This article discusses the Dutch national broadcaster NPO's switch from targeted ads to _contextual_ advertising, placing advertisements based on the content of the publisher site instead of user features of the person reading the page.
I haven't read the whitepaper (waiting on the English language version.) Where the increased revenue is coming from isn't really clear. It seems really unlikely they're increasing revenue by charging more per impression.
Cutting out the ad network could make up for it, but then this seems like a case of STER setting itself up as supply platform. It works great for large publishers, but doesn't really scale.
I still struggle to understand why people seem surprised when contextual advertising works better than targeted.
Targeted works on social media because that's the context, the user is looking for a distraction and ads can be as effective a distraction as your aunt's cat. Showing me ads for a new car when I'm reading about a terrorist attack is just the stupidest thing I can imagine. There's no context, no intent.
If I'm on a car site reading about the best new hot hatches and you show me an ad for your new hot hatch, then that's a whole different scenario.
It doesn't "scale", but advertisers get higher intent traffic, publishers can charge a higher premium, and the ads feel native so the customers might actually appreciate them. The extra effort is worth it.
...'cause _historically_ contextual advertising doesn't work better than targeted. And contextual targeting is hard, because determining context is hard and it can fail catastrophically (I recall the apocryphal story about a washing machine manufacturer's banner smack dab in the middle of a macabre news story about a toddler abandoned in a clothes dryer. Brand safety FTL.)
Your example on the "car hatches" is a really simple case and there's only so many niche publishers out there catering to specific audiences. That's how you end up with media companies like Vox and Gizmodo. And in terms of scale...well, go look at the Digital Media comscore rankings: https://www.comscore.com/Insights/Rankings
As for "advertisers get higher intent traffic", that simply isn't true. I'm not refuting your intuition 'cause it absolutely sounds right, but in terms of tracking and targeted ads knowing stuff like, "You left product in your checkout cart." is a waaay higher signal of intent.
> As for "advertisers get higher intent traffic", that simply isn't true. I'm not refuting your intuition 'cause it absolutely sounds right, but in terms of tracking and targeted ads knowing stuff like, "You left product in your checkout cart." is a waaay higher signal of intent.
For simple ecommerce flows, sure. But it isn't just intuition, having bought plenty of programmatic inventory over the years, there are perhaps as many non-online-selling advertisers using programmatic as there are straight "something in your cart" retargeters.
We used to get orders of magnitude higher conversions from websites where we did a direct buy aligned completely with the site's audience. The reason we didn't do more was scale - you can't do direct buys with every site, especially not when you already don't trust your buying agency. If we could, we'd have dropped programmatic entirely.
You also get agencies boosting their retargeting conversion numbers with BS like "view throughs". If your agency is trying to get retargeted view throughs in their hard conversion data, you're being scammed.
(In fact, I "accidentally" left the retargeting pixels switched off in GTM for a month. Made no difference to volumes or conversion rates - the reason they were turned back on? FOMO, plain and simple).
> cause _historically_
I'd argue that there isn't much "history" here to work on. The novelty of ad tracking is still very much there, and brands are still buying (and buying in huge scales, making up for precipitous drops in conversion rates), but when non-ecommerce brands stop being hoodwinked by buying agencies there will be a snap back.
Very few advertisers would want their content associated with a tragic news story like that. Not so directly as on a page with just that story anyway. During a national news cast? Maybe later in the program.
Tagging for the negatives is almost always more important than the positives.
Who tags though, publishers? I mean, you're right; I'm not being a contrarian for the sake of argument.
Contextual targeting probably will have a more interesting pitch in a post-third-party cookie Internet, but it's not going to be _the_ solution. There are already proposals for targeted advertising that may be more compelling/cheaper-to-implement, see TURTLEDOVE: https://github.com/WICG/turtledove.
OOC, what does "Scale" even mean here? is the OP saying you cannot infinitely serve ads because a given piece of content only attracts a finite number of viewers? or that there are a finite number of subject for a piece of content that can have relevant ads served?
To borrow your terrorist example, presumably there are no advertisers (that we permit and condone) who would like to advertise terrorism related products?
Do we have any reasonable numbers for what portion of actual web traffic is related to either product/service research or future purchase plans? My impression of my own browsing traffic is that it is probably about 50% by number of page loads.
You can cut the number of pages you place adverts on by quite a number when you can raise prices (in fact, probably quite a lot of news brands could cut them from their news stories entirely and just have them on their lifestyle content, especially on advertorials which often only need minimal configuration on their end). The issue with scale is the physical act of identifying and buying.
The best kind of contextual advertising is direct buy aligned with the content. For that, you need a big sales team cutting deals - you can't just tell your one man-band digital marketer to plug some demo info into a bidding platform and be done with it.
My programmatic spend was probably 10x my largest direct buy, but was a simple 20 minute phone call with the buying agency vs a month long BS sales cycle with the company I was direct buying from (although the lunches are nicer...).
