First-Party Data: A Hidden Gem for the Post-Cookie World
Amid growing concerns for consumer privacy, increased transparency and reducing complexity, the era of “cookies” (those data trackers that contain information about user habits, demographics and purchase behaviors) is ending, but not just yet.
Browsers like Safari and Firefox have already excluded third-party cookies. Google’s Chrome, by far the largest browser by number of users, is set to relinquish their use within the next two years. That’s a bit down the road, but now is the time to get ready for the next phase of organizing our digital audiences.
Every advertiser will go through this transition. The ones that have a head start will have an advantage.
So, let’s look into this cookie-less world, starting with the one asset every advertiser has — your own customer data, aka “first-party” data. Most marketers use these data for direct outreach such as customer email blasts, direct mail and opt-in promotions. Yet these same data could potentially be used to gain new customers who may behave like your best existing customers.
Regardless of whether marketers have conducted a formal customer segmentation study or not, most already possess a sense of their ideal customer profile, including the following:
Where do they live? Which region or city? Which zip codes?
How did they first get to your site? Paid search? A display ad? Through social media?
What percentage of business is driven by these customers? Is it close to Pareto’s 80/20 rule? Or is it some other percentage?
To mirror the best attributes of these customers, digital advertisers use lookalike modelling. However, lookalike modelling — as it currently stands — uses third-party data, which, as the name suggests, employ syndicated third-party cookies. To rely solely on the current practice until Google phases out third-party cookies is missing an opportunity to get ahead of the curve. Now is the time to transform your first-party data into a powerful advertising tool for post-cookie lookalike modelling, using a process of “Scrub. Test. Repeat.”
Also known as practicing “data hygiene.” The first step is to “scrub” first-party data; that is, data that have been coded in such a way that no personal information indicators are divulged. Companies like Neustar or LiveRamp specialize in data hygiene to provide first-party data sets ready for advertising purposes. Programmatic digital vendors routinely work with these companies, which ensures a turnkey onboarding process.
Compare your first-party audience with current third-party audience data sets to determine the performance. 10% – 15% allocation of a major campaign initiative over 6 – 8 weeks should be adequate to determine learnings and provide recommendations.
After making any adjustments to the test, repeat the process for the next campaign. While third-party cookies have a proven history behind them, the goal of this three-step process is to make your first-party data work as hard as the legacy cookie-based approach.
The advantage in building lookalike audiences from first-party data is that it not only helps in growing your existing customer database, it also helps your future marketing and advertising efforts become much more effective. By the time Google cuts support for third-party cookies, you won’t need them, while those who waited will wonder why they didn’t make the transition sooner.
First-party data can be a valuable asset that YOU own. Still it is just one aspect of a digital world without third-party cookies. Next time, we will look at how to use data from digital publishers: “Leveraging Second-Party Data for Digital Campaigns.”