Uncommon Sense for Ad Tech Download

UNCOMMON

SENSE

FOR AD TECH

DHAR METHOD

SHAILIN DHAR

FOREWORD I read the trade publications of advertising for years and grew frustrated with the lack of awareness and initiative when it came to ad-fraud. Everyone wanted to be a victim of it rather than address it head on with real intention to eliminate it. I will never call anyone out in my seminars or in writing, I don’t believe in that. I just want people to wake up and be curious about why things are the way they are. There is a Warren Buffet quote that goes something like: “Criticize by catego-ry, praise by name.” That’s the doctrine I am following.

This book is essentially a series of rants about different topics in digital advertis-ing. Those close to me have had to listen to me rambling about these things for years now.

I want to thank John Drake for being the person who inspired the idea of putting my rants on paper and into a collected series. Upon his suggestion, I reread Com-mon Sense, by Thomas Paine on a flight from Seattle to San Francisco. This is what pushed me to finally start writing things down.

I need to thank Matthew Wood who helped me tone down my rants to more palatable language and also for being a mentor in how to share my perspective about the industry with people.

Lucas Reller was instrumental in the actual creation of this project by working on concepts with me, doing the design work and not getting too bored having to look at concepts that he already knows.

My brother Sachin deserves credit for never letting me get lazy. My dad, Sanjay Dhar, was my guinea pig for testing out different methods of explanation.

Oh and I love you Ma.

My hope is that people that have anything to do with advertising use this book to add to their perspectives on online media. The intention of these writings is to help expose people who spend time or money in online advertising to the sort of underground concepts in the industry.

Feedback is always welcome. I love talking Ad Tech. Reach out and let me know what you think. I’ll just be grateful that you read this book in the first place.

Shailin Dhar

TABLE OF CONTENTS

Introduction

Buying Traffic

Financial Incentives

Tech Tax

Programmatic

Arbitrage

Toolbar Traffic

Ad-Block

Botnets & Bot Farms

Current State of Ad Tech

Action Items

What can Publishers do?

What can Brands do?

What can Agencies do?

What can Exchanges do?

What can fraud-detection companies do?

Conclusions and Contact

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INTRODUCTION

1

The business of Ad Tech is different from any other because of the

commodity it involves; especially now with programmatic becoming

the major factor in digital ad-buys.

Automated advertising invites, as well as eliminates, a multitude of

problems and as a result, the industry has been on fire discussing and

arguing what needs to be done and how to prevent one of the biggest

problems of all, ad fraud.

Here are the type of headlines we see all too frequently:

“$11 Billion of fraud plagues advertiser budgets in 2014 - 40% of digi-

tal ad budgets spent on non-human traffic”

“Publishers lose $15 Billion in potential revenue to fraudulent play-

ers.”

We all need to take a deep, deep, deep breath…hold it…

and now exhale.

STOP trying to think of the problems and solutions that are affecting

us as black and white scenarios. Let's think critically and think how we

are taught as kids: Think Outside The Box.

My favorite quote of all time about this industry is this:

"Here’s the thing — online ad impressions are

more like snowflakes than stocks: no two are

exactly alike, and they melt."

- George John (Former CEO of RocketFuel)1

DHAR METHOD

INTRODUCTION UNCOMMON SENSE FOR AD TECH

I believe this is the most insightful single sentence about digital adver-

tising (and programmatic in particular) to date. It not only acknowl-

edges the concept of a disappearing commodity but embraces it. This

is where my main concern with how programmatic media is ap-

proached by thoughtful business minds. Most approaches and philos-

ophies refuse to incorporate the basic premise that the "good" or

"commodity" of digital ad space is finite in nature. The actual life-span

is sometimes a fraction of a second.

The other basic business philosophy that has resulted is the concept

of infinite growth. Unrealistic business goals that are agnostic of how

the digital publisher business really operates have created a need for

what is often called "audience acquisition," "audience extension" and

“buying traffic.” Expecting a digital publisher to have 30%, 20%, or

even 10% revenue growth year over year is not entirely feasible.

Note: I indicate revenue growth, not audience growth (or other

growth metrics such as time spent, engagement, etc.)

The need for high growth rates for content websites led to a need for

traffic providers to exist in the market. These providers generally sell

PPC/CPC traffic to websites to help increase the number of "visitors"

to a site. Buyers of the traffic are able to specify geo (generally coun-

try but can even get as granular as metropolitan area), browser, OS,

and even device they want the traffic to come from. These traffic pro-

viders have been around as long as scaled ad supported websites;

since the late 1990s.


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In an all too typical model, a CRO sets financial goals, which are

passed down to the Head of Operations, who passes it down to their

ad operations team. One person on the ad-ops team tells their man-

ager that they can double their audience this year for a mere $1000/

month. Now the pats on the backs start going around and nobody is

truly concerned with where the traffic came from. And NOBODY is

going to go give back all the additional ad revenue once they find out

that the traffic they bought might not be the cleanest.

Unsurprisingly, when a provider is charging $0.01-$0.05 per new user

to the site, a lot of the PPC/CPC traffic is not real humans. In the be-

ginning, these bots or "fake users" were very basic in their behavior

and operation. As the detection of bots and process of verifying a real

user has become more and more complex, so has the behavior of the

bots. And why wouldn't they get more advanced? They have every

financial incentive to do so.

A lot of the rhetoric to describe bot traffic and the perpetrators of

non-human traffic portrays them as malicious, "cyber criminals,"

hackers, or bad actors.

I personally know several of these people, and many are upstanding

citizens, great family men, loving mothers, and educated profession-

als. None of them individually feels responsible for a headline like:

"IAB estimates $8.2 Billion of ad-fraud to affect advertising industry in

2015."


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Also, they know that any financial harm is being borne by big corpora-

tions like GM, Walmart, Rolex, Toyota, or Coca-Cola that "can probably

afford it."

This leads into another one of my favorite quotes:

"No snowflake in an avalanche ever feels re-

sponsible."