I meant in context of the number of publishers that advertisers need to deal with to purchase impressions.
Cutting out the ad networks probably makes sense for Ster and NPO. I know nothing about Dutch media, but I'm guessing they're big enough to court large brands with big marketing budgets on their own.
NPO is the public broadcaster umbrella organization. It could very roughly be compared to e.g. BBC, with the big caveat that NPO itself does not create any content. Instead, its member broadcasters do. That's a relic of the Dutch pillarized system. NPO is funded both through taxes, and through advertisements. STER is the organization that handles the latter, and indeed it is a public body.
Presumably they mean that contextual advertising is hard to automate, thus requires consistent marginal human effort for each marginal amount of revenue. (Not sure that's true, but it's what "scale" generally tends to mean.)
> presumably there are no advertisers (that we permit and condone) who would like to advertise terrorism related products?
How about a handgun ad (tagline: "When seconds count, the police are only minutes away.")? Assuming the advertisee isn't in a oppressive regime, you can make money by selling them guns (or ammo if they already have guns), and do some minor bit of good by increasing the chances that the next terrorist is shot dead before they can kill anyone. (If they are in a oppressive regime, you've at least added one more bit of impetus toward violently overthrowing said regime, and hey, maybe they'll buy one of your guns on the black market.)
Edit: depending on the type of terrorist attack, you could probably advertise other emergency supplies like gas masks or fire extinguishers.
What about counter-terrorism products? I can totally whip up some copy for anti-virus or firewall software by referencing terrorism. It's not a direct connection, but probably strong enough.
How do contextual ads deal with language and geographic location? If reddit were to use only contextual ads does that mean that someone from, say Latvia, will never see ads that are locally relevant to them? I imagine most Latvians on reddit don't hang around the Latvian subreddit and advertising a local Latvian service on r/hairdressing isn't going to work. You also have to consider that if you just assume people's language then you'll end up with a lot of pissed off people, because you keep serving them content in Russian.
In other words: it's all well and good for the Dutch national broadcaster, but what about everyone else that gets an audience from a variety of countries?
Contextual advertising doesn't imply the system's completely ignorant of the device's detected language or geolocation. It simply means you're not employing a series of correlated requests across a stable identifier (browser cookie, IDFA, etc.) to model some outcome, e.g. probability to purchase, for a given advertisement.
Instead you infer a set of user features based on the domain/content _and_ attributes of the single request: device, geo, time of day, language, etc.
I’ve always thought that the “advanced tracking” touted by some in AdTech was:
1. Generally not that advanced (yes I searched for hotels in Florida and so yes I’m probably taking a trip to Florida... don’t need fancy ML to figure that out.)
2. Not that smart. (Hey we actually got back from our Florida vacation two months ago... don’t need to keep seeing hotel offers for Florida!)
It totally makes sense that just “dumb” targeting (show people adverts related to the content on the page they are currently looking at, which requires no tracking) might actually work better than all the black magic products companies promote.
It totally makes sense that just “dumb” targeting (show people adverts related to the content on the page they are currently looking at, which requires no tracking) might actually work better than all the black magic products companies promote.
This is exactly kind of "if all you have is a hammer, everything looks like a nail" that turns me off about AI/ML community.
This kind of page-content-based ad targeting did exist way before fine tuned retargeting (say, search or audience/segment retargeting). There are whole bunch of companies that serve this exact market. The reason a more complicated retargeting was created is proof that there is value in it, for advertisers. I am not claiming this is good for people - I am talking only about the business side of things.
> don’t need to keep seeing hotel offers for Florida
This is not for the lack of smartness in code - it is that the conversion funnel is so narrow that "saving that $30 per month, by not showing you the ad, on a $1m campaign" is not worth tracking and excluding. Although I do believe companies should take the extra effort to avoid the annoyance and be a good citizen - particularly once they have identified "the one real person who actually bought something" among 99 other bots/crawlers/untraceable entities. Not all ad companies appropriately value the real person and the annoyance caused to them. Some do.
> The reason a more complicated retargeting was created is proof that there is value in it, for advertisers
I'd argue the value was in it for media buyers. A lot of retargeted inventory is spent targeting people who are going to come back anyway. The agency then spins the numbers and presents it as if they were the only step in the process.
Some even take it a step further and conflate their retargeting with their prospecting numbers - there's a lot more uneducated advertisers out there for agencies to rip-off than educated ones.
Other than your standard ecommerce flows, online advertising is still an area of very murky attribution.
Which is why tools and reporting for incremental lift analysis need to be more widely used. It doesn't help that there are walled data gardens complicating things either.
Especially when your dashboards are prepared by the buying agency - always request the raw data behind the scenes. If it takes them a while to find it, there's perhaps a reason...
For sure. Although never attribute to malice what can be attributed to messy spreadsheet exports and databases cobbled together with shoestrings, gum, and vendor swag.
