There was a time when basic demographics were all that was needed to plan campaigns. We’d look at the reach and frequency based on age, gender and basic socio-economic factors. Publishers provided the data for us because they knew their audiences.
As you know, digital has changed all that. With the growth of programmatic we’re seeing a massive rise in the range of data that can be used—psychographic, demographic, purchase behaviour, social and, of course, search. With this change we need to shift the emphasis on who is responsible for determining audience profiles. It’s no longer realistic to assume this is the job of the publisher.
Publishers are trying to provide the answers, of course. They are creating personas of their audience, often using rich data sets, but they’re generally too broad to be of use to major brands with their own specific segmentation approach. How can publishers be expected to understand the audience nuances of each client, particularly when, increasingly, audience profiles will be dependent on the brand’s own behavioural data? To develop meaningful profiles they’d need to know from advertisers, in detail, what worked, what didn’t, and in what context. Even with the right technology, it’s unlikely brands or agencies will be too keen to share such information, for fear it would be shared with competitors.
For this reason, it’s likely the emerging model will see publishers highlighting broad categories, but large-scale advertisers increasingly supplementing that information with their own data and other unique data sets to develop bespoke customer profiles. Such information could be shared with their agency, or developed through in-house platforms.
AOL is already seeing this happen in Asia Pacific. Campaigns with Dentsu (for Honda Malaysia) and Vizeum (Ikea) among others have used the AOL Mobile Platform to develop and serve campaigns. Even though the actual buys happened through traditional insertion-order methods, the technology enables behavioural data to be collected and provide the learning to forge future media buys.
Over time, each brand will be able to see how their audience segments interacts online, based on the media chosen. Is one medium more effective than another at driving website visits, or online purchases, or email subscriptions? Does time of day, location or device influence those outcomes? It’s powerful information for brands, and definitely not the sort of data you’d want in the hands of publishers.
This story is set to take another turn. Until now adtech and marketing-tech have developed in parallel. One technology helped plan media campaigns, the other drove activity through owned channels, like websites and EDMs. Ad-tech focused on mass-media executions, marketing systems on one-to-one communications. There’s little doubt that, over time, the two approaches will become one and the same. Today, when a customer reaches an identified stage in a buy-path, a marketing-automation system will enact some sort of response—an email or a sales call. As the advertising and marketing technologies become joined at the hip, the triggered response could just as easily be a series of media placements, with a target audience of one.
This brave now world of advertising presents enormous opportunities and efficiencies, but only for those who are along for the ride. Relying on publishers to provide all the data you need will see you seriously hampered in your marketing efforts. Brands and agencies need to be using a mix of first and third party data to supplement their media planning, and over time it’s their first-hand IP that will provide the biggest opportunity for differentiation. If your brand is not already building the behavioural data to provide the intelligence behind future media buys there’s every chance you are building a dependency that will cost you dearly in the future.
Alex Khan is Asia MD at AOL