- Stanislaw Jerzy Lec

This certainly can apply to society at large, but it fits well into this com-

mentary since we're already talking about "snowflakes." Each person

involved in the bot traffic space does not feel, nor necessarily bear, the

full responsibility for the problems this causes.

To really understand the core of the problem, take a look at the finan-

cial incentives; profit margins of 100%+ are the norm. A reasonable

operator can spend $1 to return $3. Few businesses see numbers like

that. At what point would someone give up potential pay-offs like that

to make sure they do not compromise what is seen as a moral grey

area? I call it a grey area since there is nothing (currently) illegal about

what is being done. The laws behind what defines a "user" have not

been clearly written yet, nor do the majority of insertion orders explic-

itly prohibit purchased bot traffic.


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So how should we all combat ad-fraud right now? There are many bot

-detection companies that scan a publisher's traffic and provide data

on what is human, and what is not. These companies are run by bril-

liant tech minds and diligent engineers. Ultimately however, these are

for-profit businesses. They have a financial incentive in the existence

of fraudulent traffic. Morally, the company should be ecstatic if all the

bot activity disappeared. But if the percentage of bot traffic on the

Internet drops to < 1%, how many people will continue shelling out

$15,000 per month to ensure their not buying bad ad-space?

My prediction is: Very few.

Similarly, anti-virus software continues to flourish because viruses

continue to exist.

To conclude, we ALL must start approaching these problems with a

different mindset. We cannot fight technology with technology exclu-

sively. People armed with both technology and knowledge will prevail.

A true, comprehensive understanding of how the economy of the

internet is set up will allow us to analyze and then eliminate the prob-

lems of fraud that plague the digital advertising ecosystem.

Knowledge is power.

Let's all be powerful together.

BUYING TRAFFIC

Who buys web traffic? Why do they buy it?

The majority of purchased web traffic is bought by publishers ranging

from small to multi-million dollar companies. That might sound surpris-

ing but lets think about the numbers.

If you are a publisher with an audience of 2 million people and you

generate $10M yearly in ad-revenue and subscriptions together. By

spending $10,000/month on additional traffic at $0.01 CPC, that is an

additional 1 million "users" visiting your site every month. Assuming

you're buying back the same audience or same type of audience each

month, you've increased your audience from 2 million to 3 million by

spending $120K/year. If the same proportional increase happens in

revenue generation, your company has gone from $10M to $15M in

yearly sales.

Lets isolate those numbers: $120K in investment resulted in $5M in

gains. Why wouldn't you do that?

This model is what resulted from years of direct sales by big publishers

who would get ad-buys from agencies because of the demographics of

their audience.

Let's look at a different scenario.

If you are the same publisher with an audience of 2 million readers,

and you average 1M ad-impressions per day. You have ad-buys from

agencies that have already booked 850K impressions per day, leaving

you with 150K unsold.

Now an agency comes to you with a campaign that requires 500K im-

pressions per day. Do you turn it down? Do you tell them "Oops, sorry.

We only have 150K available." No, most likely you'll say yes and then

find a way to fill that Insertion Order.

6 DHAR METHOD

BUYING TRAFFIC UNCOMMON SENSE FOR AD TECH

There are two ways you can fill this IO, add 350K impressions worth of

traffic to your site for the flight dates of the campaign, or engage in

what people kindly refer to as "audience extension."

To add 350K impressions per day, you need to buy at most 100,000

clicks, which at $0.01 CPC, will only cost $1000/day.

For that 500,000 impressions/day campaign, let's take a minimal CPM

rate the agency is paying of $5 CPM.

That $1000 of spend is allowing you to fulfill a $2500/day in spend

campaign that you previously could not have filled.

Now Audience Extension is a different story. As someone who started

in this industry when programmatic had already become a big player in

the industry, this is bizarre to me that anybody was okay with this;

ever. Audience Extension is the concept that if a publisher like

www.americaninvestmentadvice.com with an upper-middle class male

audience, to help fulfill insertion orders from agencies, can go out and

buy impressions on 50 small sites with similar upper-middle class male

audiences for cheap and sell those impressions at the rate of Ameri-

canInvestmentAdvice. This is essentially arbitrage; buy low and sell

high.

In terms of the campaign goals, they are still being achieved because

the advertiser's target audience is still being reached.

Now what is wrong with this picture? The issue is the implications of

this model where now those small publishers have a financial incentive

to have more inventory available for AmericanInvestmentAdvice to

buy up. So they start buying up cheap CPC traffic to make sure that

they become the preferred partner of AmericanInvestmentAdvice

when it comes to helping them fulfill their buyer requirements. It’s a

heavy downward spiral in terms of the integrity of the ad-campaigns.


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How do they buy it? Who do they buy it from?

If you want to be completely shocked by how freely available cheap

CPC traffic is, search the terms "PPC" or "CPC" on LinkedIn or even a

search engine and you'll see all the groups, forums, and companies

dedicated to this channel. You can pick browser types, geographic tar-

geting, Operating System, and now even what security filter you want

the traffic to pass. It's like a restaurant menu for the attention of ro-

botic software programs.

You simply provide them a URL that you want the click to land on and

provide the targeting you want, and then just click start and let it run.

It really is as easy as that.

The only real calculation necessary is how much you can spend per

click. To figure out your maximum CPC, you need to know two things:

the CPM you will be paid and the number of ad placements on a page.

In Figure 1 there is a $2.50 CPM buy on the site and the pages load 4

ad-placements.

So the maximum this publisher can pay per click is $0.01.

Are there good sources of traffic?

Yes, there most definitely are good sources of quality human web

traffic. The best practice with buying hits to your site or a specific page

is to monitor the data and reports after the fact to in-effect, police the

supplier of the traffic. Even with a traffic source that is primarily clean,

there can be unintentional instances of bots coming through that the

supplier may never know about unless it is brought to their attention.

They can only take action for future prevention if a customer makes

them aware of it. Every business' product offering is developed around

the needs of its customers.