Oh definitely, but often you're paying them a pretty penny to have it all together, they might not be deliberately BSing you on the data, but they've probably BS'ed you before that they would have the data.
Ad companies being able to figure out that I just reserved a hotel room, so they can stop advertising hotels to me, might reduce the annoyance level. But I'm also pretty sure that, if I found out that they had done this, I would never patronize that hotel again.
I am talking about cases where the ad results in a click or view through and finally tracked to a purchase from the same provider. You shouldn’t see the same ad again or another ad to rent a hotel room from same hotel chain. I thought that was the case GP was taking about.
I am excluding the likes of companies like BlueKai (now Oracle) who facilitate trading the cookie to other companies for further targeting or completely different chain of ads based on a search click to another hotel chain
That said, all of this is getting killed by recent Safari and Chrome change of getting rid of all 3rd party cookies
Amazon showing me a selection of typical buy-once products of the kind I just bought is a depressing sight. They have infinite money and his is the best they can come up with?
Let’s say you buy a washing machine on Amazon. You’re not likely to need more than one. Amazon knows whether you canceled or returned your order.
So the only way it makes any sense is if Amazon is advertising on the chance that you’re going to cancel or return it in the future. Amazon certainly has those numbers. But do you think the chance you’re going to cancel or return it is so high Amazon should advertise the same product to you instead of something else you might buy?
> But do you think the chance you’re going to cancel or return it is so high Amazon should advertise the same product to you instead of something else you might buy?
It’s not either or - Amazon showed me grill accessories along with other models when I bought a grill. Regardless, I don’t really have a hard time believing that even a small chance of buying and canceling could make the expected value of showing that item higher than other items, even if that’s counter intuitive to you. I have a harder time believing that what’s shown is not well optimized and “obviously” wrong.
Any individual spot Amazon is advertising you something they could easily know you will not buy is a spot they could have instead used for an ad for something they do not have this knowledge about.
The point is that if you have multiple ad slots you can cover a wider range of buyers. For example, the chances that someone would click on a 5th grill accessory ad is probably pretty low if they didn’t click on any of the previous 4. But if they’re thinking of returning the grill they already purchased, they might be interested in a different model. Averaged over all buyers, the best strategy might well be to show a mix of accessories and other models.
Or, depending on the numbers, all grills or all accessories could also make sense. My broader point is that it’s perfectly possible the best strategy doesn’t line up with people’s intuition, which is why we use ML for recommendations in the first place.
I mean, sure, I don't have any scientific studies to back this up.
But I really don't feel like this is a case where "intuition might be completely wrong" applies—buying a $400 grill, and then just going back and buying 3 more $3-500 grills, just isn't something that people do on a regular basis. Same for vacuum cleaners, refrigerators, etc. And yet Amazon does regularly advertise these things to us after such large purchases.
The only logical conclusion is that it's cheaper for them (in the short term, at least) not to update their ad/recommendation algorithm to take into account the nature of large one-time purchases.
The question isn’t “do they do it on a regular basis” it’s “do people do it often enough that the expected value of showing that product is higher than something else.”
> The only logical conclusion is that it's cheaper for them (in the short term, at least) not to update their ad/recommendation algorithm to take into account the nature of large one-time purchases.
Is that really the only logical conclusion? I’d think that “I don’t know people’s buying behavior on Amazon well enough to understand why this happens” should at least be a possible explanation.
I'm trying to imagine a scenario where someone returns a single-purchase item and then purchases the same exact item as the result of seeing an ad for it. They're already aware of the item and if they want another one after return they're probably just going to exchange it because something is wrong with it. It's not even a sale and I'm skeptical that seeing the ad has a strong influence on whether a customer asks for a refund or a replacement.
ML is not some holy grail that always produces optimum algorithms. It depends heavily on inputs and on the assumptions, both explicit and implicit in the training data. My guess is Amazon does not have a "single-purchase item" model and it's not something the AI was trained to identify and so they aren't specifically excluded from groups of "similar-or-same" items.
I think it is far more likely that Amazon is optimizing the cost of development against the marginal benefit of not showing ads for single-purchase items than that this is somehow driving more sales.
1. Buy a large ticket item (e.g. furniture).
2. See an ad on Amazon for a different/nicer/better/faster shipped version.
3. Buy it.
4. Cancel the old order.
Is that a common pattern? No idea. But it’s not crazy to me that it happens often enough that it’s worth it to Amazon to show similar items to people who already bought them.
I bought a quality vacuum from Amazon and then continued to be aggressively advertised vacuums for months (on Amazon still) while shopping for things that honestly I could have used some advertising for to let me know what even existed in the space. Seems like not a great strategy for any involved party.
That would probably be a better strategy. But if you are looking at a naive, single variable, a prior purchase is the greatest single predictor of future purchases. If you know nothing else about a person, the fact you purchased one post-hole digger makes it more likely you'll purchase another, as opposed to some random other internet denizen for which we know nothing. Having worked in email marketing analysis before, this effect was surprisingly robust across categories. It implies you are the kind of person that could use such a product - most people aren't.
