It's crazy how many apologists there are for Big Web Advertising!
So many commenters are giving the customer a hard time for realizing, "99% of my budget is spent on zero value, i.e. fraud."
The biggest lie the online advertising industry has sold is aggregate statistics. Of course a handful of traffic sources convert massively while the supermajority (99%) don't convert at all. Advertising intermediaries rely on the statistical mean to hide all the garbage in the gold. It should surprise no one that for the vast majority of customers, like Chase, conversion as a function of source is skewed.
I suspect too many ad tech companies rely on the ignorance of their customers to make money. They monetize the basic math of "if it's more than break-even, it's working"—in other words, their objective is to take as much ad budget as possible while still delivering a profitable conversion for the customer. By simple math, ad tech uses garbage inventory until the customer's profit is close to but above zero. It works, and you'd have to be a real blowhard to believe that it's not how the ad tech ecosystem works.
That ad-tech does this by laundering e-mail spam, blogspam and other forms of spam into Google AdWords: that's the real fraud. All those Googlers then go on to pretend like it's not happening.
I mean, what 400,000 sites do you think Chase was advertising on? Ones that really have to do with banking? Or just ones that, by some idiotic metric, have a keyword that ".equals('banking')"?
I would love for someone at Google's direct navigation ads (or whatever ridiculously obscuring name they're called now) to come out and say how "Nobody clicks twice [on spam ads] by accident." It's like they inhabit a make-believe universe. The ad exchanges aren't ignorant: they're facilitating the massive fraud of their own customers.
> I mean, what 400,000 sites do you think Chase was advertising on? Ones that really have to do with banking? Or just ones that, by some idiotic metric, have a keyword that ".equals('banking')"?
The reason a Chase ad ends up on 400K sites is not because all of those sites are contextually relevant, it's because of retargeting. A user goes to chase.com, gets pixeled, and then shown retargeting ads on what ever websites they happen to visit that are hooked up to the exchanges. This could be either a good or bad thing.
It's hard to tell from the article, but I don't think there was any change in Chase's advertising spend. My interpretation is that they are spending the same amount, but restricting bidding to a whitelist of sites.
If so, the fact that they don't see an impact in # of impressions means more about the ad exchange's bidding system and inelastic demand (or lack thereof) for inventory on those whitelisted sites.
Yep, as far as I'm concerned this article is a non-event without data showing this isn't what happened. "Business slightly tweaks marketing expenses" just isn't as attractive and rant inducing.
>Yep, as far as I'm concerned this article is a non-event without data showing this isn't what happened.
What other things should the article show "hasn't happened"? That will be quite a big list.
As the OP says, it's odd that people lean towards "everything is A-OK!". I guess there are many, many jobs that rely on the ad-tech bubble sustaining itself.
"Of the 400,000 web addresses JPMorgan’s ads showed up on in a recent 30-day period, said Ms. Lemkau, only 12,000, or 3 percent, led to activity beyond an impression."
I agree completely with your assessment. I run a website called HeyAmIFat.com where you can send in a picture of yourself and we'll tell you if you look fat or not in minutes. I often look at the huge companies advertising on my site and think "if they could see where their ads are being placed right now they'd probably realize they're wasting their money"
On the other hand this huge "fraud" is what makes Google free and has thus powered the information revolution that now looks like a pivotal turning point in human history. Hard to be all that mad that Google made all the worlds information freely searchable by ripping off dumb businesses...
I mean what do people do after learning they are fat and feel depressed? They buy crap to feel better. Maybe your website is exactly what advertisers need.
>I mean what do people do after learning they are fat and feel depressed? They buy crap to feel better. Maybe your website is exactly what advertisers need.
It is quite sad that anyone would consider this a business opportunity.
Swaths of consumer products are targeted at people with self esteem issues. Fashion, makeup, fitness performance, jewelry luxury and stats products of allmstripes. It's especially bad for young women who are bombarded with Photoshoped images of "perfection" and reminders that attractiveness = success and that sex sells.
At the risk of oversimplifying, making people feel a certain way in order to leverage that emotional state for the benefit of another is at the heart of a lot of marketing and advertising. Maybe it tastes worse when it is as blatant as the case above.
Saying someone is "fat" is an insult ( I think its considered an insult) you can be overweight without being fat. Fat has more todo with how you feel about your body then being overweight. I think you've found a niche market. ;-)
I agree with icebraining that it's not necessarily dumb for a business to advertise on less known or even irrelevant websites. It's the same difference between an ad flashing on a video wall on Time Square, or a billboard along a busy highway, or a poster hanging in a mall. Each has a different reach and purpose and with that comes a different price.
