It’s Nothing Personal: The Other Kind of First-Party Data

By John Donahue, Founding Partner, Up&totheRight

The issue of end user data privacy centers on the acquisition and activation of identities at the individual and household level. But, while user data is important to everyone, it is less important to some advertisers than others.

For many advertisers, particularly those that are focused on reach and lack direct customer relationships, user identity at this level of granularity is not always the most important data set. Rather, other data collected and owned by the advertiser, such as sales volume and breakdown by region and by time, is much more important.

This proprietary data could be thought of as the other kind of first party data, even though it’s not connected to individual users. Our view is that ‘first party’ can refer to BOTH personally identifiable data AND corporately identifiable data.

As an easy example, knowing how much you sold of something, where and when you sold it, and how much you sold it for, is a very high value data asset for many advertisers.

Given all of this data can be time, location and/or context specific, it can be used as a parameter in bids and applied in auctions through integrations with media supply.

In doing so the advertiser also gets to choose between price and precision. The less constrained the targeting, the lower the price per impression. As always, the thing that doesn’t change in this dynamic is that supply and demand economics govern all.  Further, advertisers can arbitrage the lift in effectiveness that targeting brings, knowing, for example, that 3x more effectiveness warrants up to a 2.9x increase in price–adding more flexibility and upside into the process.

Generally, the thoughtful and measurable trade-off between price and precision when using business data leads to better media efficiency than when relying simply on leveraging cookie based targeting. This is because advertisers can examine the cost productivity advantages of all of their data tactics and optimize their media spend to the most scalable and profitable investments.

This requires the advertiser to begin to think about how they can integrate their data into the tech stack in a way that enables their activation teams to take advantage of it.

While cookie based audiences are easy—simply select the audience you want to target in your DSP of choice—business data integration requires APIs and manipulating the bidder through different integration points.

However, the market participant that can identify leading indicators of changing demand and respond promptly acquires a real competitive edge. For example, advertisers can study the stores in which they have the greatest sales velocity and prioritize investment based on where they think the category is out performing their brand.

Perhaps, this kind of internal data harvesting and activation should be the central focus of digital marketers. Few would argue against the idea that the nature of digital marketing lends itself to high velocity responsive marketing. If you can rely on technology to deliver accurately, and at speed, in respect of the where and when of impression delivery, the need for addressability and cookies goes away, as the audience becomes defined by the signals of where sales have the greatest growth potential.

This approach may not work perfectly. But for everything you might lose in precision you might gain in trust from avoiding mind-numbing retargeting and cookie bombing.

Of course there’s nothing easy or cheap about achieving great data alignment in organizations. But focusing on the data points that tell you the most–like where and when a brand is showing the greatest sales growth–can actually cost the least in terms of driving precision in advertising. And that makes the pursuit of better data a worthy endeavor.