Incrementality tests serve as educated starting points, or priors, in marketing mix models (MMMs) to improve accuracy in measuring the impact of marketing channels. By utilizing a robust database of over 2,000 tests, marketers can input informed priors that enhance model reliability, particularly benefiting new brands with limited sales history. This approach helps distinguish correlation from causation, ultimately refining the understanding of marketing effectiveness.

The Haus analysis reveals that while Meta's advertising platform generally shows incrementality in driving sales, the shift towards automated campaigns like Advantage+ may not improve incremental efficiency for all brands. Data from 640 incrementality tests indicates that although Advantage+ performs well in new customer acquisition, many brands still see better returns from traditional Manual campaigns in terms of overall efficiency. The findings underline the importance of understanding individual business performance relative to Meta's automated tools.