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.
2DHAR METHOD

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."
3DHAR METHOD

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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5DHAR METHOD
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.
6DHAR 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.
7DHAR METHOD

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.
8DHAR METHOD

9DHAR METHOD
CPC=CPM÷
1000
#ofadsonpage
()
DHARCHARTFIG.#1:BuyingTraffic
()
Example
1000
4adsonpageCPC=$2.50÷
Breakeven:CPC=$0.01
AD
AD
AD
AD
MaxAffordedCPC

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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11DHAR 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.

12DHAR METHOD
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.

13DHAR 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.

14DHAR METHOD
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.

15DHAR METHOD
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.

16DHAR METHOD
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.

17DHAR 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.

18DHAR METHOD
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.

19DHAR 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.

20DHAR METHOD
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

21DHAR METHOD
AdvertiserDSPExchangeSSPPublisher
$5.00$4.00$3.50$2.50
DHARCHARTFIG.#3:HiddenIntricaciesofthe“TechTax”

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.
22DHAR METHOD

23DHAR METHOD
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.
24DHAR METHOD

DHARCHARTFIG.#4:RTBAuction
25DHAR METHOD
AD
AD
ImpressionInformation
Location:NewYorkCity
Time:7:29PM
Browser:Chrome
Cookies:
-shoes
-sweaters
-lifeinsurance
-carbrand
PriceFloor:$2.00CPM
(2ndPrice)Auction
$1.50-Bidder1
$2.52-Bidder2
$2.00-Bidder3
$3.75-Bidder4
$2.50-Bidder5
$1.75-Bidder6
Winner:Bidder4
WinPrice:$2.52

26DHAR 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.

27DHAR METHOD
DHARCHARTFIG.#5:DaisyChainProcess
Publisher
Impression
Demand1
$5.00Floor
DomainABC
300x250
ATF
150ms
Demand2
$3.50Floor
150ms
Demand3
$2.00Floor
150ms
Demand4
$1.00Floor
150ms
Demand5
NoFloor
150ms
Total:0.75-0.80seconds

28DHAR 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.

29DHAR METHOD
DHARCHARTFIG.#7:TheArbitrageProcess
-$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

30DHAR 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.

31DHAR 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.
32DHAR METHOD

33DHAR 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).

34DHAR 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

35DHAR 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.

36DHAR 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!

37DHAR 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.

38DHAR 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.

39DHAR METHOD
BOTNETS & BOT FARMS UNCOMMON SENSE FOR AD TECH
FILTER
SOURCEA
TESTSAMPLETRAFFICSUCCESSFUL
TRAFFIC
SOURCEB
SOURCEC
SOURCED
SOURCEE
SOURCEF
SOURCEG
F
E
C
DHARCHARTFIG.#9:ReverseEngineeringBotFilters

40DHAR 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.
1Awareness 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
2Many positions, both on the media buyer and media seller side,
are over-worked and don't have time for extra-curricular learning
3Most companies do not provide in-house education for new em-
ployees or continuing education for current staff.
4Conferences 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.

41DHAR METHOD
DHAR CHART FIG. #8: Bot Traffic Over the Years
%ofBotTraffic
100
75
50
25
1996 20162006 2026
Projected Good
Practices
Projected Bad
Practices
Years

42DHAR METHOD
5Bot 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.
6Our 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.
7We have an unhealthy reliance on popular yet arbitrary metrics
like Alexa ranks, IAB definitions, and quality ratings like Comscore/
Quantcast.

43DHAR 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.
1Pursue an understanding of the economy of the
Internet.
2Make it routine to have continuing education for
all employees at your company.
3Bring 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.
4Ask more questions. Knowledge is power.

44DHAR METHOD
WHAT CAN PUBLISHERS DO? UNCOMMON SENSE FOR AD TECH
WHAT CAN PUBLISHERS DO?
1Be more discerning of who you buy web traffic
from.
2Make your programmatic monetization partners
work hard for you. They need you and you have
options.
3Ensure that your ad sales and operations teams
are educated about the industry past the point of
what their roles entail.

45DHAR METHOD
WHAT CAN BRANDS DO? UNCOMMON SENSE FOR AD TECH
WHAT CAN BRANDS DO?
1Ask your media buying agencies what they are
doing to ensure your marketing dollars don't go
into the wrong hands.
2Educate your marketing teams on how the pro-
grammatic system is set up so they can ask better
questions.
3Don't compromise on quality assurance for a re-
duced price of media. You get what you pay for.

46DHAR METHOD
WHAT CAN BRANDS DO? UNCOMMON SENSE FOR AD TECH
WHAT CAN AGENCIES DO?
1Hold your technology partners accountable by
knowing as much as, if not more than, them.
2Educate your clients on why cheap media buying
is not safe and that it's better to not buy anything
at all.

47DHAR METHOD
WHAT CAN EXCHANGES DO? UNCOMMON SENSE FOR AD TECH
WHAT CAN EXCHANGES DO?
1Do not stop innovating. Your teams should find the
loopholes in your platform before someone else
does. Then make sure you close the loopholes.
2Have consequences for bad actors. They hurt the
interests of your actual clients which are real me-
dia buyers and sellers.

48DHAR METHOD
WHAT CAN DETECTION COMPANIES DO? UNCOMMON SENSE FOR AD TECH
WHAT CAN DETECTION COMPANIES DO?
1Don't give out accounts to everyone.
2Understand 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.

49DHAR 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.

50DHAR METHOD
CONTACT UNCOMMON SENSE FOR AD TECH
CONTACT
To find out more:
http://www.dharmethod.com/
email us:
info@dharmethod.com

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>.
51DHAR METHOD
REFERENCES UNCOMMON SENSE FOR AD TECH

Uncommon Sense for Ad Tech Download

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