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9 DHAR METHOD

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How do you differentiate a good source versus a bad

source?

Some people will say that the "easy" way to determine good traffic is

by the cost (higher the better) or the performance of the traffic with

advertisers.

There is no consistent clean cut method of determining what source of

traffic is good or bad.

The reason "bad" sources of traffic have persisted and grown is be-

cause the requirements of the buyers did not include things like viewa-

bility or bot detection filters because the buyers of the ad-space did

not have these requirements.

Spotting the intricate differences between types of web traffic and the

sources selling them require lots of experience that the majority of

above-ground players in advertising will never be exposed to. In lieu of

this organic exposure, it’s imperative to find advisers and employees

that can provide assistance based on their first hand experience.

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11 DHAR METHOD

FINANCIAL INCENTIVES UNCOMMON SENSE FOR AD TECH

FINANCIAL INCENTIVES

DHAR CHART FIG. #2: Financial Incentives in the Ad Industry

Organization Financial Incentive

Publishers Sell as much advertising as possible to fund

operations & content creation

Advertisers (Brands) Derive maximum value (sales & aware-

ness) from money spent

Agencies Generate margin by taking over planning

& execution of media buying

Ad Tech Companies Process & serve as many impressions as

possible

Bot Detection Companies The existence of bot traffic makes them

valuable

Every business has a purpose that helps define its financial incentives.

In this paper, I want to outline how this principle informs the behaviors

of the various for-profit segments of the digital advertising industry,

and specifically their unique financial incentives.

While I recognize there are non-financial purposes of all players which,

in turn, contribute to a positive and beneficial internet experience for

users, the financial incentives often conflict with one another.

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PUBLISHERS

Sell as much advertising as possible by selling ad-space for

as much as possible AND increasing the quantity of availa-

ble ad-space.

The overarching purpose of most publishers is to produce engaging

content that attracts, retains and grows a loyal audience that values

the messaging of the publisher and contributes to the overall commu-

nity of the site/app. The financial incentive of a publisher is to sell as

much advertising as possible. This is done by either selling the existing

ad-space for as much as possible or by creating more ad-

opportunities; or commonly, BOTH. (The previous section outlined the

simple way that publishers can increase their ad-opportunities).

What I want to dive in to here, is how they maximize the dollars gen-

erated per existing ad-opportunity.

The traditional way of selling media was to have a sales person or

team that reached out to agencies and other media-buyers and con-

vince them to put their media buys through their property. These

sales or deals were done on what we refer to now as a "fixed deal."

This deal outlined the flight dates of the campaign, the number of im-

pressions required, and the rate structure (i.e. CPM) paid for the ad-

space.

As publishers increasingly move towards monetizing through program-

matic channels, there is less need for these direct sales teams and re-

lated infrastructure.

13 DHAR METHOD


PUBLISHERS CONT.

But because of the fewer number of people as well as the introduction

of a complex and often misunderstood technology, the awareness and

knowledge of the team becomes the key differentiating factor in per-

formance. I cannot stress how shocking it has been for me, someone

whose career path in this industry began with the existence of pro-

grammatic, to meet and work with publishers who monetize program-

matically and have limited awareness of how the technology works,

and the potential impact on their business.

The root cause of the problem is not specific to one person or one

company but the nature of how we work as people. We think that

once we have enough years under our belt or have achieved what we

consider sufficient, we think it's okay to stop learning. I believe that

the day we stop learning, is the day we become obsolete.

The cause of modern inefficiencies and under-performance by publish-

er sales/ops teams is largely a lack of knowledge and understanding of

the tools and resources that are available to publishers. More often

than not, this deficit is reinforced by a lack of training resources or

access.

Knowledge is power and our goal is to level the playing field by equip-

ping everyone with the same tools so the environment becomes truly

competitive.

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BRANDS & ADVERTISERS

Derive maximum value from dollars spent

To avoid any confusion, when I refer to advertisers, I am referring to

companies that spend money to promote their products or services. It

is because advertisers are spending more money programmatically

that the publishers have shifted to monetizing through those chan-

nels.

Let’s be clear: Advertisers Control The Ecosystem

It's just a matter of how involved they want to, choose to, and are ca-

pable of being.

And so far, since the advent and adoption of programmatic, they have

been the hands-off CEO that only gets involved when they see a dip in

the revenue numbers or profit margin. They have not been guiding the

process along the way or contributing to the improvement of the tech-

nology to the extent that the power of their dollars would otherwise

indicate.

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BRANDS & ADVERTISERS CONT.

If advertisers truly want to be in control of how their marketing dollars

are spent, they must truly be involved in the discussions with the par-

ties that control the critical parts of the ecosystem. Attending the

yearly meeting of the ANA or the AAAA is NOT ENOUGH. They must

meet with the publishers, the Ad Tech vendors, and the agencies to-

gether. It MUST be an open discussion where everyone is held ac-

countable and must answer questions from the other sides of the in-

dustry. We cannot silo ourselves to have our regular discussions within

our own segments of the advertising realm.

The problem, at least on a surface level, seems to be that even though

estimates of cost of ad-fraud to the brands of the world is estimated

between $10-$15 Billion, the total number spent on marketing/

advertising is almost $570 Billion.2 This means that holistically, adver-

tising is only suffering a loss of 1.7%-2.6%. Looking only at the percent-

age, it is understandable how CMO's of major brands have not felt the

pressure to band together and tackle the problem. When you're busy

worrying about TV, radio, magazine, newspaper, billboard, and brand-

ing spend, it becomes difficult to consider programmatic ad-fraud a

significant enough issue to dedicate a lot of resources and time to pre-

vention.

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AGENCIES

To continue to be the intermediary between brand budg-

ets and media buying venues; they must make the execu-

tion of media-buying more efficient so they can increase

their margins

Even if an agency is aware of the level of bad or fraudulent traffic in a

source they are buying media from, they often do not have a financial

incentive to alter their behavior as often they are compensated on a

percentage of their media spend for their clients. Changing trends in

how media buying is compensated is definitely changing this, but it

continues to occur.

