Bots: How to Find Them &Keep Them Out of Digital Advertising

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Agenda

Setting the StageSpeakers

●Marvin Hidalgo Senior Product Manager, Integral Ad Science

●Vamshi Sriperumbudur VP of Platform Marketing, Yume

●Elizabeth Cowley VP Global Partnerships, Viewster

Open Discussion / Q&A

Marvin HidalgoSenior Product Manager

What Are Bots?

Bots noun \ˈbäts\ a device or piece of software that can execute commands, reply to messages, or perform routine tasks, or problem routine tasks with minimum human intervention

Illegal bots noun \(ˌ)i(l)-ˈlē-gəlˈbäts\ computers that are compromised and whose security defenses have been breached and control conceded to a third party

Botnet: noun \ˈbät net\ a collection of bots communicating with command center in order to perform tasks

Fraud: Why Does It Take Place?

• Supply and Demand

• Because of the way that we buy media:

• Eyeballs (CPM)

• Action Taken (CPC, CPA)

• Because it’s easy for hackers

Who Are the Participants?

Profile

Hacker:

Sex: Male

Age:18-35

Location: Eastern Europe, Asia

Background: good computer skills

Botnet Operator:

Sex: Male

Age: 34+

Location: Eastern Europe

Characteristics: Disregard to law, confident, driven by money

Typical Infected Computer Owner:

Technologically challenged

Owns a dated computer and software

Suburban, rural, household without kids

Unlikely to own a smart phone/tablet

How are Bots Detected ?

First we look at behavioral patterns

We flag the following un-human signals:Cookies that are deleted at the end of activity cycle

Intense activity

Reoccurring activities patterns/levels

At this point: some bots are detected, others are able to go undetected

Next – we look at each impression• Signals that are untypical for human• Density of page loads• Density of page visits• Untypical distribution of browsers• Browser spoofing• Conflicting measurement results• Was the impression traded in a suspicious

way

Cross validate all of the above and determine validity of signals and patterns

Bot

…or not

How do Publisher’s approach Fraud?

Proactive

Passive Pretend the problem

doesn’t exist

Knowingly or unknowingly sell bot traffic

Able to eliminate

some of the bot traffic

Eliminate most to

all bot traffic

Partially address the problem:

• Use a subpar list based solution

• Run the technology only on part

of the inventory

Are serious about fraud:

• Use cutting edge

technology to vet 100% of

inventory

Vamshi SriperumbudurVP of Platform Marketing

Ad Industry | Market Opportunity

2013 2014 2015 2016

$517 $544 $568 $596

$117 $132 $146 $160

Global Ad Spend (in billions)

Total Ad Spend Total Digital Spend

2013 2014 2015 2016

$171 $179 $188 $198

$42 $50 $57 $65

US Ad Spend (in billions)

Total Ad Spend Total Digital Spend

Source: eMarketer, Dec. 2013 & Mar. 2014 reports

Q1 Q2 Q3 Q40%

10%

20%

30%

40%

50%

60%

70%

44% 42%

51%

61%

Q1 Q2 Q3 Q4

19%22%

27% 25%

Ad Industry | Challenges

Non-human Mobile Activity

Non-human Web Activity

2013

Source: Solve Media, Mar. 2014

2013 US Non-human Traffic – Online & Mobile

Challenge: In 2013, non-human Online Activity in US grew 40% & non-human Mobile Activity grew 30%

Solution: Publishers and Advertisers should prioritize investments in anti-fraud technologies

CTV platform needs review

Traffic Quality Solutions

Viewability

Tracking and measuring ad positions on publisher

pages and properties

Fraud Detection

Monitoring of non-human traffic resulting from

traffic fraud designed to manipulate ad-serving

counts

Brand Safety

Consideration of the content quality and

context that appears next to the ad

Solutions | Viewability

At least 50% of the ad is visible on the users screen for at least 1 second

Above the fold

View AreaWidth x Height

Player Width x Height

3 Player Location

3

4 View Area

4

2 Player Size

2

5 No auto-play

5

1 Minimum Player Visibility

1

Solutions | Fraud Detection

1. Diligent evaluation of every publisher before adding to the network to make sure they meet the standards

2. SDK / Process for Placement Quality – Algorithms to grade value of each video ad impression and assign quality score. Fraud detection capabilities to address:

• Click Fraud (bots browse/click on bogus & legit sites)

• Impression Scams (bogus ad requests)• Ad Stacking (stacked muted auto-play ads behind

in-view video ad)• Ad Clutter (multiple ads in close proximity)