Google gives you the choice where you want your ads to be displayed; whether it's within the Google search results, or on websites like yours, or there are programs like Google Doubleclick where you can chose which websites you want to display your ads.
I think most of the criticism here doesn't so much reflect the ignorance of advertisers like the parent comment says, but ignorance of the people commenting how advertising works.
I often look at the huge companies advertising on my site and think "if they could see where their ads are being placed right now they'd probably realize they're wasting their money"
But are they? If they're paying per click, completely uninterested visitors won't cost them anything anyway. As dkuebric pointed out, we have no idea if those 395k sites were actually costing them any significant amount of money.
It’s actually both. The site determines what categories of ads can be displayed, and the viewer profile determines which in those categories will be actually shown.
How does this tracking really works? Is it really this sophisticated behemoth of AI research that makes it impossible to avoid?
Why is it that I get targeted as an balding middle aged man with erectile dysfunction when I'm not?
The adtech places I've worked at relied on cookies. They usually have massive networks of major sites and track your browser activity as you browse different.
However, the servers were always crashing and I was always wondering when the customers would figure out that they were throwing money away.
Age and gender seem to be two of the more significant variables in ad selection. Many women I know started getting ads for baby stuff once they turned 26 despite having never been interested in the topic.
What makes you think that they reduced their spend by 99%? They simply limited their campaigns' targeting to a whitelist of 400 sites, there's not any indication that they were spending equal $ per placement.
I'm not sure why you believe that aggregating statistics is some sort of lie -- in AdWords, advertisers are able to easily see the placement for each one of their clicks. It's not some big secret hidden from advertisers.
You are also confusing why and how much advertisers care about the content of the sites. The site's content is only one signal as to the quality of an impression. It's a proxy for quality, because it's a good indication that a particular user might find the ad interesting and relevant. It's not as good of a signal as the characteristics of the user. Why would Chase be interested in only advertising on "banking" sites anyway? It's pretty silly to think that it's somehow a big scandal if the website content isn't directly connected to the business of the advertiser. Advertisers definitely don't want that. What they want is a quality user -- Chase wants someone who is actively shopping for banking services to see their ad everywhere, but they don't want to waste an impression on someone who isn't. If I were guessing, they were likely aggressively remarketing on the entire network, and now they're restricting to sites. In other words, they were following users across the entire internet, wherever they could find inventory, and now they'll just follow them to the most popular sites.
You're conflating two issues -- brand safety and ad spam. The first is the relevant issue: "I don't care how good the user is, I can't have the NYT printing that my brand name showed up next to a terrorist recruitment video."
You're talking about ad spam, or "you charged me for this click but it was fraud from the publisher." That's not at all what the story is about. You're jumping to a conclusion that the now excluded websites were fradulent to begin with. Do you find it unbelievable that there might be 400,000 legitimate websites in the set of available placements for Chase's ads, without spam? Why?
You are mixing terms, Adwords isn't an exchange -- AdWords has inventory from owned-and-operated sites (Google, YouTube) and network partners (AdSense, AdMob, Google Display Network, etc.) AdWords doesn't sell any inventory from ad exchanges, it has its own network, particularly because it wants to maintain the quality of the placements. Spam is actively and aggressively policed.
Again, that's not what the article is about -- none of the big tech co's have been doing much to prevent ads from showing against certain types of offensive content -- especially content like hate speech, fake news, etc., because it's really difficult to identify correctly at scale. The media and advertisers have started caring because it's the cultural moment we're in right now, I guess.
Finally, it's not the case that "garbage inventory" is spread around, subsidized by the good stuff, in a money making scheme. Such a scheme wouldn't make sense anyway. High-spending, sophisticated advertisers know the conversion rate of the advertising, and they have a sense of the return on ad spend that they'd like. Cost-per-click is just a shallow metric in the market, if the real value wasn't there then demand would decrease.
Does the industry advertise until they break even? Of course, that's the market dynamics, and it's economically rational. Advertisers should, and do, spend up to the breakeven point (or the discounted lifetime value of the new customer acquisition). They do so because one should accept growing one's business by a marginal customer even if it's a breakeven proposition.
That's not to say that advertisers don't reap value from advertising, of course they do in reality (or at least, they always try to). I'm just pointing out that click auctions are expensive because the competition is willing to spend -- not because you're subsidizing spam.
> Of the 400,000 web addresses JPMorgan’s ads showed up on in a recent 30-day period, said Ms. Lemkau, only 12,000, or 3 percent, led to activity beyond an impression. An intern then manually clicked on each of those addresses to ensure that the websites were ones the company wanted to advertise on. About 7,000 of them were not, winnowing the group to 5,000.