The worse is they keep showing me, say a stereo receiver even after they know I bought one, and it makes me feel like maybe I bought the wrong product when I see other products with better features/price advertised. These ads literally give me buyers remorse for the product that they themselves sold me.
The best argument for the usefulness/profitability of deep tracking is simple statistical inference.
As in if there are 10000 people that with browsing patterns similar to yours and non-trivial fraction of them one day show interest in a discount/service/trip then you are also likely to be interested.
It is the official explanation of how facebook/google can magically listen to conversation IRL that they were not supposed to hear: we simply are not as unique/unpredictable as we would like to think.
It was at least 5 years ago when I started to notice businesses "A/B testing themselves to death"
— "It makes no common sense, but increases sales,"
and then it does until it doesn't, and you are left with no idea what your client actually wants, and no idea how to get out of that "A/B tested to absurdity" situation
Yeah, I often wonder this... a/b tests only ever measure short term differences. What if the change you are making increased sales for a few months, but pisses off users in the long run?
This also seems to be an inherent danger with thinking that data science == machine learning == AI.
I don't want to fundamentally challenge the ŷ-centric approach approach of machine learning. But I do want to say that there's a lot of danger in taking it too far, and thinking that β̂ doesn't matter as long as ŷ is good enough. β̂ has a habit of not mattering until, very suddenly, it really matters quite a lot. And it's even more dangerous to think that an algorithm for generating formulas is somehow doing something intelligent just because you like what you're seeing in the ŷ department.
ŷ is the prediction you get out of the formula, β̂ is the coefficient(s) on the variables in the formula.
So, take the simplest possible model: You think that your dependent variable is linear in the dependent variable, and that the line passes through (0,0). That gives us a simplified version of the classic equation for a line, where we say that y is equal to x times some constant that indicates the slope of the line:
y = mx
In machine learning (or statistical inference), the variable conventions are slightly different, so it would look more like:
y = βx
And then, since this is machine learning (or statistical inference, or whatever), we don't know the true equation, we're just working with an estimate we've inferred. We stick hats over the estimated values to make it clear that they're estimates:
ŷ = β̂x
What I was describing, then, is which side of the formula you're focusing on. Traditionally, statistics has been all about scientific inference, and trying to figure out and characterize causal relationships. So you want to know "If I change x in some way, how will that affect the outcome, all else being equal?" β̂ is your tool for teasing those things apart. Machine learning is typically cast as being more about making predictions from observational data. ŷ is just the formal notation for describing those predictions.
It's pretty common in machine learning to say, "We are working with observational data, we're not worried about causality, so we'll only pay attention to the predictions." There can be value to that approach, but only to the extent that you really don't care about causality. Which. . . surprisingly often, β̂ matters, even when the people who built the model were trying to ignore it. It becomes especially important when you're using the model to make decisions. For example, when a company is using a machine learning model to try and identify candidates for a position they're trying to fill, they should absolutely be paying attention to what the model thinks about people who liked Lane Bryant on Facebook, and how that compares to people who liked Jos A Bank, and whether they really want things like that to be playing into how they make hiring decisions.
I see that but I think the broader point (and the point of the article) is that too often “success” in finding some less obvious link actually comes at the cost of overlooking the simple stuff. In the end there’s an argument that while neat the fancy ad targeting actually fails to meet the core business objective of maximizing ad performance.
My girlfriend is currently experiencing the dark side of smart tracking. Female who hit 30 and is in a stable relationship.
The ML just can’t figure her out. One day every ad is for dating sites, the next day it’s all babies and pregnancy, then engagement rings, wedding locations, more dating sites, a few days of houses to buy ... it’s like the algorithms can’t decide what life stage she’s in.
That's what you want. You don't want these assholes knowing your business. The classic example is when they start advertising a whole lot of pregancy stuff to someone who doesn't want to be pregant and for whom that might be a serious personal problem - advertising seen by others who she does not want to see that.
Dumb algos means freedom and privacy. Smart algos that actually work stuff out are dangerous and vile. Nobody gave them permission for that. Nobody complains about seeing ads not specifically tailored for them.
Confounding all of the targeting is one simple fact: Ad selection is based on what the advertiser is willing to spend, not on what the consumer wants to see. If a jewelry shop has extra ad budget and their target market is saturated, then the ad network starts serving ads to people who are married. Either that or they tell the jeweler to stop giving them money.
Just like she is right? Are you going to marry this guy or move on? Are kids in your future? How about a house, are you two moving in together? Probably all the same crap nosey family and friends want to know. Are advertisers an omnipresent nosey entity? Probably :-)
It actually makes a lot of sense when you think about. Sure, you may be interested in buying fishing gear, but not while reading an article about Tour De France.
