Biased Attribution

Biased Attribution occurs when credit for a conversion is inaccurately assigned, affecting marketing insights and budget allocation.

Why it matters

Leads to misinformed marketing decisions.
Skews budget allocation and ROI analysis.

How to measure

Analyze conversion paths for inconsistencies.
Review attribution models regularly.

Details

In mobile marketing, biased attribution can significantly impact how resources are allocated across channels. It often arises from improper attribution models that favor certain touchpoints over others, such as last-click models that ignore earlier interactions. Mobile engineers and growth teams must ensure that their attribution models are comprehensive and account for all user interactions to avoid bias.

To mitigate biased attribution, teams should employ multi-touch attribution models that consider the entire user journey. Regular audits of attribution data can also help identify and correct biases, ensuring that marketing efforts are accurately measured and optimized.

Examples & formulas

Consider a scenario where a user interacts with multiple ads before converting. A last-click attribution model would credit the final ad, potentially undervaluing the earlier interactions. A multi-touch model would distribute credit across all touchpoints.

Multi-Touch Attribution = Sum(Credit for Each Touchpoint)

Common mistakes

Relying solely on last-click models; use multi-touch models instead.
Ignoring data discrepancies; conduct regular audits to ensure accuracy.