They're pretty plainly saying that 388,000 sites were trash. How else to interpret no "activity beyond an impression?" I could print their ads on toilet paper and have the same result.
> Do you find it unbelievable that there might be 400,000 legitimate websites in the set of available placements for Chase's ads, without spam? Why?
Yes! I do find it unbelievable! The customer did! Everyone should! There just isn't that much valuable content on the Internet. There really isn't. Not valuable for you, not for me, not for Chase, not for anyone with a brain!
When a major sports apparel company sponsors a famous athlete to wear their gear on televised events, they are getting no activity beyond an impression. Doesn't mean the sporting event is trash. It's up to the advertiser to determine whether or not those impressions have value.
Isn't that the thrust of the article though? They narrowed their ad spend to whitelisted sites and have not seen a drop in sales. If the major sports apparel company stopped paying for endorsements and saw no drop in sales, you might be tempted to conclude that those endorsements are not good investments.
> They're pretty plainly saying that 388,000 sites were trash.
> How else to interpret no "activity beyond an impression?"
I'd argue the reverse.
Sites that generate a consistently high click rate are optimizing for people to leave. Sometimes the click target is obscured, so you'll end up with a high bounce rate. At the end of the day: If you don't prove the relationship between clicks and acquisitions you're going to just fund ad fraud.
Meanwhile, if the ad is in-view, and your marketing team isn't an idiot and managed to get 30 or so impressions on someone in a month (and enough someones in your market) then you'll be able to detect (by surveying) an increased brand awareness and preference.
This could be valuable because I suspect a lot of people who are considering another credit card will call in on the deal they remember, after talking about it with their spouse, than will click on an ad.
Of course, Chase doesn't ask people why they are signing up, so the only attribution data they have is clicks and post-click signups.
> I could print their ads on toilet paper and have the same result.
Yes you could, but that says more about the tools they're using to measure the result than the usefulness of toilet paper.
In this case, someone looked at their sources breakdown in mediaocean, it said the pay-per-click stuff was a winner. Well no kidding.
And when I say probably, I should say: I've worked with the ZO guys on the Chase account in my past life. This is probably what happened.
> An intern then manually clicked on each of those addresses
Even if the intern was paid, that's probably illegal.
Interns generally can't perform useful work for a business—they're actually supposed to cost the business money, time, etc. and cannot work on a project the business would normally pay someone to do.
1-5% click through rate on a display ad is pretty normal. If had impressions on 400k sites, the distribution of impressions per site had a long tail, and then you removed all of those that had no clicks, you'd expect to have a small set of placements with clicks. It doesn't mean they're spam sites, it's just math.
Yeah. It feels like the New York Times is lying with statistics and fearmongering about "toxic sites" to encourage companies to only advertise with big sites - something that, as basically the biggest name in news in the US, they're positioned to benefit from financially.
If 98% of the sites generate what is rounding error on your sales, then you measure that benefit against the risk that your brand gets associated with a hate speech site (maybe in the nytimes no less). It's math alright, but it means that the brokers are not adding a whole lot of value.
Even if these websites were legit, their traffic might be trash. If it's some sort of white supremacist website (the reason for restricting the # of websites), I am not sure that the sort of inbred white trash living in a swamp in Louisiana and consulting this website is a valuable customer base for Chase. Readers of wsj.com probably more so.
> So many commenters are giving the customer a hard time for realizing, "99% of my budget is spent on zero value, i.e. fraud."
This is something the Ad Contrarian hammers on a lot (http://adcontrarian.blogspot.com/). There seems to a lot of fraud and BS in the system, but it's to the benefit of most players in the system to ignore that. Even for many ad buyers, it'd be embarrassing for the CMO to admit to having thrown away tons of money on something that doesn't work nearly as well as it's said to.
"An intern then manually clicked on each of [the 12000] addresses to ensure that the websites were ones the company wanted to advertise on." - true hero of this article
Yeah, success of this entire pivot relied largely on this intern's audit report. I imagine that the intern had a massive list of 12,000 URLs and would click through them, taking care to note why the site passes muster or otherwise so that management can add a layer of justification to the final decision. Even at an average of 3 minutes per URL, that still amounts to >600 hours of repetitive and sometimes traumatising work. Remarkable that they only selected a single (unpaid?) intern to deal with this...truly remarkable.
You're assuming the intern actually did the job - that he didn't e.g. get bored a third of the way and finished the rest by dragging down the "No" field through the rest of the column in in Excel, and then changing a bunch of random URLs to "Yes".
