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.
The average cookie doesn't belong to a high-value segment, explaining why the average benefit is limited.
Of course Mercedes wants to reach people shopping for a BMW and will pay substantially more for it. They are paying extra to reach a small subset of users.
But are targeted ads worth more? Yes, if I'm shopping for a BMW then Mercedes definitely wants to advertise to me. However, targeted ads don't seem to work as well as Google/Facebook would like advertisers to think. Mercedes can just advertise if I'm searching duckduckgo for BMW, rather than pay to advertise to me for 2 months after I bought a BMW.
Note that this is how targeted advertising currently works, I see ads for products I have already purchased, which is just wasted money.
While I agree with a lot of what you said (Mercedes can just pay for keyword searches on BMW or similar to still target and be effective with cheaper and "old school" methods). But I don't think a lot of the advertisements for already purchased products is wasteful.
See Coke (and what follows is overly simplified).
Everyone already knows who they are and their opinions on them. You might ask "Why does Coke advertise?" and it'd be a good question. Sriracha doesn't and they are a household name, surely Coke has more standing than them. Coke advertises not only to influence you from a young age (getting new generation of coke drinkers) but to ensure that you associate a good feeling with your purchase. This is apparent in car commercials too (especially in America). That BMW commercial isn't to convince people to buy a new BMW, kinda ridiculous when you think about it and the money that you have to spend on a car like that (consider how often you see commercials for high end cars that the general public can't afford). Luxury car makers sure do want you to feel superior about your decision to buy their car though (which there's connection with "my next car will be X so I'm superior).
Compare this to McDonalds, who knows you'll be hungry soon and wants you to visit them for your next meal. These companies have different goals, and of course their advertising will be performed in just as differing ways. Not all advertising is the same. Though I'm not sure this is the best strategy for Amazon when I buy a deck of cards, I don't need 20 more types. But maybe it is effective and that's why they keep doing it.
Yes, such second order effects are important and often overlooked. One thing is to confirm that the recent buyer's decision was right.
But also, these ads create a general impression of high quality for a brand, and for this to be effective, everyone needs to know about this. Status symbols can only be status symbols if they are recognized by both the people who can and cannot afford it.
Therefore ads of luxury items viewed by people who will never buy it is still valuable to the company because they set the stage for the status associated with the brand.
This is a second order effect of crucial importance that people often overlook when only looking at first order effects.
>I'm not sure this is the best strategy for Amazon when I buy a deck of cards, I don't need 20 more types. But maybe it is effective and that's why they keep doing it.
For standard playing cards, probably not, but for collectible card games, tarot cards, the blank cards used by game designers when building prototypes, card driven board games, etc. it might be significantly more effective. Those are all "cards" things where customers are likely to be repeat buyers or interested in trying other options.
They were laughably bad about distinguishing those sorts of different types/audiences in the past, and as in your example still aren't always good, but anecdotally seem to be gradually getting better. Maybe the gradual investment in development of machine learning and accumulation of data over time will result in less ridiculous suggestions in a decade or two.
Oh I fully agree with this. I think they keep suggesting playing cards because I have bought a ton of board games from them. But I just bought a single deck of bicycle cards and I get way more suggestions for cards than games or other categories of stuff I buy. But I think that is just a categorical distinction that they haven't made and might be hard for ML to pick up on because of the nuances involved.
If you are seeing ads for stuff you already purchased, it could be that the ad network tracked that you have viewed the item but didn't properly track the purchase.
The tracking isn't perfect and not every targeted ad you see is intentional.
'But are targeted ads worth more? Yes, if I'm shopping for a BMW then Mercedes definitely wants to advertise to me.'
Since you are likely already aware of Mercedes and have opted for BMW instead, I'd question the logic of Mercedes spending good money to continue advertising to you?
Let me know if I'm wrong but content providers are paid a flat rate for inpressions, are they not? It would be interesting to pay forward high value impressions. Would you start to see content providers fishing for ad whales?
No, most ad impressions are transacted in real-time through an auction where they receive bids from dozens of adtech companies representing thousands of advertisers and millions of campaigns.
Sometimes campaigns are bought on a flat-rate basis for a certain amount of impressions but as of 2019, these are just treated as any other bid in the auction and only override the bid price where there's danger of not meeting the final quantity.
