Case Study: beehiiv achieves more accurate channel attribution and budget reallocation with BlueAlpha

Beehiiv cuts Meta signup CPA error by 345% with BlueAlpha

beehiiv, a newsletter platform for creators and media companies, faced a challenge in accurately measuring the performance of its paid advertising channels. Due to a mobile-to-desktop attribution gap, platform-reported metrics were unreliable, making it impossible to determine which channels were genuinely driving incremental newsletter signups and paid plan purchases. This led to uncertainty about budget allocation and concerns over the quality of paid-acquired users. beehiiv engaged BlueAlpha to uncover the true value of its marketing spend.

BlueAlpha implemented a two-phase approach, using a Bayesian Marketing Mix Model to identify test candidates followed by geo-based incrementality tests. The tests revealed massive discrepancies; Meta's true cost per signup was 345% higher than reported, while TikTok was validated as its most efficient channel. Crucially, the tests proved the channels were driving far more paid conversions than platforms could attribute. Armed with these insights from BlueAlpha, beehiiv confidently reallocated its budget to scale the proven channels of TikTok and YouTube, optimizing its spend for scalable growth.

Beehiiv