Showing all posts tagged adtech:

Help, I'm Being Personalised!

As the token European among the Roll For Enterprise hosts, I'm the one who is always raising the topic of privacy. My interest in privacy is partly scarring from an early career as a sysadmin, when I saw just how much information is easily available to the people who run the networks and systems we rely on, without them even being particularly nosy.

Because of that history, I am always instantly suspicious of talk of "personalising the customer experience", even if we make the charitable assumption that the reality of this profiling is more than just raising prices until enough people balk. I know that the data is unquestionably out there; my doubts are about the motivations of the people analysing it, and about their competence to do so correctly.

Let's take a step back to explain what I mean. I used to be a big fan of Amazon's various recommendations, for products often bought with the product you are looking at, or by the people who looked at the same product. Back in the antediluvian days when Amazon was mainly about (physical) books, I discovered many a new book or author through these mechanisms.

One of my favourite aspects of Amazon's recommendation engine was that it didn't try to do it all. If I bought a book for my then-girlfriend, who had (and indeed still has, although she is now my wife) rather different tastes from me, this would throw the recommendations all out of whack. However, the system was transparent and user-serviceable. Amazon would show me transparently why it had recommended Book X, usually because I had purchased Book Y. Beyond showing me, it would also let me go back into my purchase history and tell it not to use Book Y for recommendations (because it was not actually bought for me), thereby restoring balance to my feed. This made us both happy: I got higher-quality recommendations, and Amazon got a more accurate profile of me, that it could use to sell me more books — something it did very successfully.

Forget doing anything like that nowadays! If you watch Netflix on more than one device, especially if you ever watch anything offline, you'll have hit that situation where you've watched something but Netflix doesn't realise it or won't admit it. And can you mark it as watched, like we used to do with local files? (insert hollow laughter here) No, you'll have that "unwatched" episode cluttering up your "Up next" queue forever.

This is an example of the sort of behaviour that John Siracusa decried in his recent blog post, Streaming App Sentiments. This post gathers responses to his earlier unsolicited streaming app spec, where he discussed people's reactions to these sorts of "helpful" features.

People don’t feel like they are in control of their "data," such as it is. The apps make bad guesses or forget things they should remember, and the user has no way to correct them.

We see the same problem with Twitter's plans for ever greater personalisation. Twitter defaulted to an algorithmic timeline a long time ago, justifying the switch away from a simple chronological feed with the entirely true fact that there was too much volume for anyone to be a Twitter completist any more, so bringing popular tweets to the surface was actually a better experience for people. To repeat myself, this is all true; the problem is that Twitter did not give users any input into the process. Also, sometimes I actually do want to take the temperature of the Twitter hive mind right now, in this moment, without random twenty-hour-old tweets popping up out of sequence. The obvious solution of giving users actual choice was of course rejected out of hand, forcing Twitter into ever more ridiculous gyrations.

The latest turn is that for a brief shining moment they got it mostly right, but hilariously and ironically, completely misinterpreted user feedback and reversed course. So much for learning from the data… Twitter briefly gave users the option of adding a "Latest Tweets" tab with chronological listing alongside the algorithmic default "Home" tab. Of course such an obviously sensible solution could not last, because unless you used lists, the tabbed interface was new and (apparently) confusing. Another update therefore followed rapidly on the heels of the good one, which forced users to choose between "Latest Tweets" or "Home", instead of simply being able to have both options one tap apart.

Here's what it boils down to: to build one of these "personalisation" systems, you have to believe one of two things (okay, or maybe some combination):

  • You can deliver a better experience than (most) users can achieve for themselves
  • Controlling your users' experience benefits you in some way that is sufficiently important to outweigh the aggravation they might experience

The first is simply not true. It is true that it is important to deliver a high-quality default that works well for most users, and I am not opposed in principle to that default being algorithmically-generated. Back when, Twitter used to have "While you were away" section which would show you the most relevant tweets since you last checked the app. I found it a very valuable feature — except for the fact that I could not access it at will. It would appear at random in my timeline, or then again, perhaps not. There was no way to trigger it manually, or any place where it would appear reliably and predictably. You just had to hope — and then, instead of making it easier to access on demand, Twitter killed the entire feature in an update. The algorithmic default was promising, but it needed just a bit more control to make it actually good.

This leads us directly to the second problem: why not show the "While you were away" section on demand? Why would Netflix not give me an easy way to resume watching what I was watching before? They don't say, but the assumption is that the operators of these services have metrics showing higher engagement with their apps when they deny users control. Presumably what they fear is that, if users can just go straight to the tweets they missed or the show they were watching, they will not spend as much time exploring the app, discovering other tweets or videos that they might enjoy.

What is forgotten is that "engagement" just happens to be one metric that is easy to measure — but the ease of measurement does not necessarily make it the most important dimension, especially in isolation. If that engagement is me scrolling irritably around Twitter or Netflix, getting increasingly frustrated because I can't find what I want, my opinion of those platforms is actually becoming more corroded with every additional second of engagement.