Check out realtime bidding[1]. About 5 million impressions per second are bid upon by hundreds of ad companies. Yes they all see all the data, including IP, cookie, useragent, url, etc.
AdSense and AdWords work a bit differently and aren't exactly "real time bidding" in the industry terminology sense of the word. By that I mean they are real time and there is a bidding element, but AdWords for example stays under the Google roof and typically does not go on a real time bidding ad exchange. Contextual targeting is definitely kosher under GDPR, so Adwords and Adsense likely fall under that umbrella, for the most part.
AdX is Google's ad exchange. Over there, you do see a lot of data. However, I would bet that the personally identifying data is mostly scrubbed in the EU. User agent and page URL are not identifying enough, so they're probably included in the data.
It’s important to realize that this way of advertising is definitely important for advertisers, and adds a lot of value to them. It’s just that it’s not visible to publishers.
Having said that, 2009 is a long time ago, and I would like to see this study repeated before drawing conclusions about the current ad landscape.
Exactly. This study completely ignores the fact that retargeting through the Facebook and Google pixels is highly effective for advertisers. I have run retargeting campaigns with ROAS (return on ad spend) as high as 30x.
Without the ability to retarget, advertising revenue at both Facebook and Google would plummet. The majority of conversions for advertisers come from retargeting (behavioral) campaigns. Advertisers run cold traffic campaigns (non behavioral) just to be able to cookie a group of users interested in their niche of product or service. They then show a different set of ads to those that clicked on the initial ad and met some behavioral criteria - for example they read to the bottom of the landing page or watched more than 1/2 of a sales video. It is this second set of ads that results in most conversions from new customers.
So the entire model falls apart if we lose the ability to run retargeting (behavioral) campaigns. Most advertisers lose money on cold traffic campaigns, and make up for it with behavioral campaigns. When behavioral advertising stops, so does non-behavioral, and the whole Facebook and Google house of cards comes crumbling down in a hurry.
I spent many years of my life working on websites that used ads as a monetization method. I've spent thousands of hours working on projects where the intention is to "show more ads" or "implement more effective ads".
To be honest, I wish I spent that time looking for a cure for cancer instead. Or advertising for a cure to cancer. But I don't think showing ads to people is dishonest, a scam, or spying on people.
No, you don’t. When I put a Facebook pixel on a landing page, Facebook doesn’t tell me who they are or where else they have been, and I have no idea what they do on any site other than my own. I setup a campaign at Facebook that says “show this ad to everyone that spent more than 30 seconds on my landing page”. Facebook then shows my ad to only to those people if and when they return to Facebook (or Instagram).
That is the entire extent of retargeting campaigns. Comments like yours are nothing more than fear mongering. Unless you have installed malware on your computer, nobody is “constantly tracking” you.
> When I put a Facebook pixel on a landing page, Facebook doesn’t tell me who they are or where else they have been, and I have no idea what they do on any site other than my own.
You are not constantly tracking them, Facebook is. I understood the parent comment to be aimed at Facebook, not some individual advertiser.
Even Facebook is not "constantly" tracking people. They only track people when they are on Facebook, in one of their apps, or on sites that integrate Facebook's pixel/javascript. Granted, that is alot of places, but it is far cry from "constant" tracking.
That's kind of semantics. Sure, the Staatssicherheitsdienst in East Germany didn't see literally everything (I'm sure they would have, but the technology for widespread cameras just wasn't there - they did have about a quarter million people on payroll, though), but the people were constantly under surveillance.
I don't have any numbers on that, but for the average surfer that doesn't actively block tracking, they'll likely be tracked by FB or Google on > 50% of pages they visit. If you're mostly googling and chatting on Facebook, that easily sails past 90%, if you're on more niche content that is anti big-tech/adtech/surveillance, it's very low.
The money could have been eaten up by the advertiser.
If the untargeted ads lead to less valuable placements, then it will hurt the revenue of the advertiser.
Short term, both the ad network and publisher can get away with bad placement and make the same amount of money. It will take longer for the advertiser to see the loss in conversion and reduce their spend accordingly.
I think statistics wins here vs collecting and computing everything. Google has search intent so as long as you keep searching for something you are still interested. Same with Amazon. FB is more demographic based. I mean I guess you Google could just retarget you in every search query or in gmail but you might be off put when you get BMW ads when you search for vitamins. I've been retargeted by Amazon on FB but it's been pretty comical. Those ads have largely stopped so my guess is that Amazon did not find a positive ROI.
