We need to stop debating GDPR and start embracing predictive marketing
For The Drum’s data deep dive, Builtvisible’s Gary Stubbenhagen argues that it’s time to finally accept the post-GDPR world, and invites performance marketers to embrace predictive marketing enabled by GA4.
Builtvisible’s Gary Stubbenhagen attests that there is method in the madness when it comes to comes to predictive marketing / Michael Dziedzic
It’s been nearly five years since the General Data Protection Regulation (GDPR) came into effect, so you’d be forgiven for expecting that we’d have moved on from discussing privacy and tracking prevention by now.
However, many marketers and analysts have spent that time trying to find workarounds and testing the boundaries of what ‘strictly necessary’ means – despite it being one of the clearest phrases in a piece of legislation.
The result? There are still a lot of non-compliant sites out there, and many marketing teams aren’t prepared for the impact on their data and advertising that compliance will bring.
But let’s be frank: the old days of precision marketing are over, and they aren’t coming back. We did this to ourselves. GDPR wasn’t inevitable, but rather a reaction to some pretty shoddy work by our peers.
Remember the panic over the rise of ad blockers? This was a consumer reaction to the impact of analytics and advertising trackers on website performance and mobile data plans. It naturally led many to question what they were doing, raised privacy concerns, and attracted the attention of regulators.
The statistics are a matter of debate, but it’s generally accepted that tracking represents more than 40% of internet traffic. A 2019 piece (in response to Elizabeth Warren’s explosive claim that 70% of traffic goes through Facebook or Google) does a good job of breaking this down.
Consumer trust: the basics
GDPR is there to address the genuine concerns of your customers. This might sound obvious but we are regularly talking to prospective clients who still fail compliance checks.
Beyond that, when we do deploy tracking, we must make sure it’s well-optimized. Duplicated or redundant tags and scripts are still a regular feature, and they’re hurting your site performance. This is a frustration for your customers, and it’ll hit your SEO, too.
If you can, consider a server-side tag management solution. This will help minimize scripts that are sending the same data to different locations. It may come with some increased cost and complexity, but you’re going to see returns on that investment.
But we have to address the elephant in the room. There’s a lot that can be done to optimize opt-in rates, but compliance is going to lead to substantial data loss.
Welcome to the era of predictive marketing
To maintain the level of targeting precision we all know and love, we’re going to need to get comfortable working with data samples and using machine learning to get the most out of it.
I know those words can feel a little daunting, but you don’t need a big data science team to succeed in the new digital marketing paradigm; a clear plan and solid data foundations will serve you well.
While it may have received a lukewarm reaction from the digital marketing community, Google Analytics 4 (GA4) is doing us all some favors here. Many businesses are still carrying a lot of legacy issues in their measurement strategies, and the need to re-implement tracking is an opportunity to finally address them.
You may have noticed Google’s notices that they will automatically create a GA4 property for you, linked to your Universal Analytics tags. My advice: don’t rely on it – migrate properly. Once you have your GA4 property up and running, you’ll get access to new AI features almost immediately.
For example, ‘anomaly detection’ automatically highlights where movements in time-series data are beyond the norm, allowing you to focus your analysis where it really counts. And the ‘predictive audiences’ function allows you to identify users who may be ready to buy or churn soon, analyze their behavior, and target them in Google Ads. AI features are clearly a big focus for this iteration of Google Analytics, so expect more in this vein once the big migration is done.
And if you can’t wait for that, fear not; Google has opened up BigQuery exports to all properties. So, you can use your GA4 data in your own machine-learning pipelines and algorithms, or plug it into a third-party solution without worrying about sampling or API limits.
Well-optimized data collection coupled with predictive marketing will allow us to achieve good returns for our businesses and better experiences for our customers. It’s not simple, but it’s not as complex as many fear. So, here’s hoping 2023 is the year we finally move on from debating GDPR and embrace the future.
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