There is a common unstated assumption behind both of the factors above, which is that whatever system is driving the personalisation is perfect, both unbreakable in its functioning and without corner cases that may deliver sub-optimal results even when the algorithm is working as designed. One of the problems with black-box systems is that when (not if!) they break, users have no way to understand why they broke, nor to prevent them breaking again in the future. If the Twitter algorithm keeps recommending something to me, I can (for now) still go into my settings, find the list of interests that Twitter has somehow assembled for me, and delete entries until I get back to more sensible recommendations. With Netflix, there is no way for me to tell it to stop recommending something — presumably because they have determined that a sufficient proportion of their users will be worn down over time, and, I don't know, whatever the end goal is — watch Netflix original content instead of something they have to pay to license from outside.

All of this comes back to my oft-repeated point about privacy: what is it that I am giving up my personal data in exchange for, exactly? The promise is that all these systems will deliver content (and ads)(really it's the ads) that are relevant to my interests. Defenders of the model will point out that profiling as a concept is hardly new. The reason you find different ads in Top Gear Magazine, in Home & Garden, and in Monocle, is that the profile for the readership is different. But the results speak for themselves: when I read Monocle, I find the ads relevant, and (given only the budget) I would like to buy the products featured. The sort of ads that follow me around online, despite a wealth of profile information generated at every click, correlated across the entire internet, and going back *mumble* years or more, are utterly, risibly, incomprehensibly irrelevant. Why? Some combination of that "we know better" attitude, algorithmic profiling systems delivering less than perfect results, and of course, good old fraud in the adtech ecosystem.

So why are we doing this, exactly?

It comes back to the same issue as with engagement: because something is easy to measure and chart, it will have goals set against it. Our lives online generate stupendous volumes of data; it seems incredible that the profiles created from those megabytes if not gigabytes of tracking data have worse results than the single-bit signal of "is reading the Financial Times". There is also the ever-present spectre of "I know half of my ad spending is wasted, I just don't know which half". Online advertising with its built-in surveillance mechanisms holds out the promise of perfect attribution, of knowing precisely which ad it was which caused the customer to buy.

And yet, here we are. Now, legislators in the EU, in China, and elsewhere around the world are taking issue with these systems, and either banning them outright or demanding they be made transparent in their operation. Me, I'm hoping for the control that Amazon used to give me. My dream is to be able to tell YouTube that I have no interest in crypto, and then never see a crypto ad again. Here, advertisers, I'll give you a freebie: I'm in the market for some nice winter socks. Show me some ads for those sometime, and I might even buy yours. Or, if you keep pushing stuff in my face that I don't want, I'll go read a (paper) book instead. See what that does for engagement.

🖼️ Photos by Hyoshin Choi and Susan Q Yin on Unsplash

Lessons in Hiring

Some of the most insightful and succinct commentary on the whole Antonio Garcìa Martìnez debacle comes from an ungulate with a Classic Mac for a head:

the Macalope believes Apple should not have hired García Martínez only to fire him. He believe it never should have hired him in the first place.

I'm not going to go over all of the many (many, many) red flags about this person's opinions that should have at the very least triggered some additional scrutiny before hiring him. The reaction from Apple employees was entirely predictable and correct. Even if the misogynistic opinions expressed in his public writing were exaggerated for effect, as he now claims, there would always be a question mark around his interactions with female employees or those from minority backgrounds. At the very least, that would be enormously disruptive to the organisation.

Leaving that aspect aside for a moment: even if this had been someone with the most milquetoast opinions possible (and no NYT bestselling book in which to trumpet them), it's still not great that Apple was looking for someone with his specific professional experience — honed at Facebook.

This particular hire blew up in Apple's face — but it's extremely concerning for Apple users that they were actively recruiting for this type of experience in the first place.

I'll lay my cards on the table: I dislike the idea of search ads as a category, especially in the App Store. We can argue the merits of allowing apps to "jump the queue" of results for generic searches, but as it is today, you can buy yourself into a position ahead of your competitor even for direct searches on that competitor app's name. Where is the value to users in that?

Display ads in Apple News or Stocks, which are the other two Apple properties discussed, might be acceptable — as long as they are not too intrusive. I don't have as much of a philosophical issue as some do with Apple using first-party tracking data within iOS, precisely because those data are not available to other parties or to other platforms. It's easy to opt out of Apple's tracking, simply by not using those apps, and ads from there won't follow me around the rest of the web.

The lesson I hope that Apple takes away from this whole situation is not "don't hire people with big public profiles" but "users really hate sleazy adtech". I would hate for Apple to go the way of YouTube, which is becoming unusable due to ad load. I understand that Apple is trying to boost its Services revenue, and App Store search ads are a way to do that, but if it makes my user experience worse, that's a problem. Apple products command a premium in large part because of how nice they are for users; anything that undermines that niceness weakens the rationale for staying in the Apple camp.

