With ITP, it's back to the future.

It’s been almost 5 years now since I started out in the (m)ad tech world, hell bent on finding a sustainable way to fund digital news journalism. 

The industry has pivoted, changed and developed in countless ways; but I must admit, it’s beginning to feel like I’m in a new release of ‘Back to the Future’ — waiting for The Doc to screech up beside me in the DeLorean and take me back to the present; or forward to the present. Who knows anymore! 

Now more than ever, with Apple’s second iteration of ITP, it feels as though the industry is having to go backwards to go forwards — looking for a way forward without the cookies that we’ve become so accustomed to. Without all that historic data, how can we possibly plan an effective campaign; let alone measure one.

We're data obsessed

The media buying industry has become obsessed with data and targeting. It’s already clear to see on the internet — and soon it will impact what you watch, listen to and walk past.

The allure of data is very obvious. If you can predict a consumers propensity to buy something, you can tip them over into actually buying — by placing the right advertising message and call to action in front of them at exactly the right time. Your media budget can become a sales funnel, rather than just part of the marketing budget — providing a halo effect on top of your wider sales channels.

And Robert’s your father’s brother!

So what do we mean by data?

First things first though — let me quickly explain what we mean when we talk about data in a digital advertising campaign. Data’s become one of those words that gets thrown around willy nilly, like blockchain or AI; and the truth is, means something different to each person within the industry.

When we create a campaign, there are usually two types of data signals — as they like to call them in the industry (nice to throw in a bit of the lingo, show you all I’m not an imposter after all!) — that people will be referring to:

1 - Audience signals

This is information including demographics, website analytics and social media behaviour. Globally, every second there are 32,000 Google searches, 10,000 Facebook likes, 9,000 YouTube video views, and 4,000 tweets. What this means is that every second there are 50,000 audience signals produced on these four channels alone.

2 - Environmental signals

This is information about external factors that may influence the mindset of your customers when they’re exposed to your financial marketing, including device information and location.

Is it the be all?

There are, however, problems with these types of signals — not least of all the fact that they’re stored in soon to be banned cookies!

For starters, they’re historic (Google only makes it search data available through its display network, two weeks after the fact). It’s all well and good knowing who’s looked at content relating to buying or doing something — but once they’ve bought or done that something, it’s not much good at all. Not many people who’ve just bought a car will be in the market for another!

A further challenge is the strength of the signal. Reading about international football does not make me an international footballer (as much as I do like to believe I should be!) — yet much of this data is based on such simple assumptions. Reading an article or visiting a website once is enough to land me in that historical data set. 

Now I’m by no means saying that all historic data is useless! Far from it; it can play an important role in certain campaigns. But it’s not the be all and end all. Maybe Apple’s crusade against the cookie isn’t such a bad thing — it could even be a blessing in disguise — the kick up the proverbial you know what that the industry needs.

There is another way

There is after all a 3rd type of data signal — which is often forgotten about — but is just as powerful, if not more so: 

3 - Media Signals

This is information about the particular content that readers are looking at before your ad appears. It includes keyword contextual targeting (e.g. keyword content on the page where the ad is running) and also category targeting (e.g. website or app category where the ad is running) — and is commonly referred to as contextual targeting.

“Nothing so special” I hear you say. “We’ve heard of this before, pretty standard stuff really” — and you’d be right. It’s been around for yonks, and is often considered less technical, or less advanced than its cooler signal siblings. But the beauty of it is, that unlike those siblings, it contains information about your readers intent — a look into the future.

We can gain a pretty clear understanding of a readers’ interests, but more importantly their mindset, by simply looking at what they are reading. If we can then match that mindset with the appropriate advertising, we might just create that halo effect we’re striving for. After-all, for almost any product, anyone is a potential customer — you just need to get them at the right time. If you’re a Byron Sharp fan — this must be music to your ears!

So in a time when it appears we need to look backwards, to go forwards, I ask you — is it time to think less about historic data stored in cookies, and more about the context in which you find your readers. 

It could just be the answer to the Apple ITP conundrum.

Is that the DeLorean I see?