The agency world is already altering their model because as advertis-

ers are trying to curb their spend, the agencies are having trouble

maintaining margins and meeting revenue projections. Many holding

company agencies outsourced programmatic media buying to an ATD

(agency-trading-desk) which continue to be challenged by visibility and

compensation challenges.

17 DHAR METHOD


EXCHANGES

Process and serve as many impressions as possible

Just like stock exchanges, ad-exchanges are for-profit businesses that

make money on the number of transactions that occur in their

platform. Rather than trading fees, ad-exchanges charge ad-serving

fees for holding the real-time auction; and rather than facilitating the

sale of corporate shares, they facilitate the buying and selling of ad-

impressions that disappear after the transaction is complete.

Most of the ad-exchanges have taken big steps to ensure that they

take care of both buyers and sellers, by implementing creative ad-

quality audits to protect publishers and implementing intricate do-

main tracking to ensure traffic quality for advertisers. But this is the

tough position that exchanges are put in, in terms of what functionali-

ties to implement and prioritize; they serve the interests of both buy-

ers and sellers, which often conflict. Although most exchanges have

taken great measures to protect both sides, even these engineering

feats are funded by the revenues from ad-serving. The more impres-

sions that are handled by the exchange, the more money they make.

Even though they take some steps to eliminate bad traffic, exchanges

have a financial incentive to transact as many impressions as possible.

This conflict of interest is a tough place for the executives of these

companies to be in because they are being pulled in two opposite di-

rections.

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FRAUD DETECTION COMPANIES

The existence of fraudulent web traffic

Fraud/bot detection companies are created and run by extremely bril-

liant engineers and technical minds. The amount of research and cal-

culation that goes into creating effective bot detection software is un-

fathomable to most of us that are not adept in coding and program-

ming. They invested the time and money into creating this detection

software because there was a market for it due to the high amounts of

fraudulent web traffic in the online advertising world. The mission was

and still is, to keep advertisers safe from wasting their marketing

budgets on advertising that would never have an ROI. The risk to ad-

vertisers was high enough that it is completely justifiable to spend sig-

nificant monthly resources to protect themselves from bad traffic

(resources that would otherwise be spent on marketing).

As time went on, several fraud detection vendors have emerged, all

with different (the degree is debatable) metrics of what qualifies

traffic or even whether a specific impression should be delegated as

suspicious or fraudulent. If a publisher uses Bot Detector-A to filter

their traffic, but their main SSP uses Bot Detector-B, and the ATD or

DSP uses Bot Detector-C, this can result in problems for the publisher

as well as the SSP. Even though the supply side players are making

efforts in time and money to ensure their traffic quality in the market

is clean, they are using a different standard than the buyer who can

reprimand them and even blacklist the publisher in certain cases.

19 DHAR METHOD


FRAUD DETECTION COMPANIES CONT.

On top of the incongruence in standards for what constitutes bad

traffic, there is an elephant in the room. This elephant comes in the

form of a bot detection company's financial incentive in the existence

of fraudulent traffic. They would not have had a reason to build a busi-

ness if there was not a rising amount of bot traffic inflicting losses to

advertisers, and they do not have a reason to be necessary to the mar-

ket if the amount of bot traffic were to eventually decrease to only 1%

of the entire web.

There is no assertion being made that the detection companies are

complacent, but we as players in the industry have to be aware of this

simple but evasive truth.

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TECH TAX UNCOMMON SENSE FOR AD TECH

When a new technology is introduced to improve the efficiency of a

business process, it involves a cost. The cost of garnering scale in the

business involves an incremental cost that causes reduction in profit

margins. If the implementation is successful, the overall profit goes up

and benefits all parties involved in the supply chain of that product or

service.

This can become a problem however, when the implementation of

this technology creates a big disparity between the original seller and

end-buyer.

Thus is the case with programmatic: the disparity between advertisers

and publishers involved in programmatic advertising has grown sub-

stantially, to the point that the majority of the money goes to technol-

ogy companies between the two parties.

Platforms and technology companies took 55% of the money spent by

advertisers, with only 45% reaching publishers.3

The cost of doing business in programmatic is costing both publishers

and advertisers substantially, but that is the price paid for efficiency,

scale, and advanced targeting.

TECH TAX

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If we take the example in Dhar Chart Fig. 3, we see that an advertiser

puts a campaign into a DSP for $5 CPM.

Since the DSP's profit margin to cover its costs of overhead, technology

and staff, is 20%, the actual CPM bid placed into the exchange is $4.

The exchange takes a portion from the DSP bid, as well as ad-serving

and a rev-share from the seller, which in this case is an SSP, which to-

tals $0.50, leaving the SSP with $3.50.

The SSP deals directly with the publisher, who receives $2.50, because

the SSP takes a rev-share of just under 30%.

So the publisher takes home $2.50 from the original bid of $5.

Each individual party in that example serves a purpose and adds value

to the entity on either side of them in the transaction. But when you

zoom out and look at the big picture, it looks troubling to see the dis-

parity between advertiser cost and publisher revenue.

This is a simplified version of the usual chain of events because it does

not involve any arbitrage, which will be covered in the following sec-

tions.

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PROGRAMMATIC UNCOMMON SENSE FOR AD TECH

PROGRAMMATIC

programmatic - adjective

pro·gram·mat·ic - \ˌprō-grə-ˈma-tik\

Definition: of, relating to, resembling, or having a pro-

gram

Although it's getting better, the word "programmatic" is used incor-

rectly by many people in the industry who deserve to have a compre-

hensive understanding of what it is, how it works, and why it affects

them. In non-technical terms, it is the automated process of buying

media through ad-exchanges that allows impressions to fit an adver-

tiser's targeting to be bid on by multiple buyers and finally, awarded

to the one willing to pay the most for that impression. The automa-

tion refers to the way that a campaign will be plugged into many

different ad-exchanges which makes thousands of domains and mil-

lions of users available to a single buyer with one campaign.

