Intent, Context and Attention: 3 Signals Helping Brands See in the Dark
After Google’s cookie drama, you’d be forgiven for feeling like the lights have been switched off. But when discussing what’s next, there’s yet another major topic largely and mysteriously absent – the consumer. How does the public feel about the intent of people-based tracking and profiling online? And how will that help or hinder our response?
The International Association of Privacy Professionals (IAPP)’s found that 68% of consumers are concerned about their online privacy. While Nano’s own research confirms the same – with around 70% of consumers taking steps to ‘mask’ their data, via all the methods available to them, from VPNs to Incognito Mode. According to Pew, 81% of Americans are concerned about the intent of companies collecting and using their data, and 72% believe there should be more regulation to protect personal information.
The Past Doesn’t Repeat, it Rhymes
We sit at a tipping point where, according to eMarketer cookies are almost completely switched off – plateauing at around 13% coverage worldwide. The choice is quite simple – we attempt to replicate a token which brought us to this point. Or we push for something new, which the combined forces of public opinion, legislators and big tech are less likely to disrupt once again in future.
The good news is that, ever since Google’s on-off cookie breakup entered the news, in targeting as for measurement, an industry crisis has spurred innovation. Viable, and genuinely alternative approaches have emerged. Solutions continue to evolve which disavow profiling, and people-based data points completely. As such, they can genuinely be described as approaching future-proof – more independent of future disruption by big tech, more consumer-centric, and robust in the face of shifting privacy laws at large.
Something Old, Something New
Moving onto specific examples, what these offerings all seem to have in common is a considered, smart combination of the latest innovations – such as around AI and machine learning – with aspects tried, tested and trusted. That is, proven approaches from the past. In some cases, in the face of media’s ‘shiny new thing’ obsession, these were largely forgotten, only to return to the mainstream at this turning point for adtech.
Viewability Evolves to Attention
First, see the rise of attention as an example of consumer-centric advertising’s potential rebirth. Emerging as an evolution of viewability, attention takes in a combination of newer, more sophisticated measures – from time spent, to ad volume, ad to content ratio and other page quality features. Again, all of which add value for advertisers, and none of which surveil the individual consumer. Attention standardization is now on the horizon from IAB and MRC – itself a sign of attention’s widespread adoption and success.
Another oasis in what might otherwise be starting to look somewhat like a measurement desert is the rebirth of marketing mix modelling (MMM). MMM’s renaissance comes once again in response to signal loss, of which cookie chaos is just the latest example. And with people-based signals on the wane, there is a necessary shift from individual and seemingly deterministic data to more predictive models – especially since machine learning and AI is more than ever accessible to all. In a market where almost three-quarters of consumers are taking active steps to mask their data, is it any wonder that predictive models should come to the fore?
Measuring Direct Response ID-Free
Delving further into campaign measurement specifically – it is often said performance measurement is most seriously disrupted by signal loss. Versus brand uplift, this is certainly the case. However, here as elsewhere, there are innovations combining old and new, which are helping advertisers see in the dark. Using Circana’s point of sale data, for example, which is untethered from any individual or user profiling, Nano was able to successfully measure direct sales results for Heineken around a new launch in the UK.
Finally, there are some exciting approaches to targeting that have emerged, marrying the latest technology with traditional techniques. These include ID-free solutions that bring together intent targeting and context with classic media research methods, to verify audiences and manually vet machine learning models for accuracy.
As we face up to signal loss in its many forms – from IP addresses to location, link decoration to mobile SDKs – these new solutions, and new approaches to old challenges – are needed. And not just because the long-term forecast for cookie coverage stands at 13%. If the forecast also takes in consumer behavior, any alternative or workaround following a similar approach risks a similar fate all over again.
Despite this, the future is bright for adtech. Especially if it embraces some of the genuinely innovative, consumer-centric approaches outlined above. These techniques, more than ever, mean advertisers can still enjoy 20:20 vision, reaching consumers in a trusted, impactful way. Even as others feel like the lights have been switched off completely.
