With 86% of consumers saying they feel a growing concern about data privacy, and 78% fearful about the amount of data being collected, per KMPG, this issue is only going to be amplified in the future. With regulations continuing to increase and more walled gardens launching audience solutions, huge swaths of audience visibility will be cloaked.
Moving forward, brands will need a three-dimensional approach to cope with the new realities of privacy:
Tech infrastructure that maximizes first-party data. More brands are considering using first-party data, and those with sufficient volume and value in that data need to examine whether their tech stack is built to support the use cases.
Pixels and third-party cookies have enabled brands to skip the internal customer data tools used to send real-time data to marketing platforms. But these data tools often lack the connectivity or speed to replace the critical targeting and measurement functions pixels and cookies provide.
Brands with valuable first-party data should ask themselves whether they have sufficient access to that data and the ability to easily port it into platforms where they target customers. Brands without access to large pools of valuable first-party data or the ability to use it appropriately and efficiently can create an efficient batch audience upload process that spares them the heavy upfront cost of a new data platform.
Navigating a cookie-free world and coping with walled garden audience solutions. Without cookies available to provide pervasive control over consumer groups, brands will need to consider different strategies to reach known users versus strategies used to reach unknown, anonymous users.
To reach a scalable group of broadly aligned, anonymized users, Google’s Topics API and LiveRamp’s Rampld is an alternative for providing highly deterministic targeting to a fixed set of known users via a brand’s Personally Identifiable Information (PII). But ultimately, neither fully replaces the control cookies have over consumer groups. It will require further testing to identify the tools within the landscape of “cookieless” targeting providers that best support the brand’s strategic needs into the future.
Create a new measurement paradigm. One of the most challenging aspects of measurement has been the reduction in underlying data platforms can access to attribute conversions to ad impressions and clicks, as privacy initiatives have continually lessened the size of data pools.
As a result, advertisers struggle to make month-over-month and year-over-year interpretations of performance. New measurement tools can help mitigate this issue by delivering a level of stability to the underlying data. But what does this mean for advertisers?
Measurement frameworks that provide increased privacy also bring decreased granularity. Therefore, advertisers will need to think about the events and data that are passed to these measurement frameworks in a much more strategic way.
Advertisers will also need to understand how to read performance within each universe their measurement protocols access. For example, the Chrome Privacy Sandbox framework might be best for measuring display ads directing to the website in Chrome browser.
Finally, brands should invest in tools like Marketing Mix Models -- which provide cross-channel views but deliver less real-time insights -- to augment tools that provide more frequent and granular insights but cannot measure performance across platforms or reduce stress on tools being used across platforms beyond their capabilities.
To successfully navigate this changing environment, brands must learn to manage the necessary complexity of systems and approaches critical to the privacy-first era.