publishers

On-Site(embed code)

social

nativevideo

display

affiliate

Progressively clean campaignsAnalyze and turn off the fraud yourself

Launch Week 3 and beyondWeek 2

Initial baseline measurement

Measurement after first optimization

After turning off more “sites that cheat”

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.

Display 4

2,036 humanshuman conversion rate

Compare actual outcomesSite Traffic Conversions

8,482 818

4,216 humans

5%human conversion rate

14,539 193

225 humans

2,248 23

168 humans

1,527 9

Display 3

Display 2

Display 1

Humans

“buyer beware”and

“you get what you pay for”

About the Author

September 2018

Augustine Fou, PhD.

acfou [@] mktsci.com

212. 203 .7239

Dr. Augustine Fou – Independent Ad Fraud Researcher

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

Harvard Business Review

Excerpt:

Hunting the Bots

Fou, a prodigy who earned a Ph.D. from MIT at 23, belongs to the generation that witnessed the rise of digital marketers, having crafted his trade at American Express, one of the most successful American consumer brands, and at Omnicom, one of the largest global advertising agencies. Eventually stepping away from corporate life, Fou started his own practice, focusing on digital marketing fraud investigation.

Fou’s experiment proved that fake traffic is unproductive traffic. The fake visitors inflated the traffic statistics but contributed nothing to conversions, which stayed steady even after the traffic plummeted (bottom chart). Fake traffic is generated by “bad-guy bots.” A bot is computer code that runs automated tasks.

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