By Amy Fox, product director, Blis
The upcoming cookie apocalypse is leading advertisers and their agencies to reconsider tactics and techniques from the past, however, the key to succeeding will be to dive headfirst into bold and ambitious next-generation technology and new ways of working.
Advertising doesn’t need to be one-to-one to be personal, nor to deliver solutions that compromise on performance, scale or privacy. It’s time for marketing to look to the future, rather than continuing to dig in the past.
In the era of the cookie, success was built on the back of massive data sets of personal information flowing through the ecosystem, allowing marketers to track people across their entire online life. However, we are facing an impending data drought, beginning imminently and accelerating over the coming years, that will change everything. Evolving privacy legislation and platform changes by the likes of Google, Facebook and Apple means that very soon there will be less data available, not only to brands but to the entire ecosystem.
Yet as daunting as this might sound, this is actually a once in a generation opportunity to change the way that we, as an industry, define what an ‘audience’ means, and how ‘personal advertising’ can continue to deliver value. The key question is going to be, how?
What brands should be asking
2021 is going to be a year for marketers to reconsider how they find, build, and target audiences and how they embed customer insight into the heart of every brief.
It also means brands should be enquiring about just how future-proofed their suppliers are. For instance: will the partner be able to operate in a post-cookie world and are they at risk of future regulatory or browser changes? Can they offer a credible privacy-compliant solution at a scale that will perform well enough to deliver the outcomes they need?
Three (flawed) solutions for a post-cookie, post-device world
The ad tech ecosystem has many options for operating in a world with less personal data, with the various players gravitating around their preferred horse to back. However, marketers need to be alert to both the good and bad aspects of each potential route to avoid falling into pitfalls as our industry recalibrates.
Watch, wait and see: Many companies have not evolved their strategy and are continuing to rely upon pervasive 3rd-party cookies and personal identifiers. Although this will be the least disruptive option, in terms of technology changes, it’s also the most naive. With Apple placing their identifiers, IDFAs, behind a strict opt-in choice that’s likely to have a low opt-in rate and with Google removing 3rd-party cookies from Chrome in 2022, companies choosing this path will see their reach and measurability plummet..
Unified IDs: Others in the industry are pinning their hopes on the adoption of universal, open or unified IDs. These cross-site tracking solutions are ultimately based on a consumer’s personal information – an email or phone number that they’ve shared with the site on login. However, most sites will not have a deep enough relationship with the user to garner this trust, meaning that the scale of these identifiers will be limited. Furthermore, Apple has clarified that across iOS, such identifiers will still require opt-in consent, meaning that universal IDs will primarily serve as a 3rd-party website cookie replacement. Many are raising the question – does trading an anonymous cookie for one based on your actual email or phone number in fact go against the spirit of where users and regulators want to be?
Contextual targeting: This is a privacy-friendly solution that is having a renaissance at the moment, as it doesn’t require personal identifiers – you simply target pages or sites based on their content. However, this provides only a one-dimensional view of a consumer and there’s a reason most of the industry evolved past it over a decade ago: it simply doesn’t perform well enough. Marketers don’t just want to reach people browsing the latest football scores, they want to reach young, health-conscious sports fans who routinely go to the gym. It is becoming increasingly clear that context alone isn’t the answer to today’s challenges.
All of the above options will play a part and continue to have their uses in a post-cookie world, but alone they are not enough. Marketers must find smarter ways to leverage both the opted in and anonymous web in order to run effective and high performing media campaigns in a post cookie world.
A fourth way forward
Blis sees an additional possibility. Modern machine learning and massive datasets mean we’re capable of consumer analysis in a way that was never possible a decade ago. By looking at a myriad of personal and non-personal data signals and finding out what makes an audience unique and different, we have built a technology, with location intelligence at its heart, that can map precise audiences built from cookies and device identifiers through to non-personal factors that represent them and similar consumers.
These dynamic audiences are an ever-evolving, multi-dimensional snapshot rooted in location, context and time. Critically, they don’t require any personal data to target and execute media campaigns and can scale across almost every programmatic channel. Best of all, they perform like the highly personal audiences marketers are familiar with.
At Blis, we currently see GPS-based movement data from over 1.5 billion consented mobile phones every month, over 160 countries. This is a huge pool, and even facing the reductions ahead, we will still be looking at one of the biggest ‘panels’ of opted-in, accurate and useful data across the entire advertising spectrum. This location panel goes well beyond the small sample sizes seen with more traditional surveys and market research studies, and past the problems of bad assumptions and inaccurate responses based on browsing data, to paint an accurate and valuable picture of how consumers move about in the real world.
We start with a seed audience derived from precise and directly observed location behaviours, before various offline and online data sources are overlaid to build a comprehensive view of the characteristics that make an audience unique. By combining these signals, whether it’s where people live, what they browse, or their average income, together with our real-world movement data we can understand consumers and their behaviour better than anyone else in the world. Our machine learning models use these signals to build an hour-by-hour snapshot of high indexing targeting criteria that uniquely differentiate this audience from the rest of the population. In essence, an ever-changing ‘dynamic audience’ that can be targeted without depending on personal data.
These dynamic audiences don’t require cookies or devices as the basis of a transaction, or an email, phone number, name, or any other personal identifier. Not only is a consumer’s privacy respected, but this method of targeting also delivers better performance and scale than other alternatives. The net result? Brands can continue to reach those precise audiences they otherwise would have lost. Best of all, it’s future-proofed by design.
If the decade just gone was one dominated by marketers hoping to deliver one-to-one marketing solutions heavily relying on cookies and personal identifiers to retarget and drive performance, the next should be seen as an opportunity to reset the rules for a privacy first world. One that works better for everyone.