Programmatic buys are put into a digital ad-platform like an ad-

exchange or a DSP with the required targeting and a CPM bid that

represents the most the advertiser is willing to pay per 1000 impres-

sions. The transactions are executed individually for each impression

despite the bids being per 1000 impressions. So for a $5 CPM, the

most each impression can cost is $0.005.

The purpose of programmatic started originally as a way to effectively

sell ad inventory that was not sold through direct deals between pub-

lishers and agencies. If a publisher has on average 10,000,000 impres-

sions per month and the sales team is only able to sell 8,000,000 for

agency campaigns, they are left with 2,000,000 unsold impressions.

Typically these ad-placements would show either a house-ad pro-

moting the site itself or a non-profit organization that the publisher

has a relationship with. Once there was an exchange to plug this rem-

nant inventory into, it was a no-brainer for publishers to monetize

there even if the CPM was $1.00 compared with their agency deal of

$8 CPM.

$1 is still better than $0.

As re-targeting became more and more prevalent, which is the display-

ing of ads to users based on their past web browsing behavior, pro-

grammatic become significantly more appealing to publishers since

advertisers were willing to pay much higher CPMs for users that had

already shown interest in their product or service.

The main advantages of programmatic advertising are scale, efficiency

of execution, and advanced targeting.

RTB, or real-time-bidding, is the crux upon which programmatic execu-

tion is done. The RTB auction happens in 100-150 milliseconds depend-

ing on who you ask and which platform you are referring to. This frac-

tion of a second timespan allows multiple auctions to be held for a sin-

gle impression based on a publisher's price requirements.

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25 DHAR METHOD


AD

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26 DHAR METHOD


Since publishers now had multiple opportunities to sell a single im-

pression, many of them set up what is called a "daisy-chain" or a

"waterfall." This set up is when the publisher’s ad-server creates vari-

ous levels of price floors and sends the impression to different de-

mand partners based on price priority.

Demand 1 had the highest price and thus the highest priority so the

impression was sent for auction there first. If Demand 1 did not fill at

the required price, the impression was sent to Demand 2 at a lower

price floor. Now if the impression was not filled there either, it was

then sent to Demand 3 and so forth.

This is where the term "first-look" comes from. It becomes harder to

sell the impression at the same price the farther down the chain you

go because it means that other groups of buyers did not want it, thus

the price floor decreases as the impression makes its way down the

"waterfall."

Programmatic is what pushed online advertising to focus more on the

value of a user rather than the estimated value of a domain. This is

great for advertisers but can cause concern for publishers who relied

on their brand value to command high CPMs from advertisers.

This change caused media planning to not only include demographics

in their process but psychographics as well.

As programmatic buying progresses and evolves, the reach of this

technology will expand while increasing its effectiveness and pro-

moting educated use of related platforms. This will be imperative as

people’s lives include more screens and more technology mediums to

become addressable, programmatic methods will prove to be ex-

tremely versatile.

27 DHAR METHOD


DH

AR

CH

AR

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G. #

5: D

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28 DHAR METHOD

ARBITRAGE UNCOMMON SENSE FOR AD TECH

ARBITRAGE

Arbitrage is one of the most fascinating concepts in digital advertising

over the past several years and still exists today. The term represents

the practice of the near-simultaneous purchase and sale of an asset to

profit from the exploitation of differences in price between both iden-

tical and different markets.

There is CPA arbitrage, in which one purchases a lead for $5 and sells it

immediately for $8 to a buyer who is in need of it.

There is CPC arbitrage, in which one purchases a click from a traffic

provider to a certain page and sells that visit to the owner of the page

for a higher price. Similar to a broker.

Then there is CPM arbitrage, which involves buying an impression early

in its life-span and selling it either in the same exchange or different

exchange for a potential higher price. This is possible only because of

the speed of auctions happening in fractions of a second. CPM arbi-

trage occurs in display as well as video, desktop as well as mobile; it is

just that video auctions take at least twice as long.

Refer to Dhar Chart Fig. 7.

If you take a 150 millisecond timer, you can hold 1-6 auctions before

the final ad-creative is served or the impression disappears. That's the

strange thing about arbitrage, even if the impression times out before

there is an actual creative served, the publisher, exchange-seller, Net-

work D, Network C, and Network B all made money. It is Network A

that suffered the loss because it purchased the impression without

having enough time to sell to the Exchange-Buyer.

29 DHAR METHOD


DH

AR

CH

AR

T FI

G. #

7: Th

e A

rbitra

ge

Pro

ce

ss

-$0.50

$0.35 (10% fee)

$0.05 (Ad Serving)

$0.10 (Profit)

Exchange

Buyer

$3.50

Network

A

$3.00

Network

B

$2.70

Network

C

$2.25

Network

D

$2.00

Exchange

Seller

$1.50

Publisher

$1.00

-$0.25

$0.05 (Ad Serving)

$0.20 (Profit)

-$0.50

$0.05 (Ad Serving)

$0.45 (Profit)

-$0.25

$0.05 (Ad Serving)

$0.20 (Profit)

-$0.50

$0.05 (Ad Serving)

$0.45 (Profit)

-$0.50

$0.05 (Ad Serving)

$0.30 (Profit)

$0.15 (Rev-Share)

$1.70 Lost to

arbitrage players

30 DHAR METHOD


The scale of arbitrage is not mentioned or discussed in industry arti-

cles and trade publications because the majority of people are not

aware of the extent to which it has reached. Until recently any ex-

change buyer could purchase 100's of millions of impressions a day at

around $0.01 CPM and resell these in other exchanges for an average

of $0.05 CPM. This profit of $0.04 CPM seems small initially but if you

take 100M impressions at $0.01, the cost is $1000. The revenue is

$5000. The gross profit is $4000 and once the ad-serving fees and rev

-shares are applied, the net profit comes to around $3000 for little to

no work which remains essentially on auto-pilot until the dynamics of

the market demand change.