One of the reasons Google have been able to make a ton of money on ads on google.com is because they are able to deliver contextual ads based on you search. Google isn't using targeted ads on google.com. Think about that for a second. The worlds most visited site and largest ad company is NOT displaying ads based on tracking users on their own main site. They are showing you contextual ads.
Search for "cement" on Google, you're not getting ads for the washing machine you looked at on another site yesterday. Google most likely have the data to target you and show you washing machine ads, but they choose to show you an ad relevant to your search.
Are we really surprised that contextual ads might generate more revenue?
They have more context of what you're after and what's more effective + the ad keywords limit the audience. But in your situation if there's any crossover between washing machines and cement that will bring clicks, you can be sure they know about it and will serve it.
That's a fair point, the ads are almost always localized at least. Still they're also not random, they are related to your search.
You don't really need much more that a GeoIP database to figure out where in the world you user is coming from, and that should be enough to deal with the location targeting. I'm not sure you'd need much more information about the users than that.
But they're still incredibly targeted. They're not just using info from your search, although that information is highly relevant in choosing what ad to display.
Retargeting is one of the stupidest things on the Internet that actually works, there's statistics on that. The only thing that's stupider is email spam where one hit justifies a million misses.
Something similar happens here as I understand it: in one out of N cases you may have added the thing to the shopping cart but didn't pay. Another possibility is that you might actually want to buy another one. Though this leads to comical situations like [1] but advertisers have no time figuring out which items are less likely to be purchased repeatedly. But then you might think of purchasing another toilet seat for your other bathroom after all, so... :)
>STER says that non-personalised ads are "just as effective", measured by number of clicks an ad attracts, though the click-through is not a complete analysis of effectiveness.
The fight against Google and Facebook (and soon Amazon) is still strong in the trenches.
How to fight the massive data hoarders that have no competition, and have their data locked down so no publisher can access it? Well you try to dismiss the value of data.
Then they make the mistake of evaluating the effectiveness of ads by the number of clicks and CTR... yeah... big red flag there.
It's easy to see a publisher get more money out by cutting out players in the value chain, and probably dropping the bidding of their inventory (doesn't matter if it's on cpm or cpc).
The problem always ends up with the inventory left out to be monetized, greed is a hell of a thing...
If they measure the number of click-throughs as an absolute and not a percentage, it might very well have been that more ads have been served because there were more online productions or they simply drew in more visitors. I think this is a matter of correlation implying causation.
Clicks and Click-Through-Rate are measures for direct marketing efforts, not advertising as a whole. You can have an effective branding ad and you don't even consider clicks as a main KPI.
Presumably because the ads are already hyper targeted, because the site is written in Dutch! Now imagine you run an English ad for say, a local micro brewery in LA. It's totally obvious that you don't want to waste money on people who don't drink, don't live in America, or are 12 years old.
Clearly there's significant diminishing returns to how specifically you target, but it's completely ridiculous to claim that untargeted ads are even a fraction as good.
I think the implication is that using the context of the page to serve ads to users (i.e. you're reading an article on beer, so I'm serving you an ad about beers) is better than using context about the user to serve ads (i.e. you're reading an article about beers, and I'm serving you ads about that one item you've searched on Amazon last week).
> I think the implication is that using the context of the page... is better than using context about the user
I think this is largely true. My favourite ad-supported site is The Online Photographer, a blog on photography which has ads about... camera equipment. No tracking or 3rd party script required.
You don't need to chase the user, retarget them to death, etc. Cool, you're tracking your user and showing them shoe ads over a tech blog, a news website and a pet care website. Doesn't this sound weird to you?
Micro-targeting is good money for the ad brokers, not the advertisers nor the publishers
One of the advantages of tracking users is to optimize your spend, taking into account your reach and the frequency a user see's your ad.
The result could be during one month you're seeing a Guitar Brand Ad in your favorite music blog, and you're a saxophone player. Yet the ad was shown to you 30+ times, when in reality it could have been capped to 10-12 times.
Some brands can afford this wastage, and factor in for it - hell some brands thrived with wastage (like those who grew in TV golden age, for example P&G) - but for a lot of them, this is too much.
Is it really wasted though? Back when I still bothered to watch TV with ads, I felt like seeing the same ad for the same product dozens of times per day had a brainwashing effect. It gets into your head.
At the very least it creates brand awareness and you're unlikely to forget about the company or the product. It also forms a strong association between the subject (in the parent's case, professional photography) and the brand/product.
Even if it doesn't result in a direct sale it might still be highly beneficial for the brand.
I mean if it wasn't, would we see so much product placement in movies and TV? Those are not proper ads, there's no call to action, the viewer has to go looking for the product if they like it. But it does wonder for brand recognition and prestige.
>Is it really wasted though? Back when I still bothered to watch TV with ads
The world was a very different place back then. Where the majority of "housewives" (as in the person who makes the decisions - and bought - all house purchases) were actually the wives, and ad jingles was part of the soundtrack of our existence. Attention was less split and focused mainly on TV, and fewer players had access to it.