The Wrong Frame

The conversation about the proposed Australian law requiring Internet companies to pay for news continues (previously, previously).

Last time around, Google had agreed to pay A$60m to local news organisations, and had therefore been exempted from the ban. Facebook initially refused to cough up, and banned news in Australia — and Australian news sites entirely — but later capitulated and reversed their ban on news pages in Australia. They even committed to invest $1 billion in news.

One particular thread keeps coming up in this debate, which is that news publications benefit from the traffic that Facebook and Google send their way. This is of course true, which is why legislation that demands that FB & Google pay for links to news sites is spectacularly ill-conceived, easy to criticise, and certain to backfire if implemented.

Many cite the example of Spain, where Google shuttered the local Google News service after a sustained campaign — only for newspapers to call on European competition authorities to stop Google shutting its operation. However, it turns out that since the Google News shutdown in Spain, overall traffic to news sites went largely unchanged.

Getting the facts right in these cases is very important because the future of the web and of news media is at stake. The last couple of decades have in my opinion been a huge mistake, with the headlong rush after ever more data to produce ever more perfectly targeted advertising obscuring all other concerns. Leaving aside privacy as an absolute good, even on the utilitarian terms of effective advertising, this has been a very poor bargain. Certainly I have yet to see any targeted ads worth their CPM, despite the torrent of data I generate. Meanwhile, ads based off a single bit of information — "Dominic is reading Wired" (or evo, or Monocle) have lead me to many purchases.

The worst of it is that news media do not benefit at all from the adtech economy. Their role is to be the honeypot that attracts high-value users — but the premise of cross-site tracking is that once advertisers have identified those high-value users, they can go and advertise to them on sites that charge a lot less than top-tier newspapers or magazines. The New York Times found this out when they turned off tracking on their website due to GDPR — and saw no reduction in ad revenues.

Of course not every site has the cachet or the international reach of the NYT, but if you want local news, you read your local paper — say, the Sydney Morning Herald. Meanwhile, if you're an advertiser wanting to reach people in Sydney, you can either profile them and track them all over the web (or rather, pay FB & G to do it for you) — or just put your ad in the SMH.

Hard cases make bad law. The question of how to make news media profitable in the age of the Web where the traditional dynamics of that market have been completely upended is a hard and important one. This Australian law is not the right way to solve that question, even aside from the implications of this basically being a handout to Rupert Murdoch — and one which would end up being paid in the US, not even in Australia.

Let us hope that the next government to address this question makes a better job of it.

🖼️ Photo by AbsolutVision on Unsplash

Advertise With The End In Mind

Even though I no longer work directly in marketing, I’m still adjacent, and so I try to keep up to date with what is going on in the industry. One of the most common-sensical and readable voices is Bob Hoffman, perhaps better known as the Ad Contrarian. His latest post is entitled The Simple-Minded Guide To Marketing Communication, and it helpfully dissects the difference between brand advertising and direct-response advertising (emphasis mine):

[…] our industry's current obsession with precision targeted, one-to-one advertising is misguided. Precision targeting may be valuable for direct response. But history shows us that direct response strategies have a very low likelihood of producing major consumer facing brands. Building a big brand requires widespread attention. Precision targeted, one-to-one communication has a low likelihood of delivering widespread attention.

Now Bob is not just an armchair critic; he has quite the cursus honorum in the advertising industry, and so he speaks from experience.

In fact, events earlier this week bore out his central thesis. With the advent of GDPR, many US-based websites opted to cut off EMEA readers rather than attempt to comply with the law. This action helpfully made it clear who was doing shady things with their users’ data, thereby providing a valuable service to US readers, while rarely inconveniencing European readers very much.

The New York Times, with its strong international readership, was not willing to cut off overseas ad revenue. Instead, they went down a different route (emphasis still mine):

The publisher blocked all open-exchange ad buying on its European pages, followed swiftly by behavioral targeting. Instead, NYT International focused on contextual and geographical targeting for programmatic guaranteed and private marketplace deals and has not seen ad revenues drop as a result, according to Jean-Christophe Demarta, svp for global advertising at New York Times International.

Digiday has more details, but that quote has the salient facts: turning off invasive tracking – and the targeted advertising which relies on it – had no negative results whatsoever.

This is of course because knowing someone is reading the NYT, and perhaps which section, is quite enough information to know whether they are an attractive target for a brand to advertise to. Nobody has ever deliberately clicked from serious geopolitical analysis to online impulse shopping. However, the awareness of a brand and its association with Serious Reporting will linger in readers’ minds for a long time.

The NYT sells its own ads, which is not really scalable for most outlets, but I hope other people are paying attention. Maybe there is room in the market for an advertising offering that does not force users to deal with cookies and surveillance and interstitial screens and page clutter and general creepiness and annoyance, while still delivering the goods for its clients?

🖼️ Photo by Kate Trysh on Unsplash