My experience is that most people assigned with boring, repetitive jobs will either automate some of it or start cutting corners to avoid the work.
(In fact I'm starting to believe that the first runaway evil AI trying to take over the world will get stopped in its tracks, because it will not understand just how different the "on-paper" states of inventory and books in small and medium businesses are from reality.)
Many people do think exactly like that, but now realize that the output of such a task is often an input to another one. Garbage in, garbate out applies just as much to decision processes as to computers.
An as your boss I'd do simple random spot checks of some of those urls - you'd be under deeper review in a heartbeat.
The intern's requirements in this job are not "press every link presented" they are "find out who is not providing value for their worth" however the press dgaf about that.
The above is not advanced management techniques, it's basic check work.
3 minute per URL seem like a whole lot, it seems more likely that 7k of them were trash and were removed within seconds. A simple automated script/iframe with a "tinder" like interface of yes/no/maybe seems like the way to go here. Spend seconds on most, then minutes on the maybes.
Good point. Perhaps if you gave the job to a CS major, or an engineer they'd invest the time in making a time saving interface. But an intern in Chase? I doubt they would have the skills or the knowledge to do that.
Like, load the list into stumbleupon. I'm thinking about 6 seconds for trash, 30 seconds for interesting. So, maybe about 2 work days to remove trash and a few more to complete the rest. Could be done in less than a week.
For better results, have that intern gather the email addresses of those 12,000 pre-approved sites, and email them a personal ad placement buy offer, or request a media kit.
You'll find all sorts of personalization opportunities and you get to cut out the middle-man.
No. Billing is a huge pain in the ass. Negotiating price with each site is a huge pain in the ass. Building a reliable JS snippet that works everywhere and that these sites will trust is also a huge pain in the ass. Everything about dealing with 5k sites manually is a pain in the ass, which is why ad networks exist in the first place.
I'm sorry, I don't understand. Are you saying that there exists direct advertising libraries for web development frameworks and CMSes, and that they've possibly been around for a long time?
Sorry for the slow reply. I'm not familiar with currently available frameworks/etc. so I can't speak to that side.
The point I intended to make is that, in my experience, there aren't site owners going "I wish I could do this if only it wasn't so technically hard", they're going "I wish I could do this if only it didn't mean people would spend less money with me". Because on the other side of the equation, ad buyers (generally, though obviously not universally) don't want to work that way, and they're the ones with the money and therefore the power.
I'm not a developer myself but I've worked with developers who created various in-house ad-tech, and while this sort of thing may be too complicated to do for Mr Random Joe Blogger without a CMS plugin, it's really not something that is too technically complicated to be feasible.
This is definitely an interesting tactic, but this is a pretty poor article.
#1. Chase is claiming performance hasn't been affected, but it has only been a couple days since they made changes. With display you can't measure performance in only a few days.
#2. The author confuses the number of sites with the number of impressions. Chase is buying the same number of impressions - if everyone else followed this strategy it wouldn't hurt exchanges. It would have weird outcomes, but if the same volume is served the exchange makes the same amount (excluding data costs and how cpm would be affected, etc).
2 - The exchange would likely make more because the increased auction pressure from the same amount of advertisers trying to buy the same amount of volume (same demand) on a smaller list of websites (lower supply) would lead to higher prices being paid to show ads.
1 - depends on volume. high enough and you can get goodp-value of the population even in a few days
2 - still a win-win-win-win, Chase get more views for the same budget, few website of good content that attract good traffic get more money out of ads, bad website spamming keywords get less money and the exchange gets the same money but displaying the ads few times as the unit price increase so it has more margin.
1 - It's not really about the volume of impressions, but about typical attribution windows. Banner ads typically aren't measured on 1 day click attribution. In more DR oriented workflows the impression logs will be ingested into MMM (media mix models) to project the impact the banners had on conversions across all of your acquisition channels.
In non-online conversion paths (e.g. offline retail, call centers, etc) or branding campaigns, many are measured using offline lift studies or brand lift studies which take at least a couple months to show results.
2 - Not exactly. The prices would be driven up, meaning eventually Chase would get less impressions for the same budget. If both you and I used to buy 1,000 impressions for $5 across 100,000 websites who had a total supply of 2,000 impressions, but then we limit our list of allowable websites to 5,000 websites that only have 1,200 impressions... prices will rise.
The impact is not apparent when only I change my bidding strategy, because I'll buy 1,000 of the 1,200 impressions from the top tier websites, and you'll get 200 from them and then 800 from the bottom tier. But once we both change our bidding strategies, we're now both competing on the same 1,200 impressions. Prices will go up as we compete over them.