And you're right, it did have a brainwashing effect, and I bet to this day you still know the lyrics or you can hum songs from jingles, or you know brand claims by heart. People underestimated that.
But still like you, hundreds of million of people never consumed, became customers, recommended or influenced any decision for a lot of those brands - but for those brands it was still worth it. It was part of their business model - mass media + a big share of shelf in large retailers. Coca Cola Company, P&G, Mars, and many other mammoths grew with this.
>I mean if it wasn't, would we see so much product placement in movies and TV?
The problem is that TV is different from the Internet, still to this day. Just because they share the same type of media (video), it's different how you watch and how you manage your attention.
A banner in a website is very different from a spot in break on a TV show. Even a preroll on youtube is different from a tv spot - because if you're not watching the tv spot and you're fiddling with your phone, the sound is there, and it grabs your attention for a fraction of time.
I'm not saying that high frequency doesn't work - it does work very well! Does wonders! But wastage makes it expensive, and it works differently depending on the media..
There are no primary exchanges for targeting content.
You can't 'put your ad near an article for beer' at any real scale.
In the old days, if you were paying $$$ for a spot in a magazine, you might be able to control where your ad was going to be placed, and certainly today, if you want to do that, you can find ways. Certainly you could buy ads on a 'beer blog'.
But by and large, this doesn't exist at any meaningful scale where you can just go out and buy 'a bunch of ad spots in articles about beer'.
Second - it's something, but still arguably not more effective than individual targeting. Most products and service have baseline demo. targets and that's quite important.
If you're L'OREAL you really don't want to be hustling your new eyeliner to middle aged men, that's pretty much a 'first order concern'.
Targeting does mostly work, we should not be in denial about that.
> and I'm serving you ads about that one item you've searched on Amazon last week)
As a side note, Amazon is not that big yet in the Netherlands so it would probably be something searched on Bol.com.
The problem I'm having with ads nowadays, besides that they are indeed often out of context, is that they are far to late and outdated. Because most times advertisements for a product start to appear when I already bought said item. So for me if they do tracing in a sense I'd rather have them double down on it and provide real 'value' to me in their ads. But I still prefer no tracking at all.
But they can’t predict the future so the ads will always be bad.
Targeted ads would probably work best in categories of things that you buy regularly, like snacks. I’m not sure how they’d get that sort of information though.
> Targeted ads would probably work best in categories of things that you buy regularly, like snacks.
If you show me an ad for something I already buy regularly, are you hoping it will cause me to increase my habitual amount? That doesn't really sound like an effective ad.
Nearly every beer drinker in the US has heard of Budweiser, yet they still spend millions on advertisements. It may not work on you, but they are definitely getting a return on that investment or they wouldn't keep doing it.
It will be partly to attract new (young) customers to their brand and also to reaffirm the brand image with existing customers.
You see this a lot with car commercials. You won't buy a car after seeing the average car commercial. Most of them don't even explain why you should buy a specific car over another. They focus more on the aesthetics. They sell you the idea of being part of something by driving a car of this brand. And even if you have already bought a car for that brand, seeing a commercial again reenforces your binding with the brand (given you feel positive about the commercial message). This works really well with cars as for most people they are emotional irrational purchases.
Maybe the core competency of advertisers is to convince businesses their services have value, not to convince consumers that products have value. The later is done only insofar as it's necessary for the former.
Also if I were to see ads for something unrelated in my city on a small LA brewery web site I would feel a bit suspicious. Instinctively I still consider websites as publishers of their own ads, so if they show ads for things completely unrelated to their service/page I judge them negatively for it.
If top HN comment completely misses the point on targeting and shows zero understanding what does it mean, and also considers "site is in Dutch" as "hyper targeted" what chance have an average marketer to properly set targeting goal for an ad?
Average site can profit more from untargeted ads than from the wrongly targeted ads set by the "ad experts", especialy after saving the costs of hiring such "experts".
Funny or not, you have to take into account HN context (ah!), where the great majority of users thinks marketing is a scam and hate advertising (here comes the downvotes...) - and they have reasons to feel like that. We've been flooded by bad professionals that give a bad rep to the craft.
They can profit more because they don't need any third party tech provider that take bites out of their inventory margin, or are not being forced into bidding their inventory and they set the prices they want.
It's smart on the publisher part, but they end up falling into 3rd parties because of the times they have inventory not being monetized (money lost).
For centuries publications sourced ads to finance them just by themselves. But suddenly we got those worldwide ad auction houses that monopolize the market, and now nobody can source their own ads anymore, because the buyers are all on the auction houses.
They shouldn't have more unsold inventory than if they got the alternative.
You make a good point about the marketplace dictating the market.
In my hometown there is a weekly newspaper that is still going strong, that can support a half dozen employees, etc. All with direct ads for B2C and B2B local businesses and legal notices.
