Attribution
Biased attribution occurs when attribution platforms, also providing traffic and conversions, may favor attributing results to their services over competitors. This conflict of interest can skew accurate performance assessment. While platforms like Google and Facebook offer valuable analytics, using a third-party provider like Singular ensures unbiased ad performance insights, allowing for accurate ROI calculation and optimized ad spend.
Common Biased Attribution Examples:
- Using multiple ad networks. Misattribution occurs when self-attributing networks claim conversions that result from other networks impressions or clicks.
- Correlation-based bias. Incorrectly assuming one event causes another, leading to misattribution.
- In-market bias. Attributing a conversion to an ad when the consumer was already intending to purchase.
- Cheap inventory bias. Misattributing high conversion rates to ad effectiveness when it may be due to lower-priced products.
- Digital signal bias. Favoring online activity in attribution over offline sales, skewing data towards digital.
To counter these biases, marketers employ third-party attribution services for a comprehensive view of ad performance.
How Singular Addresses Biased Attribution:
Singular offers unbiased attribution by measuring across all channels, tracking ROI by integrating cost data, and considering the entire customer lifecycle through advanced tracking techniques. This approach provides marketers with an accurate view of campaign effectiveness, aiding in better decision-making and ROI improvement.