This is a simplistic auction, of course. In practice, the ad exchange values different sites differently... but this is just to give a rough mental model about how the increased competition on fewer sites will lead to increased auction pressure thus driving prices up and volumes down for each advertiser. The exchange and publisher will be happy, though.
> #1. Chase is claiming performance hasn't been affected, but it has only been a couple days since they made changes. With display you can't measure performance in only a few days.
It could be that neither display strategy was providing any value.
The fix to online ad fraud is obvious: CPA (Cost per action). If a signup occurs, then you pay for the ads. If a user pays for the service, then you pay for the ads. It would align the incentives of the advertisers (people paying for ads) and the ad networks (google). Currently it is the ad networks incentive to use CPC and to hide fraud by not releasing traceable ids, allowing clicks from bots/proxies/adsense holders and allowing ads on unrelated content which cause accidental clicks. CPA would incentivize the advertisers (people paying for ads) to commit the fraud by not reporting the action. This would be easier to maintain since the people paying for ads is a much smaller set. BUT - from my experience there would be almost no money in this system for Google since most of their income is from fraud.
All of advertising is selling possibilities, not actions at (relatively) super low rates. So that means there is more competition and a broader playing field.
My guess is that prices would go up dramatically if you started selling on CPA - and the ad tech business model would change significantly.
Seems like the best way to do this would be to hand curate targeted advertising and then charge a huge premium.
While the premise of the article is reasonable, the evidence is flimsy. This seems like an example of NY Times defending their turf. We've seen numerous [1] examples [2] lately of legacy media companies trying to drive advertisers away from new media sites and Youtube by discrediting sites as "fake news" and by running hit pieces on popular Youtube personalities.
I mean, just look at the author's latest articles. 5 of the last 6 (including this one) disparage advertising on new channels! [3] Targets include Youtube, Snapchat, Breitbart, and Google (in general).
The legacy media is just not well suited for the current state of the world. Breaking news comes first through Twitter now. Investigative journalism doesn't require a big budget to make high quality content any more. As for political commentary, many people would rather listen to a well-educated everyman craft videos on Youtube than listen to the millionaire personalities on Fox News talk about how the Democratic party doesn't understand the proletariat.
My mate worked at a giant ecommerce company, it would send hundreds of millions of e-mails a month... and with virtually no performance evaluation (only high level stats which are by no means actionable). It took a single SQL query to propose cuts to traffic in the order of 20% with ~zero loss in revenue.
I remember attending a talk, where this guy talked about their freemium app used by dozens of millions of users. Their in-app popups were cut by 30% or so without losing revenue, all thanks to a few simple if statements (they tried machine learning as well, but this did it).
One can only wonder how much of this excessive advertising there is, I guess it's mostly driven by absolute revenue numbers without much consideration for costs and efficiency.
I recently saw a talk by Foster Provost, a big ML guy at NYU. The main points of his talk were that using fine-grained behavioral data (like browsing history) is better than demographics (at least in his context: predicting ad lift), and he proposed a way to interpret the model (somewhat). I left feeling disappointed. His system for interpretation was super post-hoc and tenuous, IMHO. It felt like a computer scientist doing social science (because it was).
I think ML is great for lots of things, but there are still lots of problems with using it in systems with humans.
An example: if you do a Google search for "Amazon <some book>" then you'll almost always get an ad from Amazon. So Amazon pays for a click that would have happened anyway. Maybe Amazon does this to crowd out other advertisers, but maybe it's just the algorithm being stupid and nobody is watching.
It's not being stupid it's designed that way. "Gee that'd suck if somebody else bought ads for all your organic keywords. Sorry we don't have a better way to prevent that, you should bid on those."
Even if Google did provide a provision for blocking ads for certain keywords (and they do have one), who controls that system? Amazon is also a bad example since many 3rd parties affiliated with - and driving traffic to - Amazon buy those keywords.
Each individual advertiser on Google can provide "negative keywords," which are keywords that the advertiser would like to make sure they never show for.
Yes, you're right that buying one's own brand keywords is a defensive move. The idea that Google would show a relevant ad for a competing e-commerce site when a user is searching for "Amazon" isn't scandalous, it's the business model.
I think that's entering an area of ad ethics. Yet, its an ethical violation that companies like Google make today. If I search for "Wealthfront", I get an ad for Wealthfront, Betterment, and TDAmeritrade, in that order, before an organic result for Wealthfront. If Wealthfront didn't pay up, even though it is _obvious_ what I am looking for, the result I am looking would be buried. That's a protection racket.