It's interesting, as that business model would absolutely not work with an online platform, as it's a general interest publication that's highly local. There's no way for the local high-tensile fence contractor or well digger to generate ROI on Google. Ditto with the supermarket -- the weekly ad in the Sunday paper is very effective IMO, and superior to the online presentation in almost every way.
I think a lot of publishers preferred short term gains over a long term position... For some it was a conscious decision (as a strategy, or out of need), others thought of it as an easy cash grab.
Google, Facebook, they all gave credits/financed publishers to give them a perception of more reach, but the end result was the dilution of publisher brands and gradually lost their leverage.
Maybe Google, Facebook and Amazon were always going to be unstoppable forces in the market... but maybe, just maybe, if publishers stood their ground we would have a different narrative. Probably the cost would be too big, and many would fall... Who knows.
I guess it was just too easy and too good, free money, a way to convert inventory automatically without the need for sales teams and the pressure to have it maximized.
HN has poor understanding of ad-tech. If you aren’t in the industry, a quick coherence check is “if you’re right, you could be a millionaire next year by starting an ad agency this year, so why aren’t you doing it”.
Ads are like politics, sociology, or parenting. Everyone has what they think is an informed opinion but very few are informed. If one were to ignore every statement on ad tech posted on this site they’d be more informed than I if they read any.
Except that Mani Gandham fellow, who anyone else in ad tech will recognize as knowing the industry. I don’t know him personally except through his posts here.
But don't forget the FANGS are regulated by the USA and 18 year olds "drinking beer" (even serving troops) will lead to some serious necklace clutching by senators and congress persons.
Makes a good point not all countries regulate alcohol in the same way.
Most might not know this but brand x in the USA may be different to Brand X in the UK they may also have different names or even totally different brands - makes geo targeting really hard
I was talking about Belgium (note how that site is in Dutch and the number of 6 million approx. matches the number of people speaking Dutch in Belgium, while it doesn't match the number of people speaking Dutch in the Netherlands at all).
Why would it be a waste of money? If the market is such that there is an ROI for telling a global audience about your microbrewery, why not?
Most of the tracking issues are IMO about making more inventory available to platforms and have little to do with advertiser needs. I'm not in the business, but I remember in the olden days, the content-centric nature of Google AdWords was the magic.
In a perfect world, I'd see ads for brewpubs in my town. The reality is usually some sort of lame Amazon/Ebay/etc retarget attempt. These ads are low value and low revenue -- they are the equivalent of the Karate Dojo in a rundown stripmall.
>It's totally obvious that you don't want to waste money on people who don't drink, don't live in America, or are 12 years old.
This is a problem when you're trying to advertise in the garden of the advertiser's own making (ie Facebook). Otherwise, you're not going to be advertising your microbrewery on a children's blog.
>but it's completely ridiculous to claim that untargeted ads are even a fraction as good.
Advertising has never been truly "untargeted". I think the onus is on the targeted marketers to produce the data that their results are orders of magnitude better.
There's a pretty significant difference between tracking and targetting. It's pretty easy to limit an ad to a geographic area and target audience (to some degree of accuracy), you don't need to store any personal information to achieve this. However that is very different from tracking someone's identity to figure out their date of birth, nationality, and whether they drink alcohol.
You need to take into account what Google charges for giving you the opportunity for somewhat accurately targeted ads. Clearly, it can be cheaper to just show ads for everyone if Googles fees are to high for the value Google provide.
I'd really need to see actual numbers for this, especially as this is kind of contrary to the yearly report Ster released two weeks ago. In this they stated that while the first couple months of 2020 were more or less in line with their budget, they dropped to below budget after corona. I have some trouble believing they made a budget based on a 60% increase from the preceding year.
Also, I don't know all of the details here but selling hyper targeted ads requires to pay for a direct sales team. This adds to the cost and lowers the profitability. There's a reason FB/Google ads are so lucrative.
Also noteworthy is that the Dutch government has decided to seriously limit the amount of ads on NPO TV channels and websites. No ads before 8 PM on TV, no ads at all on the websites.
I don't think they implemented the `no ads before 8PM on tv` yet. I'm actually surprised about how open they are about advertising costs per second for each block on the npo1 channel [1].
Yes, my wording was a bit sloppy, apologies! Should be: the government has made plans to ...
Interesting document! There's a lot of information in here that I never really realized.
Looks like on any given day, you have an opportunity to be exposed to about 3 hours worth of commercials.
Further, total revenue from ads tops around 65,000 euros on a week day (on Tuesdays, it seems), much less on weekend days as more long-form programs are scheduled on those days. (The NPO does not interrupt shows for "ad-breaks"). On the other hand, there are some sketchy schedules, like the 6 PM news is a 15 minute thing sandwiched between two 8-minute ad blocks, and the "sports news" is a 5 minute update sandwiched between two 5-minute ad blocks.
