
Behavioral Ad Targeting Not Paying Off for Publishers, Study Suggests - Quanttek
https://www.wsj.com/articles/behavioral-ad-targeting-not-paying-off-for-publishers-study-suggests-11559167195
======
Quanttek
Crucial quote:

But in one of the first empirical studies of the impacts of behaviorally
targeted advertising on online publishers’ revenue, researchers at the
University of Minnesota, University of California, Irvine, and Carnegie Mellon
University suggest publishers only get about 4% more revenue for an ad
impression that has a cookie enabled than for one that doesn’t. The study
tracked millions of ad transactions at a large U.S. media company over the
course of one week.

That modest gain for publishers stands in contrast to the vastly larger sums
advertisers are willing to pay for behaviorally targeted ads. A 2009 study by
Howard Beales, a professor at George Washington University School of Business
and a former director of the Bureau of Consumer Protection at the Federal
Trade Commission, found advertisers are willing to pay 2.68 times more for a
behaviorally targeted ad than one that wasn’t.

Much of the premium likely is being eaten up by the so-called “ad tech tax,”
the middlemen’s fees that eat up 60 cents of every dollar spent on
programmatic ads, according to marketing intelligence firm Warc.

~~~
manigandham
There is no "ad tech tax". It's called a supply chain. The end product costs
more than the raw parts in every industry.

The issue for publishers here is lack of scale, no cookies, and 2nd-price
auctions, meaning they don't get enough high bids and don't get the full price
for those bids when they do happen.

~~~
reallydude
There is some confusion about what a "publisher" means. A publisher is either
an SSP (a platform where publishers are aggregated by flat contract fee on a
time or traffic basis with guarantees) or a singular site.

> There is no "ad tech tax"

That is correct. You might get better revenues (as a publisher) dealing with
SpotX (an exchange) over say...Viant (a reseller who acts as a publisher to
SpotX), but probably won't do better on volume, which directly correlates to
payout. Then again, SpotX may not pay you as much for your average demographic
and volume as Viant, who wants your business more than SpotX. None of this is
supply chain. The chain is not a chain, but more of an amalgam of situations
that is affected by the market, as much as personal relationships.
Conceptually, an ecosystem where anyone can consume from anyone (as a
publisher) and feed from anyone (as an exchange).

> The issue for publishers here is lack of scale

You don't know that. In 2009, the economy was still recovering and ad-tech had
been slapped hard in 2008, leaving banner ads at fractions of the previous
years. They have slowly floated down a few more cents to where they are today,
primarily due to better targeting, ad fraud, video, mobile browser support,
and clickbait (er native) ads.

> no cookies

This was the comparison that led to the 4% revenue bump. If platforms do not
pay forward to the publishers (because why bother, the platforms set their own
cookies anyway), it suggests that publishers shouldn't bother with targeting.
That's exactly what has happened. No platform consumes publisher targeting
data in arbitrage, because it might be faked. Using something like Zvelo for
context and your own cookies, you get a much better view of the client.

> 2nd-price auctions, meaning they don't get enough high bids and don't get
> the full price for those bids

Whatever "high bids" or "full price" means here, is nebulous. How an exchange
decides to run auctions is often negotiated up front but is, ultimately, black
box. What this has to do with publishers is confusing. Publishers rarely get
paid off what the platform makes. You sign an order for a set period of time
or slice of impressions unless you have traffic that is hundreds of thousands
per day (an exeedingly small number of sites). In the case where you run a
Real Time Bidding auction (header bidding), you might make some variable
money. It's rare and wasn't even seen in the wild (ie IAB) till well after
2009.

