Measuring Campaign Value Despite Data Privacy Regulations

User data privacy as an abstract personal private information security technology as a social media and public profile sharing of lifestyle activities in a 3D illustration style.

Understanding Incrementality

For marketing, PR, and communications professionals, being able to tangibly demonstrate the value that your efforts bring to a business is crucial. However, more restrictive data privacy regulations make it difficult to clearly and objectively determine exactly how much traffic your communications efforts drive to the company.

Brands typically use multi-touch attribution to determine the impact of communications efforts on business outcomes. Multi-touch attribution works by collecting data about all of the various touchpoints that a potential customer encounters on their journey and assigning a value to each touchpoint, helping brands see what pieces of content are driving the most conversions. However, recent restrictions on user-level tracking—which refers to a site’s ability to monitor user behavior by tracking links clicked and items searched for–have left much of this data outdated and unreliable.

To counteract this, many brands have begun turning to incrementality testing. Incrementality works via a test-and-control method: group X is shown a particular media campaign, and this same treatment is withheld from group Y. Measuring the differences in desired outcome (e.g., web visits, conversions, revenue) between the two groups allows communications professionals to get a clearer view of the direct causal impacts of a particular PR campaign. Moreover, because it works at the level of cohorts rather than tracking individual behaviors, incrementality testing is not impacted by data privacy restrictions. These tests can be conducted in-house or via a third party.

Examining Meta Advantage+

As the use cases for AI in marketing and communications continue to expand rapidly, major social media companies are racing to develop the most effective tools for professionals on their platforms. Google’s PMax has generated considerable excitement since its release in 2021, and Meta recently released its own AI-powered platform, Meta Advantage+. Advantage+ promises to use AI to help brands automate their paid ads and social media campaigns to optimize their marketing and communications budget.

Meta Advantage+ consists of three main tools: Advantage+ Shopping Campaigns, Advantage+ Creative, and Advantage+ App Campaigns. The platform automates content creation and targeting, producing extensive and varied campaigns using relatively little input from those using the platforms. Once these campaigns have been created, Advantage+ will use its available data to tailor campaigns to individual users’ needs, interests, and purchasing patterns.

Like other AI-based platforms, Advantage+ implicitly asks users to trade direct control over their content and targeting for the promise of better efficiency. AI typically achieves this by maximizing conversion rates. However, higher conversion rates alone do not tell the entire story–these tools may automatically target users who already have high purchase or interest intent, meaning that the ad dollars spent on converting them would have been better allocated elsewhere. This is where the importance of incrementality comes in.

An Evaluation

As with Google’s Pmax, Advantage+ leaves marketing and communications teams with little visibility into campaign performance. With no way of seeing exactly who was targeted or what content was shown, the platform tends to over- or under-report its contribution to actual business outcomes. For example, retargeting campaigns served to people who have previously sought out the brand are often given more credit than a more campaign that first introduced a prospective customer to a brand. The effect of the communications treatment was therefore not incremental, as it did not drive new engagement with the brand and increase its reach, but merely capitalized on already-existing reach.

Without the ability to reliably make the distinction between incremental and non-incremental conversions, communications professionals are unable to create the kind of solid, objective data they need in order to properly optimize their budgets. It also makes it difficult to pinpoint the exact value that the Advantage+ platform, or any other similar platform, is delivering to the business.

Using AI With Caution

While Meta Advantage+ and other AI-based platforms hold lots of potential value for marketing and communications teams, they need to be used with caution and strategy. Incrementality testing is an essential part of this strategy, as it allows brands to keep accurate and up-to-date measurements of the value created by these tools. By doing so, they are able to reap the benefits of AI’s efficiency and convenience without sacrificing precise targeting and content curation.

Key Takeaways

  • The potential value of Meta Advantage+ varies between brands and levels of communications and spend.
  • Advantage+ tends to both under- and over-report its contribution to actual business outcomes.
  • Improved conversion rate does not equate to higher incrementality.
  • Incrementality testing is an effective answer to the specific set of problems presented by Advantage+ and other measurement platforms, making it a necessary step in deriving maximum value from the platform.

Trevor Testwuide is the CEO and co-founder of Measured.