These are the stats for the NPO 1 channel, which is the flagship channel for the NPO and bound to bring in the most ad revenue. If all days were to bring in this much revenue, it would mean a revenue of ~24 million euros a year, meaning
a little bit over 8 NPO 1's would be necessary to bring in the revenue the STER claims to bring each year (which is 200 million euros).
I must be missing something..
Update: Ah, the stated price is for 30 seconds of ad time, rather than the price for the full block.
Update2: Recalculating, the daily top comes down to around 675,000 euros, meaning around 246 million euros a year.
I don't speak dutch, but does this mean that cost on average 1000 euros for a 30 second ad? Or is it per minute? (it as 30" on top not sure if it is minimum block you need or per 30 seconds)
I would expect a lot more to be honest! (I know it changes and I bet those values around some specific events to be bigger, but still)
The price list is indeed for a 30-second television ad. However, it seems like you can't just buy one slot, you need to spend >€30k before they start to do business with you.
According to the report, online advertising revenue accounts for 5.351.000 EUR while TV did so for 144.365.000 EUR (2019). Thus the impact of online ad revenue rise seems relatively small.
In essence they cut out adtech middlemen who rake up to 70% of the ad revenue for themselves to run the real-time bidding which underpins tracking-based ads, and sold less effective content based ads but, by taking the revenue all for themselves, ended up way ahead.
I'd need to see the site before and after to confirm but maybe it is due to the faster page load speed? Tracking scripts these days are quite heavy and really affect loading times (especially on mobile)
I don't get why people are viewing user-based and content-based signals as two totally separate things.
Aren't most ad providers using both to serve ads?
Some people here are saying of course basing ads on the page will work better, and hence tracking cookies (or for some, even ML/AI) are useless... if that was the case, why are all these different players building all this infrastructure and developing these complex models? Just for fun?
Clearly, knowing that this is an article about pets helps. But knowing that you've been specifically reading articles about dog food gives you that extra information to serve particularly relevant ads (rather than say, display hamster cages).
Wikipedia tells me it's mainly funded by tax money 800 millions euros, coming up to about 45 euro per Dutch citizen, with supplemental income from ads (200 million),
They are partly funded by people's taxes. Commercials have more restrictions on them than on non-public channels. A maximum of 10% of airtime can be a commercial (on a yearly basis), with a 15% max per day. Commercials can only be before or after a program, not within. And just like commercial channels, you cannot sponsor news programs.
Yes, but the government doesn't want to spend too much tax money on it, so it operates semi-commercially. I'd rather they cut commercials, cut one of the three channels, and focus on content that the commercial channels can't or won't broadcast with the same level of quality.
Everybody knows that bad targeting and bad ad quality results in a temporary bump in revenue. This is because there are short-term quality assumptions baked into the advertisers' bids. Eventually the bad quality cycles back through the market and prices fall.
Within Google I saw several post-mortem reports where the "impact" was extra revenue, not lost revenue. As in, due to an outage of the xyz subsystem, we booked an extra $$/minute of ads revenue. Everyone knows this is bad, not good.
My favorite Dutch blog, tweakers.net, also does personal ads. I never ever clicked on them, I don't know what they are smoking to conclude that I'm interested in what they offer. They also have a "pricewatch" section, and boy have I clicked on their recommendations often. They are usually spot on! Of course they are contextual and geared to what I want to buy and searched for. If only they'd do the same with their news articles.
I don’t understand what is going on with the graph they present at all. What is the cyan line? What are the bubbles with percentage changes in them? Why is there a “+18%” bubble right after the huge dip in the cyan line past the “Covid market shock” label?
I think the bubbles are maybe “revenue increase per month” but what the hell is the cyan line?
As an old time adsense publisher I remember when they made the switch. Everyone revenue/click rate dropped. I thought perhaps in time this would improve but it kept dropping. I guess google believed they could sell more to ad buyers with an ml approach regardless of the results.
hype and a huge amount of fancy jobs at stake who know how to keep themselves employed. Take another example, Cambridge Analytica's "psychographic targeting". There's no solid scientific evidence that it actually works. Yet the media and press, as well as CA themselves have somehow convinced themselves that they're the real world version of James Bond's spectre
STER mentioned in the article is NPO's ad agency. The whitepaper is available on STER's site: https://www.ster.nl/onderzoek/een-toekomst-zonder-advertenti...
I haven't read the whitepaper (waiting on the English language version.) Where the increased revenue is coming from isn't really clear. It seems really unlikely they're increasing revenue by charging more per impression.
Cutting out the ad network could make up for it, but then this seems like a case of STER setting itself up as supply platform. It works great for large publishers, but doesn't really scale.
Totally related: expect to see more if these articles. The demise of third-party cookies is coming and groups like W3C's Web Advertising Business Group [https://www.w3.org/community/web-adv/] and efforts like Chromium's privacy sandbox [https://www.chromium.org/Home/chromium-privacy/privacy-sandb...] are picking up steam.