The demise of third-party cookies has now been delayed for two years. But that doesn't mean marketers should be unprepared for similar tectonic changes.
When Google announced it was delaying the removal of third-party cookies from Chrome to 2023, you could nearly hear the sigh of relief from marketing professionals worldwide. After all, they're still struggling to tackle the aftermaths of the pandemic and iOS14 privacy changes.
However, that doesn't mean that the "cookie-geddon" is not coming.
"To be prepared is half the victory," as the saying goes, so evaluating the available options and doing proper planning can address many of the headaches marketers will get when the moment finally comes in late 2023.
For now, let's look at what's already changed and how can you tackle upcoming events.
What data privacy changes have occurred so far?
The release of Apple's iOS14 has given us a sneak-peek at what awaits marketers when tracking cookies get banned from prominent platforms (primarily Chrome and Android).
In the most recent version of Apple's operating system, mobile device users are allowed to improve their privacy settings by stopping the harvesting of their personal data. The result is that users can keep their data more private, though at the cost of receiving less relevant advertising across the Internet.
As in other cases of free online services, it's a trade-off between privacy and utility, and everyone has the ability to set the balance at the level they find acceptable.
Although the iOS14 privacy changes were perceived as another disaster for marketers, they don't bring about a total loss of attribution and conversion tracking. You still know whether people came to your website or online store by clicking on a Google Ad, from a share on Facebook, or through media coverage about your brand. You "just" don't know who those people are or what their preferences and habits may be, thus preventing ad networks from serving them relevant, contextual advertising (including yours).
Most marketers don't even remember a time before high-precision, targeted digital ads—when "carpet bombing" was an actual advertising strategy. It's easy to get used to more efficient methods, so it's no wonder so many are viewing the loss of performance-focused advertising as a disaster for their business (and their job).
On the other hand, half of display ads are never shown to actual people, studies have shown—so the loss might not be as huge as you think.
How can you prepare for upcoming changes to data privacy?
As requests grow for an overhaul of online user privacy standards, it's reasonable to expect that "cookie-geddon" will be the first of many challenges that will change the face of marketing and advertising as we know it today. Ironically, to seek solutions to those challenges, we need to look into the past, not the future.
First of all, let's look at the consequences of a lack of precision targeting and retargeting. Yes, digital ads will become more expensive and less efficient, but that was exactly the case not so long ago. It means that you'll have to revise your advertising strategies based on best-practices and ideas from the recent past. Maybe don't go as far into the past as Mad Men (although you can learn a thing or two from advertising campaigns from that era), but definitely look into the strategies that worked in the 2000s for companies of a similar size and industry.
It's a step back from today's efficiency and ROI measuring capabilities, but it doesn't have a to be a disaster. If you focus on things you can actually influence—for example, conversion optimization—you'll partly mitigate the negative effects of losses on the acquisition side.
Now let's take a look at attribution—one of the challenges highlighted by all marketers, whether they manage campaigns on Instagram for a small family bakery or budgets in a multinational corporation.
In a complex, intertwined world, where online and offline experiences are almost blended, finding the right attribution model—one that realistically identifies the best channels driving sales and growth—is a major challenge. The plethora of ad tech tools—powered by third-party cookies—that became available during the past decade helped make attribution a bit more refined, though it still remained complex. But now that tracking cookies are scheduled to go away in less than two annual planning and budget cycles, many marketers are asking what they can do to replace them.
The answer lies in a popularly loathed skill: mathematics. Old-school statistics, to be exact. Many of you use Excel daily, but only real data geeks enjoy it. For the rest of us, it's just a necessary tool needed to get the job done. And now we're saying you need another one? Come on!
Jokes aside, statistical modeling has been used in marketing for a long time, and it was proven efficient during the many decades before the reign of digital ad tech tools. It allows marketers to determine the best performing channels that drive sales without the need for third-party cookies.
By analyzing available, first-party data on traffic sources and conversions, tools such as Adverity's ROI Advisor use complex statistical calculations to create a picture of channels that bring the most bang for the buck and allow you to steer your budgets into channels that will actually deliver on campaign targets.
By using algorithmic, data-driven attribution modeling in analytics platforms such as Adverity, you can minimize the negative effects of the disappearance of third-party cookies as well as predict trends and eliminate anomalies in your campaign performance.
It sounds like magic, but it really isn't. It's math and science; and, as we all know, you can trust science to deliver results. Good, reliable, quantifiable results that you can show to your stakeholders and be proud of.
And what more could a marketer want in the year 2021?