Although this may seem malicious or even bizarre to some, the only

reason these opportunities existed was because there were end-

buyers placing bids of $0.02-$0.25 CPM in the exchanges. The cam-

paigns attached to these low bids were meant solely to fill budgets

and thus had very minimal targeting requirements outside of the

"users" being in the US.

Arbitrage is the dark side of daisy-chaining and waterfalls because it is

done by parties who do not own or even officially represent the ad-

space in question. Most arbitrage transactions are not connected to

the final buyer or original seller, but are between various arbitrage

players that simply re-sell without adding value. The negative effects

of arbitrage must NOT be confused with the "tech-tax" described in

Section 4, although many of the similar platforms make incremental

revenue along the way.

Although this is a fascinating concept and innovating method of reve-

nue generation for the individual party, it corrupts the value of the

impression and creates a larger than necessary disparity between

buyer cost and seller revenue.

31 DHAR METHOD

TOOLBAR TRAFFIC UNCOMMON SENSE FOR AD TECH

TOOLBAR TRAFFIC

Toolbar traffic is web traffic that is generated and provided for sale by

companies that create browser extension and toolbar products that are

supposed to enhance a user's browsing experience, either by making

access to information like the news and weather easier, or by making a

search engine tool available in the screen regardless of what page a us-

er is on.

There are many different types of traffic made available for advertisers

by toolbars, these include but are not limited to:

Pop-up

Pop-Under

Overlay

Injection

Search

Most of the time, these products are "bundled" into downloads that

users legitimately initiate from both reputable and non-reputable prod-

uct download sites. The "bundling" refers to the fact that these down-

loads come as part of the "Express (Recommended)" install method ra-

ther than the "Advanced (non-recommended)" method. If a user choos-

es the "Advanced" method when downloading, they will typically be

able to unselect the additional products being offered in the package.

Many adept computer and internet users will notice their machines

behaving differently after an online download even though the down-

load was supposed to only be for a movie player.

To avoid being detected in this manner and be removed by users, the

programs operate on a delayed monetization method. The program

essentially just remains dormant on the computer until several days

later when the change in machine behavior will not necessarily be

attributed to the instance of the download. The way this is done is by

delaying overlay ads until 3 days after the install, delaying In-text ads

until 7 days after the install, and Pop-ups until 14 days after the install.

The owner and creator of the software must recoup the cost of the

user's install within the time that an average user keeps the program

installed before removal. The products are typically distributed by CPI,

cost-per-install, companies that provide user downloads at a fixed cost.

After all that, it may come as a surprise that there are both legitimate

and malicious toolbars/extensions. The issue is that both types use the

CPA and CPI companies to promote their products. We must remem-

ber that CPI and install-monetization companies have been around

much longer than mobile-apps; and the toolbar product downloads

were and remain a significant portion of their business.

It is even difficult for a CPI company to discern between a legitimate

and malicious toolbar.

32 DHAR METHOD


33 DHAR METHOD


A legitimate toolbar product will add a weather or news widget to the

user's browser and then monetize through display ad placements and

search query based text ads.

A malicious toolbar product will do all of the above, but will also hijack

a users browser to visit thousands of pages to generate ad-revenue

whether the user is actively using the computer or if the computer is

in "sleep" mode. The fake browser activity is done invisibly so even

when a user is on the computer, they cannot see the activity happen-

ing. The malicious product, or malware/adware, cannot operate if the

computer is fully shut-down.

These types of products, running undetected and invisibly on a user's

computer are the reason that many people feel that their computer

"slows down" over time or that their battery life "gets worse" over

months or years. The computer operating speed is due to the fact that

when a user is on their computer, their processor is busy simultane-

ously running several browser windows and visiting thousands of pag-

es every hour. The issue of battery life deterioration is due to fact that

extra processing power is being used while the computer is on and

actively being used, but also when someone puts their machine into

"sleep" or "hibernate" mode.

When there is a mass network of these malicious products installed on

users' computers, it forms what is referred to as a Botnet. We will dive

into this concept in much further detail in section 9 (Botnets & Bot

Farms).

34 DHAR METHOD

AD-BLOCK UNCOMMON SENSE FOR AD TECH

AD-BLOCK

Digital advertising is an ecosystem with three primary figures: Market-

ers, Content Owners, and the Consumers. Although no one is more

important than the other, both marketers and content owners de-

pend on the basic existence of consumers. These consumers practice

consumption of both content and the advertising that funds it. This is

an implicit contract in society that is wavering in the world of digital.

Since consumers have had the available option of blocking the adver-

tising (again, this is what funds the content creation) to allow for

“better” user experience in content consumption, it has become in-

creasingly popular with 41% year over year growth.5

This trend is threatening the ecosystem that comprises the Ad Tech

space. This threat is as important and merits just as much attention

and dialogue as ad-fraud; yet we rarely discuss both in the same con-

versation.

We propose there is a direct relationship between these two issues,

and thus the dialogue needs to address both issues simultaneously.

Let’s start with the raw numbers:

$6.3B Ad Spend on Fraudulent Web Traffic

$5.8B Lost Ad Spend From Ad-Blockers

$43.8B Total Digital Advertising Spend

14.38% of Total Digital Ad Spend Wasted on Fraud

13.24% of Potential Digital Ad Spend Lost From Ad-

blockers

~45,000,000 Ad-Block users in the United States

35 DHAR METHOD


Obviously, those numbers are not exact matches, but they are eerily

close. There are some basic concepts that inform my position that ad-

block and ad-fraud are closely related.

Advertising budgets stay constant or increase over time

Publishers want their revenues and audience metrics to

stay constant or increase over time

There is a rapidly increasing segment of users employing

ad-block

The practice of content owners purchasing web traffic

to boost numbers has increased over time

More than 50% of purchased traffic is fraudulent6

The gradual decline in revenue for publishers and content owners due

to ad-block fueled the drive to acquire more consumers, most efficient-

ly accomplished via purchasing click traffic. This act, in turn, allowed for

the creation of more companies offering click traffic to publishers and

at ever-diminishing rates per click due to oversupply of traffic suppli-

ers. Somewhere along the way, we all stopped discerning how legiti-

mate a $0.01 click can really be. It’s the very nature of businesses to

focus on the end game.