Rank-based advertising, like in search results, is fundamentally unethical. To do it ethically would require perfect comprehension of what the searcher is seeking, so that you can prioritize organic, helpful results. Google never prioritizes organic results.
If I search for "Wealthfront", how likely is it that I don't know they exist and need help finding their homepage, and how likely is it that I want to read about the type of service they offer?
What? It's not a protection racket. Google is a private enterprise who is free to show whatever content they like on their page. Not showing your site is not illegal, nor is it unethical. A protection racket involves some illegal compulsion to pay for the protection. That's what makes it illegal.
I don't think you understand what a monopoly entails. Having a large marketshare is simply not the only qualifier. It's also not remotely anti-competitive. That's just not what that word means.
> An example: if you do a Google search for "Amazon <some book>" then you'll almost always get an ad from Amazon. So Amazon pays for a click that would have happened anyway
This is absolutely understood, and in fact deliberate. Amazon does not want another advertiser sitting above their top position in the organics. It weakens mind share, and risks losing a click.
Ok, admittedly my example was bad. However, the replies are all basically assurances of the form: "Don't worry, a human at Amazon made that decision, so it's ok."
I'll repeat that ML is useful, and I'll add that it's useful in human systems, but its utility is constrained because for the really important stuff you eventually have to have a person check its work.
In my experience it really depends on the vertical. For some things (ford cars) demographics don't work well, but for others (mercedes) demographics like household income and age perform really well.
I think their is so much input for rtb that it is prime for ML. Most exchanges have some basic ml auto-optimization, but eventually someone will automate almost the whole thing.
I work for a biggish company and sit near the marketing department. They report similar results, if not quite so dramatic. Advertising isn't incremental. Sometimes there's only so much demand for your product and you can only change that so much with marketing or promotion.
I'm not so sure, but I would love to be proven wrong.
The issue I'm seeing is that there are many orders or magnitude more potential content providers out there than people are willing to manually validate and white-list.
This might lead us to a situation where only the largest content providers/creators still get access to ad money which in turn will make it impossible for creators targeting a more niche audience to still have a chance in the market.
Case in point: lately I'm totally into science videos on YouTube. From the more mainstream "Space Time" to the now-not-as-niche-as-in-2012 "Cody's Lab".
While the latter doesn't share the former's production values nor budget, it's YouTube ad revenue that allows both to exist and to me personally, both provide equal value.
It concerns me that in the future, if this trend continues, only one of the two will have a chance to survive.
Niche creators can always leave the algorithms behind and work out ad deals on their own. Podcasting is an area where this is how it has always worked, and will continue to work.
Also, I think you need to change your perspective. Ads allowed these niche channels to exist, but these niche channels might not be providing value to the ad networks proportional to their cost. In essence: they're riding the gravy train. They're an inefficiency in the system.
They should work toward becoming valuable, or they should seek alternative forms of funding. Maybe people like you just need to be more open to the value-for-value model. If you like what they are doing, pay them for it.
If you watch an ad on their show but don't interact or otherwise act on it, you're part of the problem. Its like complaining about traffic while you're in your car on the freeway.
Niche creators never had a chance in the first place. The few pennies you get for thousands of impression don't cover the expenses to run the site or the time to write the content.
Tell that to the thousands of niche podcasters out there who sustain their programs through marketing partnerships.
Niche creators do stand a chance. They just need the opportunity to reach their audience with a degree of intimacy and trust that the horrific scourge of mainstream online video and corporate 'journalism' do not and cannot offer. Certain media can enable this for their viewers and others less so. It's no cliche to say that medium is the message in this context.
Native advertising in podcasting is proof that not all online advertising has to consist of bludgeoning ignoramuses over the head with colorful nonsense within the infinite scroll of their Facebook feed. It can be about legitimate respect for a brand and a brand's legitimate respect for it's engaged, targeted niche demographic. But at the current rate of things, the web will require another massive spree of innovation to fix the tragedies caused by Facebook and Google over the past 10+ years to ever reach this point.
Podcast advertising is really not the same as the ad networks on a blog or website. It's far more analogous to the advert spots that radio does.
It doesn't even need to be particularly native advertising. I've listened to a bunch of ads on Dan Carlin's Hardcore History that are completely unrelated to the subject of the podcast.
I believe you're mistaken. At the end of every Hardcore History episode, Dan Carlin recommends an Audible book related to that day's topic. It doesn't get more native than that.
Also, the comment I was responding to was using YouTube ads as an example, which are temporally inserted, very similar to podcast and radio ads.
