{"id":126850,"date":"2025-03-11T18:38:07","date_gmt":"2025-03-11T18:38:07","guid":{"rendered":"https:\/\/peraltafinancing.com\/advertising\/marketing-measurement-in-a-privacy-safe-landscape\/"},"modified":"2025-03-11T18:38:07","modified_gmt":"2025-03-11T18:38:07","slug":"marketing-measurement-in-a-privacy-safe-landscape","status":"publish","type":"post","link":"https:\/\/fivemor.com\/?p=126850","title":{"rendered":"Marketing measurement in a privacy-safe landscape"},"content":{"rendered":"


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Incrementality testing<\/u><\/a> – experimentation that measures the true incremental contribution of a media channel, campaign, ad set, or tactic to business results – is critical for savvy advertisers who recognize the myth of marketing measurement: the false belief that ‘advertising measurement is inherently defined by total, deterministic precision.’<\/p>\n

Eric Seufert, in his podcast<\/u><\/a>, suggests that platforms relying on identity resolution as a single source of truth for campaign measurement reveal more about the flawed mindset of the platform than the actual performance of ad campaigns. In a post-ATT world on the cusp of a cookieless future, deterministic tracking is likely not a broadly reliable input for proving ad performance at the level of placement, channel, or strategy.<\/p>\n

Fortunately, privacy-safe, open-source, \u201cinwards-focused\u201d statistical models such as causal impact<\/u><\/a> offer a reliable alternative. These models are built on the principle that well-powered experiments and statistical inference can establish a baseline for business impact, against which actual performance can be compared. This approach provides actionable insights without resorting to weak attempts to \u201cmap\u201d the customer journey across devices and browsers.<\/p>\n

The challenge for those controlling advertiser budgets is that experimentation, particularly randomized control trials<\/u><\/a> (RCTs), the gold standard, is both expensive and time-consuming. The costs include direct ad spend as well as the opportunity cost of \u201cturning off\u201d markets or audiences to create control groups. Additionally, setting up well-powered tests requires significant effort.<\/p>\n

Opportunities for Improvement<\/strong><\/h3>\n

Two key players in the ecosystem can address these challenges:<\/p>\n

For ad networks:<\/strong><\/h4>\n