Clean advertising | adactio

A(n expectedly) brilliant article from Jeremy highlighting some of the absurdities underlying our current privacy nightmare called "behavioural advertising". Most importantly:

...there’s a problem with behavioural advertising. A big problem. 

It doesn’t work.

Almost all of the data suggests that behavioural advertising would work, if the prediction model is accurate. The problem is that our predictive algorithms are terrible. Which isn't surprising. The biggest algorithmically-based companies in the world – Twitter, Facebook, et al. – still can't get predictive feeds to work, despite literally owning all of the data that would be needed for them, so why on earth would something as complex as consumer relationship mapping be possible?

Of course, that's not what we're told. We're told that online advertising is so effective as to be able to predict that you're gay before you know so yourself; to guess when you're pregnant; or to know ... After all, this is a trillion-dollar industry we're talking about! There has to be something more to it, right? Well, Jeremy puts it better than I ever could:

Suppose someone told you that they keep tigers out of their garden by 
turning on their kitchen light every evening. You might think their 
logic is flawed, but they’ve been turning on the kitchen light every 
evening for years and there hasn’t been a single tiger in the garden the
whole time. That’s the logic used by ad tech companies to justify 
trackers.

In other words, it's really hard to prove a negative. Any time someone criticises the industry, they point to vanity metrics like clickthrough rates as "proof", even though most of these metrics are devised by the industry, monitored by the industry, and (crucially) are near-impossible to categorically tie back to the ads themselves. 
 

The bigger smoking gun is that right now proof of the positive – that online tracking actually does lead to increased revenue – is also mysteriously absent. Sure, everyone knows about some successful online ad campaigns, but how many of those were successful due to a combination of virality, third-party talking points (such as blog posts and social media coverage), and old school contextual advertising (e.g. showing ads for a video game on a tech website)?

Jeremy makes a fantastic case in his article for why the blind adherence to behavioural advertising is terrible for the web:

  1. It's bad for users, because it serves largely irrelevant ads;
  2. It's bad for advertisers, because it wastes their time and money (not just in terms of serving ads poorly, but also in terms of the huge cost of developing tracking software and analysing the largely pointless results in the first place);
  3. And, of course, it's extremely bad for the web, causing page bloat, impacting performance, and resulting in terrible user experiences (cookie banners, GDPR consent forms, JS-requirements, cookie-walls etc.);
  4. Plus (secret option four), it's bad for the planet, too!

He also makes a great case for how we can go about improving things: ban third-party cookies, block cross-site tracking, normalise contextual ads online (y'know, the ones that actually work), and keep pointing out that the current model is just a bit rubbish.

The greatest trick the ad tech industry has pulled is 
convincing the world that contextual relevance is somehow less effective
than some secret algorithm fed with all our data that’s supposed to be 
able to practically read our minds and know us better than we know 
ourselves.

... if this mind-control ray really could give me timely relevant adverts, I
might possibly consider paying the price with my privacy. But as it is,
YouTube still hasn’t figured out that I’m not interested in Top Gear or
football.

I know it’s hard to imagine a future without tracker-driven behavioural 
advertising. But there are no good business reasons for it to continue.
 

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  • A(n expectedly) brilliant article from Jeremy highlighting some of the absurdities underlying our current privacy nightmare called "behavioural advertising". Most […]
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