3. SDK & Data – Machine learning for mimicking human behavior to downgrade fraudulent inventory

4. SDK & Surveys – First-party audience survey response rate to gauge inventory quality

5. Partnerships with right vendors who specialize in fraud detection

Publisher Site

Domain blacklisted

Player not in view

Safe domain, player in-view

Additionally, review every site/app of a Publisher and their syndication partners: Only click-to-play or user initiated video ad playback No skip button for 15 or 30s ads No muted audio Post-rolls after video content not acceptable

Publisher Syndicated Sites

Solutions | Brand Safety

2 Context

2

1 Content

1

Solutions | YuMe in The Press

“YuMe wants to ensure that there's a human behind every impression. These improvements to our fraud detection system and PQI, combined with our newly-launched anti-spam best practices, will provide an essential layer of comfort for those planning media buys or monetizing ad inventory.”

- Jayant Kadambi, CEO & Co-Founder, YuMe

According to Radar Research, up to 50 percent of all ad impressions are never

seen by the intended audience. Inclusion of unseen impressions in campaign reporting

results in inaccurate metrics.

This industry-first capability allows YuMe to prevent ads from running in video players

that have been embedded on inappropriate websites, and to work with publishers to constantly monitor and improve the list of

sites where their syndicated and user-embeddable players are appearing.

Oct 2013 Nov 2011 Jun 2010

Elizabeth CowleyVP Global Partnerships

What is Viewster?

Founded in 2007 & HQ: Zurich, Switzerland with offices in US, UK, & Australia

VOD Service with focus on TV and Movie content

Available globally in 10 languages on PC and 1M connected devices

# 18 US Video Content Provider by comScore reaching 18M unique visitors/month

Flavors of Bad Traffic

•Non-Human Traffic – bots

•Human but not Viewable Traffic – hidden iFrames“<iframe src=‘http://StealBrandMoney.com style=‘visibility:hidden;position:absolute;left0;top0;’></iframe>”

•Human & Viewable Traffic - Fraudulent Arbitrage

– Browser Plug Ins Spoof URL– In-banner sold as onsite– Multiple Players on same page– Ads run in pop-under pages– Ads auto-start BTF

Buyer is sold…

But gets this

Bad Traffic EcosystemFraudsters sell bad Traffic Because they can – Buyer

metrics are fakable.

Bad traffic hits the market and real publishers with real video [and real associated costs] are forced to compete with fake traffic that has no content cost.

Real publishers look to buy affordable traffic to compete

Bad Traffic enters the marketplace DIRECTLY through exchanges & lower-end adnets. It can then be laundered and sold as premium.INDIRECTLY through legit publishers buying traffic to compete.

Removing Bad Traffic from the Marketplace

Stop Buying It!

Publishers, AdNets and AdExchanges need to stop buying bad traffic.

Brands Can Help Too•Brands should expect to pay a decent price for decent inventory and a high price for premium inventory. •Buyers should consider campaign metrics tied to human activity.

– Increased brand recognition– Increased sales– Hijack device camera to confirm eyeball on ad? [just kidding…]

How to Spot Bad Traffic

• Before Buying– Is the price unreasonably low?– Check Alexa Rank – does the site have real traffic?– Check referring URLs in Alexa – lets you know where the traffic’s traffic is

coming from?– Check against known offenders list

• Run Test Campaign– Manual checks to verify placement– 3rd Party Traffic Verification such as IAS, Adometry or similar– 3rd Party Viewability Tool such as OpenVV

• After Buying– Don’t fall for a bait & switch. Continue to monitor manually and via 3rd party

technologies.

Do not underestimate the value of a relationship between buyer and seller.

Publisher Challenges with 3rd Party Verification Tools

Publisher Traffic

10,000

Variables

GOOD

BAD

Publishers need actionable data not just a verdict of good or bad.

A good step would be if 3rd party verification technologies would work with publishers to determine where their algorithms are producing data useful to buyers and where it is not.

There is no standard for “good” or “viewable” traffic therefore technologies do not agree with one another.

IAB 3MS Initiative“Making Measurement Make Sense” – intended standardize digital media metrics and promote shift from gross “served” impressions to audience-based “viewed” impressions (50% viewable for a minimum of 1 second).

IAB Safe Frame 1.0 InitiativeOpen source iframe code that removes browser-type restrictions on the geometric approach and enables the same level of verification coverage as browser optimization approach.

TOGI Task Force“Traffic of Good Intent” task force created to address bad traffic.

Industry Best Practice Initiatives

Brendan Riordan-ButterworthDirector, Technical Standards

Marvin HidalgoSenior Product Manager

Open Discussion / Q&A

Elizabeth CowleyVP Global Partnerships

Vamshi SriperumbudurVP of Platform Marketing