Search intent (behavioral) and demographic both suck compared to contextual. Contextual advertising is the "premium" ad space sold directly by publishers. An car maker says "I want to be in Car + Driver" and they put their ad there and it's the most expensive type of buy but it outperforms everything else by a wide margin.
The reason "targeted" ads exist is not because they work better, but because they create more inventory that would otherwise not have been sold.
Exactly. If the public justification for a behavior doesn't actually make sense and the behavior continues then there's probably another private motivation which is being satisfied.
I find this quote very odd. I mean, 4% advantage in a winner take all economy can be the difference between boom and bust.
How strange would it be for me to write the same article, wondering why elite athletes go through all the trouble they do to get an 'only 4% advantage'.
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.
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.
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.
Do you have any good links to industry sticks and studies for publisher/platform deal pricing scenarios or ballpark rates for those pubs in the several hundred thousand impressions/day range?
It seems disingenuous to compare something abstract like advertising to the process of adding value in manufacturing. They are concepts in two different classes.
I don't think it's disingenuous. The advertiser is willing to pay a lot more for the ad after the extra tech is added on. That's a pretty clear case that the extra tech makes the same ad impression more valuable.
I don't agree that it's value add since the advertiser pays the publisher directly, and the advertiser then slaps on all of the extra bells and whistles, so the impression isn't modified to be more valuable before it gets to the advertiser.
However, the comparison is not disingenuous. Even though I disagree with the parent poster, there is a clear perspective where the two are comparable.
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.
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). 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.
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.
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.
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)
I suspect the reason Netflix is better here is because Netflix goes out and chooses its content, and has few incentives to discriminate between what it shows me -- its incentive is largely to keep me using the service enough to justify renewal, however that happens.
Amazon, meanwhile, has an incentive to show whatever ads pay the most. In this case, it's something of a winner's curse situation -- the ads that pay the most are often the ones that overestimate the value of an ad placement, not the one who correctly estimates the value of an ad placement. And if the ads don't generate the expected revenue, as long as Amazon can find more suckers, there's never a feedback loop occurring where Amazon's poor ebook ad placement ends up aligning with anything they care about. So I get ads for a lot of self-published trash (either in the Get Rich Quick With Bitcoin variety or the modern day romance novel sort), Amazon gets money, and most of these authors need a very low conversion rate so what do they care.
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.
No matter how specific I enter a query, Netflix will respond with a scattershot collection of its own titles, quickly descending into utter irrelevance to my search terms.
They never, ever admit that they don't have what I'm seeking and then suggest alternatives.
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.
> 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.
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?
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.
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.
Even the paper says that the adtech companies themselves make way more than 4% more for behaviorally targeted ads. The paper's claim is that publishers get only 4% more revenue per impression, but they don't have to do anything to get that 4% more anyway.
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.
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.
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.
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.
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.
> 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.
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.
The article is what I said, but the paper isn't great either. Are those names supposed to mean something? The chair of the conference that the study is presented at is absolutely irrelevant, and I don't need to conduct my own experiments to discuss flaws in the process.
This wasn't a scientific study, nor is it well-conducted, because they looked at a single publisher over the course of a week in 2016 and are drawing conclusions for the entire market when they don't understand how big the market is and how the programmatic supply chain works. People in adtech deal with petabytes of data everyday. The fact that publishers don't see much revenue lift from behavioral targeting isn't a surprise, the whole industry knows it. So the study isn't completely wrong, but just looking at small picture that ends up aligning with the larger truth.
Why the rev is low isn't covered by the study, but the article tries to come up with an explanation. This is incorrect, which is what I cover in my first comment.
Agree that tfa is clueless. However even second price auctions cannot explain the data they claim to see. Any ad exchange these days has data showing publisher revenue delta of far more than 4% for cookie-able browsers.
It's not just oba... much of the non-oba demand running through programmatic requires a "cookie" for frequency capping or just basic anti-fraud.
Well the data here is also small and suspect. They need to separate mobile browsers and GDPR/EU regions that aren't available for OBA targeting anyway.
That's why I said scale (reach + cookies) is the fundamental problem.
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.
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.