See this more recent breakdown: [https://www.emarketer.com/content/why-tech-
firms-obtain-most...](https://www.emarketer.com/content/why-tech-firms-obtain-
most-of-the-money-in-programmatic-purchases)

~~~
manigandham
Nobody in adtech confuses publisher and SSP. And why are you mentioning 2009?
The paper is about data from a single week in 2016 from a single publisher.
Did you actually read it?

Scale is the main issue because publishers need to have users with cookies,
then match cookies to high-value bids, and then receive enough competing bids
from advertisers to see a real difference in rates. This is fundamental market
mechanics. Publishers getting flat-rate deals is rare, not common. Most of the
time they get paid on variable programmatic basis with some take rate by the
upstream SSP.

It's a supply chain because these vendors facilitate the buying of media
inventory. That's the definition of a supply chain. You can build your own car
after buying raw parts but that doesn't mean that there's no supply chain that
lets you buy the finished product from Ford. The article you linked shows
exactly where the money goes to in the chain. DSPs, DMPs, verification vendors
are used to buy ads and they need to be paid. You can easily avoid it and deal
with the publisher if you want, but advertisers don't because of the value
they get from those vendors.

------
atdt
Paper: [https://weis2019.econinfosec.org/wp-
content/uploads/sites/6/...](https://weis2019.econinfosec.org/wp-
content/uploads/sites/6/2019/05/WEIS_2019_paper_38.pdf)

~~~
sologoub
The methodology disclosed explains why the “lift” is so small:

TLDR - they analyzed logs provided from an “ad exchange” in 2016 (as exchanges
or SSPs were still “remnant” inventory players at the time and this is pre
header-bidding, so lowest quality of the available inventory went there), of
the logs they only looked at open auction (lowest quality of the already low
quality inventory self-selected by using the SSP logs).

RTB Deal ID, private marketplaces and other higher-rate products all use
behavioral/audience data and generate the lions share of the revenues. We are
talking impressions being boosted to between 10x and 100x in value easily if
they qualified for one of these higher-value channels.

By focusing on open auction that was preferred for valuable behaviorally
targeted impressions, the papers authors basically rigged the results.

~~~
sologoub
And looks like autocorrect struck again.

Last sentence should read s/preferred/prefiltered

------
jefftk
I'm very skeptical of this methodology, since it's completely correlational.
Here's how I would run this study as a publisher if I used an ad network that
lets the publisher turn off personalization on a per-pageview level (like
Google's ads, which I work on:
[https://support.google.com/admanager/answer/7678538?hl=en](https://support.google.com/admanager/answer/7678538?hl=en)).
I would run an A/B test of personalized ads vs non-personalized. This is
simple, and very robust since it's controlled.

My expectation is that if a big US news publisher tried this they would see
much more than a 4% difference, but that's speculation on my part.

------
baybal2
There is a long standing misconception regarding the value of "insight" coming
from traffic analytics.

There is no shortage of companies getting megabytes of data points per person,
yet they don't seem to be getting terribly ahead of ones who don't.

The a/b testing cult is a prime example. I knew companies who "optimised their
websites to death" blindly following the deemed "signal." I knew of a guy who
ran Borland's internet marketing and a lot of stories from him how hundred
thousands in ad spend were ending up bidden on common sense defying keyword
combinations.

~~~
cwyers
Amazon has all of my ebook buying history, and they have shown me hundreds of
ads for ebooks on my Kindle lock screen, and they have never once shown me an
ebook that I would have interest in buying. It is spectacularly awful.

~~~
dontbenebby
Maybe because many people still use libraries (which don't share data) so
there's no good database of reading habits the way there is for streaming
movies. (Which recs seem to work much better for)

~~~
sjg007
I don't find Netflix recommendations to be that useful. They recommend
categories for sure.. but I like a wide range of movies and it is usually on a
per movie basis.

~~~
atomical
I don't find NetFlix compelling because after I watch great movie X the
service cannot recommend me another movie that is of the same caliber.

Also, there are a lot of independent movies and TV shows on NetFlix. And they
suck. Horrible acting and plot but the cover is sometimes good enough to trick
you into wasting time taking a look.

~~~
visarga
> after I watch great movie X the service cannot recommend me another movie
> that is of the same caliber

Statistically, after viewing a great movie the next one will be rated as less
satisfying. We build up our expectations to a level that is not in sync with
reality. This psychological insight was used at one of the early Netflix
challenges by one of the top contestants.

------
dontbenebby
Do any of these studies factor in the labor costs? If you get 4% from
behavioral ads but need to pay hundreds engineers of 300+k to achieve it can
you really beat out a company like say, DuckDuckGo that spends less on
infrastructure/salary?

~~~
marcell
You don’t need to pay any engineers to get behavioral tracking for your ads.
This feature is provided by an ad network like Google, the publisher (like
WSJ) just enables it. Google sees 4% across their entire revenue, so it’s
definitely worth it for them.