When media consumption demands true engagement of both time and attention, the ad quality improves. Even the best niche digital video content on YouTube is too low-brow to offer a comparable experience to viewers. Again - the medium is the message.
A good thing for the big players, not the web. Everyone else (like me) me pays for their hosting with a few dollars a month in ad revenue will lose out.
Can we talk about the fact that "an intern" had to filter through 12,000 websites and make a judgement call for a second here?
Also - I presume the spending was the same in both cases - just focused. If so, the risk here is that you may miss out on a new up and coming blog "exploding" onto the scene. However, all it would take to "reset" is next quarter, "tasting" ads on 400k sites again, paying an intern (again) to filter the ones that led to revenue, and creating yet another list.
So if advertising on questionable sites bares the same results as advertising on respectable ones the bottom line is that advertising doesn't work at all.
Perhaps it's time to move away from profiling and return to the old days where the ads were correlated with the content/web site.
So, they run their campaigns with an open targeting and then they trimed the websites to the ones users clicked, and then, selected which ones had better brand value for them. That's simple optimization and they should have always been doing that.
The question arrises when you have to start from scratch. They would also have to start with an open targeting to learn what performs for them.
An important difference between buying ads on 400k sites and 5k sites is the margin for the middlemen. The money is going to get spent anyway, so the middleman needs to optimise his take.
The bigger the sites; the more leverage they have over middlemen. The lower the fees exchanges/ssps can collect - for big sites (ones people have actually heard of) the fee is effectively zero, and are needed by exchanges as loss leaders to attract any demand. Little sites with no leverage will expect to pay around ~70% to the middlemen (although not all of that will be disclosed).
True story: about 250 domains will get you above 98% of online population in most countries. This is plenty large enough for dvertisers to do all kinds of fancy targeting and optimisation within this pool.
Ad exchanges usually charge a fixed rate on revenue (like 15% or 20%).
If the spend is the same, then the ad exchanges don't make any more money.
There are other middle men, like the audit companies and the impression counters, but they end up making less money because they usually charge by the volume of impressions: Since the same budget will be spent over a smaller number of sites, the prices for those sites will raise and the number of impressions will go down.
The only people who win are the publishers of those sites who now have more money for the same users.
The article doesn't mention the precise methodology for reaching the 5000 sites number, other than some human filtering being involved.
The precise wording of another section is also vague, the 'cost of an impressions' could mean either their total Internet marketing expenditure is the same (thus 395000 sites were largely ineffective and merely exposed them to risk and complexity) OR that they've reduced their spending by around 98+% with no appreciable change in effectiveness.
The real question is how long has this been going on? I've seen these campaigns go on for years with worldwide clicks completely unchecked wasting a ton of $$. You can't trust automatic site placement but if you do, analytics will identify it quickly to exclude the loser sites.
This is just complete mis-management of paid media. Fire the agency or internal people for stupidity..
click is not a good measure of advertising value though. Clicks doesn't measure how many people see your ad and come back a couple months latter to buy.
They also didn't really mention if this is 100% of their rtb or just some. I'd be really surprised is they limited their retargeting and native to 5000 sites.
Typical pareto rule I've found. It'd be closer to 99% if all of their supply was sold into the exchanges, but most sites have a much more complicated waterfall to clear out their supply such that the premium inventory gets direct sold or sold into a private marketplace and only the remnant inventory goes into public exchanges.
In their test they had 12000 clicks, and decided they only wanted 5000 of them. So they miss 7000 clicks, or more than 50%. How is that the same result?
I could understand if they found that click from certain sites did not lead to new business for them. But that is not what the article says. It says they didn't want those 7000 clicks because they were from sites they didn't like.
It seems to me they should already have figured out which sites bring them useful clicks long ago, in an automated way. Isn't that standard procedure for advertising? Then there would be no need for moral judgements. Of course they are in their rights to shut out sites they don't like. But not everybody who browses such a site has to be a believer, among other things.
I think drawing attention to such automated matches of ads can only produce losers. The sites lose out on ads, but the companies force themselves to become political, needlessly driving away users from the other political spectrum. (Again, I assume it is in every companies rights to do so, it just seems bad for business).
> "99% of my [advertising] budget is spent on zero value,"
This has always been true for advertising. The difference is that before the internet there were zero methods for the advertising client to directly recognize this fact.
I believe that statement is wrong. 99% of advertising might not be worth the money spent, but it wasn't zero value. (if you spend $1 to generated $.50 that is advertising at a loss, but a much smaller loss than advertising with zero return). Advertising needs to figure out how to generate positive value.
