In Part 1 of my CCPA musings, I covered a bit of Data Driven Linear TV (DDL) advertising history, its early reliance on third-party data, the past problems with third-party data quality, and the likely drying up of third-party data. These factors are driving a possible shift to increased reliance on first-party data for media measurement and attribution. For digital advertising, these issues are hugely problematic while, for DDL, limiting regulations may offer a blessing in disguise.
The challenge for digital is happening fundamentally because digital advertising is based on placement of a specific ad in a specific place for a specific viewer. To reach 16 million new truck intenders, for example, digital advertisers need 16 million digital identities — cookies, device IDs, Ad IDs — some way of delivering the ad to the target. With less than a month until CCPA goes into effect, industry organizations such as the IAB are now clamoring to have the California attorney general backtrack on plans to require browser “do-not-track” requests be honored by the industry.
When GDPR was implemented in Europe, the supply of digital identities dried up. Stricter regulations saw advertisers move away from public exchanges to private marketplaces with higher quality inventories according to eMarketer, and exchanges move to contextual targeting. CCPA and related state-by-state privacy regulations are forecast to be more stringent than GDPR and the intended effect — providing consumer control over their data — is inherently designed to eliminate large data structures formed around persons without their knowledge or control. CCPA will deflate the giant digital data bubble.
So how can all of this be good for TV ad buyers and sellers? Well, first and foremost, there’s broadcasting. We’ve just recently figured out how to target, buy, measure and perform attribution on TV using granular data. Whereas digital advertising needs reach and thus tends to extend audiences with modeling and stuffing to make them ‘big,’ DDL is focused on the opposite. We’d much rather have a small, but very robust and accurate audience data set for targeting and a highly accurate first-party data set for outcomes – purchases, site visits, downloads, for example. Unlike digital advertising, DDL is based on statistics — not 1:1 reach.
So, even though third party data sets may become smaller, if they are good quality, they can still be highly effective for audience-based targeting. As well, it is completely possible to run DDL programs on first-party data and to do so in a privacy-compliant way. This means that, while digital ad spend will struggle to re-map as cookie pools evaporate and stricter browser policies on tracking and web analytics emerge, we have ways to sustain and expand data-driven TV to deliver historical digital virtues — targeting, measurement and results-based attribution — to TV ad spend.
While this, too, requires some re-mapping of practices, it’s very doable. History shows that ad investment will flow to the sources of ad inventory that are most targetable and measurable. With digital losing its 1:1 edge and Linear TV offering the higher quality engagement of large screens and a model that can more easily adapt to strict privacy regulations, it is quite possible that, going forward, ad spend will shift from digital back to Linear TV.