The resulting growth of page-views and “users” allowed publishers to

have more control over “audience scale “ and thus control volume fluc-

tuation, and therefore revenue.

36 DHAR METHOD


Advertisers continued to buy this inventory based on historical trust in

the quality of publishers’ web traffic and audience data. One problem

was that these paid clicks returned better ROI’s for publishers since the

suppliers of this traffic were forced to differentiate themselves from

their competition. This led to bots getting smarter and smarter.

Some industry pundits contend that, data-wise at least, bots are better

at being human than humans are. They accumulate lots of cookies,

abandon shopping carts, and visit a wide range of websites both large

and small. It’s very easy for a bot creator to simulate a valuable target

audience. Again, this also compensated for the lack of audience data

due to ad-blockers.

Candidly, blame cannot be exclusively pointed at either advertisers or

publishers. Economics and business bottom-lines are the fuel in this

fire. The key is whether we rapidly grow awareness of this trend and

address it properly before it’s too late. Failure to do so will result in a

painful restructuring where the entire foundation of digital media eco-

nomics and the free Internet is in jeopardy.

Ad-blocking became popular because consumers wanted to protect

their user-experience which was being threatened by bad/intrusive ad-

creatives as well as the load time of pages due to multiple ad-calls be-

ing made. The answer is clear.

The consumer is key and must be respected

Currently, with ad-blocker enabled, a user is essentially non-existent to

both marketers and content owners. To prevent the blocking of ads,

which fuels the purchase of fraud traffic, we must address the con-

cerns of the consumer!

37 DHAR METHOD


Current attempts to block ad-fraud are Sisyphean tasks because the

dialogue is not taking into account the user experience, the consumer

is the cornerstone for both publisher and advertiser businesses. The

implied contract between marketers, content owners, and consumers

is slowly going to have to change to an explicit one.

To repeat, the potential lost revenues to publishers due to ad-block

are indirectly compensated for through ad-spend on fraudulent activi-

ty from purchased traffic. The rise of ad-block is due to an increasing

distaste for bad user-experience on the web; this is correlated with

the rise of ad-fraud. So we MUST, as an industry, bring consumer ex-

perience into the forefront of dialogue when discussing the battle

against ad-fraud.

Advertisers shouldn’t be funding the ad-fraud world, but right now

unfortunately, they are.

The numbers mentioned above are solely for the US and are from

public reports published separately by PageFair & Adobe and White

Ops & DCN published in 2015.

The estimate for global potential revenue lost to ad-block is $21.8 B.

38 DHAR METHOD

BOTNETS & BOT FARMS UNCOMMON SENSE FOR AD TECH

BOTNETS & BOT FARMS

While there are many similarities between Botnets and Bot Farms,

there are some key differences that separate the two concepts.

Operation of both Botnets and Bot Farms requires a financial motive (a

demand for the traffic) as well as a keen understanding of the internet

economy and computer programming.

Ownership of Botnets or Bot Farms is a form of power of both money

and influence. The money is made by selling the traffic to various buy-

ers. The influence is held by the capability to crash both government

and private sites by overloading the server with user visits. Access to

this influence is also held by those with access to this traffic at low

costs.

Although these seem foreign and sophisticated, we must remember

that the entire system of bot traffic is made of many individual pieces

that can be understood and addressed independently.

The main differences between the two methods is their physical loca-

tion and operational infrastructure.

A Botnet relies on various machines worldwide.

A Bot Farm is physically centralized in one location.

A Botnet requires more sophistication with software.

A Bot Farm requires more sophistication with hardware.

In advertising we see the effects of bots being used to impact what is

considered the public Internet or Surface Web. There is also the major-

ity of the Internet, which is referred to as the Deep Web or Hidden

Web. Although an understanding of what all goes on in the Deep Web

is not necessary, it is crucial to understand its existence when pursuing

an understanding of the economy of the Internet.

39 DHAR METHOD

BOTNETS & BOT FARMS UNCOMMON SENSE FOR AD TECH

FIL

TER

SOU

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TEST

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40 DHAR METHOD

CURRENT STATE OF AD TECH UNCOMMON SENSE FOR AD TECH

CURRENT STATE OF AD TECH

There are many unintentional bad practices that have contributed to

the problems currently contributing to Ad Tech’s reputation with the

advertising industry at large.

1 Awareness of how programmatic auctions and systems operate.

Nearly half of the marketing ecosystem (44%) understands very

little or nothing about how programmatic works, this is particularly

prevalent amongst advertisers (63%), agencies (48%), and publishers

(47%).4

2 Many positions, both on the media buyer and media seller side,

are over-worked and don't have time for extra-curricular learning

3 Most companies do not provide in-house education for new em-

ployees or continuing education for current staff.

4 Conferences always move onto the next new thing rather than

trying to understand what has happened in the past. This way, we

get farther and farther from the basics and continually understand less

and less of what is currently happening.

41 DHAR METHOD


DHAR CHART FIG. #8: Bot Traffic Over the Years

% o

f B

ot

Tra

ffic

100

75

50

25

1996 2016 2006 2026

Projected Good

Practices

Projected Bad

Practices

Years

42 DHAR METHOD


5 Bot traffic and people associated with it are referred to and

thought of as some external problem caused by malicious people,

hackers, bad actors, and cyber-criminals. There are also many refer-

ences in trade publications and blogs connecting the operation of Bot-

nets and Bot Farms to organized crime. While this may be true, I have

never encountered any proof of this nor do I see a need for any moti-

vated developer who creates a Botnet to have any reliance on orga-

nized crime. We MUST accept that the existence of bot traffic is purely

a result of our lack of awareness of what causes it and thus how to de-

tect and avoid it.