The problem is there is two types of ad. The first is "buy this now", if the user clicks and buys it was a success, but that doesn't mean a failure to click is a failure because there is a second type of ad that I believe is more important: awareness. You advertise so that people know you exist - that way when they realize their need for your product you come to mine. I think the pay per click model that the web advertising has settled on is wrong because it doesn't well account for ads that you don't want clicked.
There is a reason McDonald's advertises on every radio and tv station they can every few minutes: it works. Some of those ads go to people who will never eat at McDonald's and if they could figure out how to save money by not advertising to those people it would be worth it. Overall though the return on those adds it large.
Exactly! Who in their right mind would deliver a report to their boss and say, "Its only been a couple days, but this drastic change has been successful!" But someone instead went to the NYT and said that same thing.
It invalidates the data? How so? Or do you mean conclusion?
Even so, there's nothing inherent with "a few days" that makes the analysis invalid due to sample size; that depends on the nature of the data. In my employment we are measuring changes hour to hour.
Because advertising is about perception. If I see chase ads every day will remember them in 6 months when I suddenly realize I need a new credit card - today I'm happy with my card selection and no amount of advertising will get a bite from me, but when that changes I might change to a "lesser" card just because I didn't think to check chase out.
thus they need numbers over months before they can state it worked.
Likely due to ppc arbitrage. It doesn't change anything in terms of spend and the return is the same, it's just that users click through different sources to get to the same destination.
With the magic of computers you could deliver 400k versions of your ad. Each tailored to the site where the ads are being displayed (or even more - tailored also to the specific user). Probably most of these sites have very distinct audience, so you could build quite targeted ads.
If you are just spamming the same ad everywhere, then I can certainly understand why it does not make difference if it appears on 5000 vs 400.000 sites if the ad display count stays the same.
The irony is that it is so easy to track online conversions with a simple pixel or server postback. It's called performance marketing, or affiliate marketing, in the sense that the advertising websites then become what is commonly called an affiliate in online advertising lingo. There really is no reason to pay for impressions these days, unless you believe in a mystical (and suspicious IMHO) quantity known as "branding value".
The NYT arguing that one should only advertise on 'high quality websites' is the equivalent to a retailer arguing that you should only buy in store because all the online stores are full of fakes. Fits perfectly in line with their 'we report the truth and anything else is fake' narrative.
I would wonder if the whitelisting is in-house or part of their contract? If it's in-house then the added cost to maintain the whitelist (in-house expertise), while not much comparatively, isn't nothing.
One would think this could be the perfect case for Big Data approach, web scale and all. But no - it is an intern manually clicking through 12K web sites. Somebody sell them some buzzwords, anybody?
More terrible tech reporting from NYT, why are they being spammed here so much now? Can it stop? Tired of the clickbait and paywall. I thought HN was against both.
If there's a book on the downfall of the NYT, I would love to know about what happened. The quality drop in the last 8 years has been truly shocking to me. Before the stopped their local coverage, their articles about the outer boros were just as bad as their tech coverage.
Go back and read old articles though and holy heck they were good. I feel like an old friend is gone.
So many commenters are giving the customer a hard time for realizing, "99% of my budget is spent on zero value, i.e. fraud."
The biggest lie the online advertising industry has sold is aggregate statistics. Of course a handful of traffic sources convert massively while the supermajority (99%) don't convert at all. Advertising intermediaries rely on the statistical mean to hide all the garbage in the gold. It should surprise no one that for the vast majority of customers, like Chase, conversion as a function of source is skewed.
I suspect too many ad tech companies rely on the ignorance of their customers to make money. They monetize the basic math of "if it's more than break-even, it's working"—in other words, their objective is to take as much ad budget as possible while still delivering a profitable conversion for the customer. By simple math, ad tech uses garbage inventory until the customer's profit is close to but above zero. It works, and you'd have to be a real blowhard to believe that it's not how the ad tech ecosystem works.
That ad-tech does this by laundering e-mail spam, blogspam and other forms of spam into Google AdWords: that's the real fraud. All those Googlers then go on to pretend like it's not happening.
I mean, what 400,000 sites do you think Chase was advertising on? Ones that really have to do with banking? Or just ones that, by some idiotic metric, have a keyword that ".equals('banking')"?
I would love for someone at Google's direct navigation ads (or whatever ridiculously obscuring name they're called now) to come out and say how "Nobody clicks twice [on spam ads] by accident." It's like they inhabit a make-believe universe. The ad exchanges aren't ignorant: they're facilitating the massive fraud of their own customers.