Tag Archives: data

The Basics: Audience Buying

Last week we looked at how publishers can take control of their own first party data in order to keep control of the sales process, extend their audiences, and offer additional value to marketers..

This week, let’s take a step back and revisit the path from buying media as a proxy for an audience, to being able to buy that audience itself.

Audience by proxy

RocketFuel's Audience Extension
Graphic from RocketFuel’s Audience Extension report.

Traditionally, advertisers were only able to target their audience indirectly, by trying to estimate who would be interested in a particular product or service based on a generalised demographic. This has supposedly helped advertisers to determine when and where to advertise—which publications, which venues, and what kinds of ads.

For example, want to advertise house cleaning products? Advertise on daytime TV or in women’s lifestyle magazines. Want to sell a Rolex? Target a wealthy and ‘masculine’ demographic in publications such as Forbes, or via outdoor on Wall Street and in the City of London. These may be somewhat dated examples but what they exemplify, apart from the reinforcement of age-old stereotypes, is a form of advertising based on certain assumptions about different kinds of people.

The idea is that, since you can’t directly buy the attention of a particular individual, you buy ad space where that audience is statistically more likely to be. And in many people’s minds, that is Advertising 101.

The rise of audience buying

The promise of digital for marketers has always been the increased ability to focus advertising messages to reach ‘the right person at the right time’, and over time this has indeed become more precise. But for a long time, digital marketing never fully managed to live up to this promise. Advertisers have still had to rely on publishers to reach audience segments that they deem statistically more likely to buy.

In recent years, though, things have started to change. We’ve seen the rise of ‘audience buying’: purchasing access to these audience segments directly rather than buying proxies for audiences. Thanks to the shift to digital and the increasingly sophisticated ability to track and store user behaviour, we have the ability to detect users’ activities, and to predict their interests based on patterns of behaviour.

In theory, this fulfils the promise of right time, right place, right person, right everything. The hyper-specific targeting of audience buying is more precise and more cost-effective, ensuring that consumers see ads that are far more relevant to them, and reducing wastage on ad spend for marketers. It also allows for a far more accurate attribution of ad spend, by making it clear which ad placements are truly driving engagement. In other words, it gives marketers full transparency, letting them see where their spend is going and with whom their message is resonating.

Fragmented industry

Audience TargetsThis shift has turned a hundred-year-old advertising industry on its head. It means that advertisers aren’t necessarily reliant on measurement and ratings companies to present them with their approximate audience segments, because they can create their own, collecting data from multiple sources and advertising anywhere that users can be detected and tracked. As we explored with the advent of publisher trading desks, publishers are also striving to reframe their own worth in this new context by exploiting their own rich user data, which they can sell within the audience buying model.

In some ways, though, this has led to such a fractured advertising landscape that we might wish for simpler times. The biggest problem is that the new and old models aren’t necessarily compatible, and yet many advertisers still try to use the old one and think audience buying can simply be tacked on.

For example, traditional TV advertising still mainly follows the old model while digital TV allows for much more direct audience targeting based on metrics like impressions and time spent with ads.

“The cost of using such different methodologies of buying selling and measuring TV and video is catching up to media companies that straddle both worlds,” says Lorne Brown, CEO of Operative. Brown continues:

Buyers and sellers often have separate media planning teams, technology stacks, sales teams, contracts and billing processes for the two worlds. As digital grows, it will not be sustainable to have two parallel processes. It also won’t be effective for advertisers, which will increase their expectations of measurable and effective cross-screen campaigns.

A cohesive model

At the same time, it might not be wise to ditch contextual targeting altogether because it can serve a different purpose. While audience buying is focused on the pre-existing behaviours of users whose data and habits have been tracked, marketers may still want to throw a wider net for growth on a larger scale.

Malcolm Coles of The Telegraph (UK) puts this in terms of ‘driving scale or becoming niche’:

a publisher has to choose between wanting to drive general engagement with their site and their brand, seeking growth over time, versus attending to the pre-existing audiences they have for, say, Telegraph Sport, or even a dedicated Arsenal FC page.

According to a white paper from Xaxis titled Harnessing Big Data for Audience Buying, a cohesive advertising model should have several ‘audience tiers’, ranging from ‘demonstrated affinity’ at one end (‘the consumers who have demonstrated through action a predisposition for the brand’), to ‘inferred affinity’ at the other end (‘the consumers who have not yet expressed affinity through direct action, but may gravitate towards the brand based on broader data such as demographics’).

The stronger the affinity with a brand, the smaller the size of a group, which means that targeting only users with proven affinity—in other words, only direct audience buying—may be insufficient for growth on its own. A good marketing plan, therefore, needs a cohesive model that encompasses both a hyper-targeted audience and a broader contextual reach.

5 signs programmatic advertising is taking off | Digiday

Well this is encouraging. I’m presenting at Digiday’s European Publisher Summit tomorrow on the future directions of Programmatic ad trading. This piece, which they ran on May 14th and only now popped up in one of my feeds, certainly backs up a lot of key points. That’s reassuring.

The only point in this piece that I don’t particularly dwell on in my presentation is the (social) platform aspect. Mainly because it’s an area I don’t know too much about. Except how to annoy people in the UK with with pictures of Barcelona whilst here for a conference.

The main points the author, Taylor Davidon, a venture capitalist with the agency-backed KBS+ Ventures, calls out are:

  • Marketers are getting smarter about programmatic.
  • Programmatic works, therefore it will get more dollars.
  • Native is going programmatic
  • Platforms have embraced programmatic.
  • Programmatic is going far beyond the banner.

“The real challenge around programmatic is not around using the pipes to send more banners,” he said. “Instead, it’s about marrying new formats with content, targeting and data to create a different model for ad deployment that’s native to the experience.” — Taylor Davidon

The one aspect of programmatic that he doesn’t call out that I pay close attention to is the use of and continued availability of increasingly rich and deep data. It think data + mobile will be the oxygen and fuel that will help the programmatic fire burn brightly in the next 12 -18 months.

5 signs programmatic advertising is taking off | Digiday.