~~~
godelski
> This feature is provided by an ad network like Google

> You don’t need to pay any engineers to get behavioral tracking for your ads.

Google doesn't need to pay any engineers?

~~~
pm90
> Google sees 4% across their _entire revenue_

This is important. Its cost effective for _Google_ to pay big bucks for
engineering labor since their network is used so widely. Its not cost
effective for WSJ to do so.

------
sonnyblarney
For context, most internet ad spending is very poorly measured, and is money
'thrown into the system' with very little direct oversight in terms of ROI on
part of the advertiser.

Either they can't measure the real ROI (brand advertising) or it's hard to, or
they are kind of lazy.

When big companies spend on ads, they often 'allocate' and the money just gets
spent.

The efficiency of those ads is going to be very low.

The world of actionable ads is narrow. Google search ads are generally very
specific and actionable, and are fairly well measurable. FB ads similarly (if
you want them to be). In those contexts, the 'targeting' will definitely pop
out at you and will make or break a campaign, so long as the advertiser is
watching the numbers.

A lot of what one would think of as 'actually targeted advertising' gets lost
in a wash of arbitrary ad spend.

------
neonate
[http://archive.is/qkfXz](http://archive.is/qkfXz)

~~~
JumpCrisscross
Thank you.

------
ivv
Since WSJ didn't bother to link to the study, its title is "Online Tracking
and Publishers’ Revenues: An Empirical Analysis," you can see it on Google's
Scholar.

It's not about whether the cookie is "enabled", but whether the cookie for a
particular impression is available for matching.

The experiment looked at ad transactions of a single media company.

------
aussieguy1234
The middleman will take 60%, unless the publisher builds their own ad tech
system. The incentive to do so for a big publisher would be large. Hire a few
ML engineers, build your own ad tech system.

~~~
majani
The biggest publishers already roll their own ad tech systems with white label
software such as OpenX, balancing out ads from third party ad networks as well
as their own in-house ads.

------
manigandham
This article, as usual, has no idea what it's talking about.

The first issue is that ad auctions are 2nd price, meaning that if an
advertiser bids really high, they still only pay the 2nd-highest bid + $0.01.
Of course the publishers wouldn't realize much from this. Second major issue
is cookies and scale. You can't get high-value bids if advertisers can't
recognize those users.

The industry is slowly moving toward quais-first-price but scale is a
fundamental problem, which is again why Facebook, Google, and now Amazon get
all the money and do really well with behavior targeting while even big
publishers struggle. Add in the new privacy regulations and this will only
further widen that gap.

~~~
denzil_correa
> This article, as usual, has no idea what it's talking about.

Are you talking about the article or the paper? The paper is published at the
Workshop on the Economics of Information Security (WEIS) with the conference
char being people like Bruce Schneier. Besides, the author is Alessandro
Acquisti and the details of their experiments are well outlined in the paper.

I understand that you see challenges, issues with their methods but you need
to perform your own experiments and make a sound argument to make any strong
statement. I'd be very cautious before I make a casual remark at a well
conducted study. The study may have limitations but this doesn't mean the
conclusions of the study are invalid.

~~~
samt
There is immense variation in programmatic ad pricing by publisher. Drawing
conclusions about the market as a whole, or about publishers not exactly like
the one studied, would be a mistake.

------
return1
anecdotally ( i turned off ads for my users and switched to contextual-only
since GDPR) non-targeted ads bring ~40% _less_ revenue. I suppose it varies
widely between publisher type , country etc. I do not believe their data is
representative, and i also think it is the wrong kind of data.

My hypothesis is that _advertisers_ overpay for targeted ads, but this is not
the right way tot test that. They would need to find data or experiment that
correlates advertising spend to revenue generated.

------
rustoo
this is quite interesting... here is the whole paper:
[https://weis2019.econinfosec.org/wp-
content/uploads/sites/6/...](https://weis2019.econinfosec.org/wp-
content/uploads/sites/6/2019/05/WEIS_2019_paper_38.pdf)