6 Our collective understanding of the new age of Ad Tech is swarm-

ing with buzzwords. A true, enriched understanding means a deep

comprehension of how the various pieces not only operate but work

together with other systems in the space as well as where they con-

flict.

7 We have an unhealthy reliance on popular yet arbitrary metrics

like Alexa ranks, IAB definitions, and quality ratings like Comscore/

Quantcast.

43 DHAR METHOD

ACTION ITEMS UNCOMMON SENSE FOR AD TECH

ACTION ITEMS

Now that you have all this information, what do we

do now? Where do we go from here?

Here are some action items that are not limited to

any one type of company. Things that we can all do.

1 Pursue an understanding of the economy of the

Internet.

2 Make it routine to have continuing education for

all employees at your company.

3 Bring more of the learning into your office rather

than sending out a handful of people to a confer-

ence. It should not become the job of those people

to understand and reteach everything from the con-

ference to their co-workers.

4 Ask more questions. Knowledge is power.

44 DHAR METHOD

WHAT CAN PUBLISHERS DO? UNCOMMON SENSE FOR AD TECH

WHAT CAN PUBLISHERS DO?

1 Be more discerning of who you buy web traffic

from.

2 Make your programmatic monetization partners

work hard for you. They need you and you have

options.

3 Ensure that your ad sales and operations teams

are educated about the industry past the point of

what their roles entail.

45 DHAR METHOD

WHAT CAN BRANDS DO? UNCOMMON SENSE FOR AD TECH

WHAT CAN BRANDS DO?

1 Ask your media buying agencies what they are

doing to ensure your marketing dollars don't go

into the wrong hands.

2 Educate your marketing teams on how the pro-

grammatic system is set up so they can ask better

questions.

3 Don't compromise on quality assurance for a re-

duced price of media. You get what you pay for.

46 DHAR METHOD

WHAT CAN BRANDS DO? UNCOMMON SENSE FOR AD TECH

WHAT CAN AGENCIES DO?

1 Hold your technology partners accountable by

knowing as much as, if not more than, them.

2 Educate your clients on why cheap media buying

is not safe and that it's better to not buy anything

at all.

47 DHAR METHOD

WHAT CAN EXCHANGES DO? UNCOMMON SENSE FOR AD TECH

WHAT CAN EXCHANGES DO?

1 Do not stop innovating. Your teams should find the

loopholes in your platform before someone else

does. Then make sure you close the loopholes.

2 Have consequences for bad actors. They hurt the

interests of your actual clients which are real me-

dia buyers and sellers.

48 DHAR METHOD

WHAT CAN DETECTION COMPANIES DO? UNCOMMON SENSE FOR AD TECH

WHAT CAN DETECTION COMPANIES DO?

1 Don't give out accounts to everyone.

2 Understand that your staff and your clients need

a holistic view of what causes fraud outside of

technology. You can't get rid of fraud alone.

49 DHAR METHOD

CONCLUSIONS UNCOMMON SENSE FOR AD TECH

CONCLUSIONS

Ad Tech as a sector of the overall advertising industry was supposed to

make things better. It was supposed to be a revolutionary addition that

made things more efficient, trackable, scalable and in some senses,

simpler. The efficiency came from having one contract for buying ad

space across many publishers which was in the end exponential

productivity from one single media buyer. The scalable aspect for pub-

lishers came from filling more percentages of their ad space with only

one buyer relationship who plugged them into the programmatic ex-

changes.

Since the infrastructure and execution was all built around technical

processes with little education for users of the services along the way,

we began to see technical "hacks" of the gaping loopholes in the sys-

tems. This consistent exploitation by individuals who are not necessari-

ly connected in their motivations or in their operations has resulted in

the cesspool of fraud that exists in Ad Tech today.

Since fighting technical "hacks" with technical oversight is a bit of a

Sisyphean game of cat and mouse, we need to start asking questions

about what allows these loopholes in the first place.

These need to be the RIGHT questions, asked to the RIGHT

people.

We need to take action and stop expecting other people

to do the right thing.

50 DHAR METHOD

CONTACT UNCOMMON SENSE FOR AD TECH

CONTACT

To find out more:

http://www.dharmethod.com/

email us:

[email protected]

REFERENCES

1 - John, George. "You Can’t Manage Online Ad Inventory Like A Stock Market." VentureBeat. 23 Feb. 2010. Web. <http://venturebeat.com/2010/02/23/you-cant-manage-online-ad-inventory-like-a-stock-market/>.

2 - eMarketer. "Total Media Ad Spending Growth Slows Worldwide." Total Media Ad Spending Growth Slows Worldwide. eMarketer, 15 Sept. 2015. Web. <http://www.emarketer.com/Article/Total-Media-Ad-Spending-Growth-Slows-Worldwide/1012981>.

3 - IAB. "IAB Programmatic Advertising Revenue Report - PwC Digital Ser-vices." PWC. July 2015. Web. <http://digital.pwc.com/insights/iab-programmatic-advertising-revenue-report/>.

4 - Fenge-Davies, Anya. "63% of Advertisers Have Little Knowledge of Pro-grammatic; 96% of Consumers Sent Mistargeted Offers | Ex-changeWire.com." ExchangeWire. 1 Oct. 2015. Web. <https://www.exchangewire.com/blog/2015/10/01/63-of-advertisers-have-little-knowledge-of-programmatic-96-of-consumers-sent-mistargeted-offers/>.

5 - The PageFair Team. "The 2015 Ad Blocking Report." PageFair. PageFair & Adobe, 10 Aug. 2015. Web. <http://blog.pagefair.com/2015/ad-blocking-report/>.

6 - "The Bot Benchmark Report." White Ops. Digital Content Next & White Ops, Inc., 2015. Web. 12 Feb. 2016. <http://www.whiteops.com/bot-benchmark>.

51 DHAR METHOD

REFERENCES UNCOMMON SENSE FOR AD TECH

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