Identifying attribution bias involves a critical review of your data analysis methods and recognizing patterns that may indicate biased thinking. Here are some steps to spot it:
Cross-Channel Analysis: Assess whether your attribution model considers interactions across multiple channels, not just email. Longitudinal Studies: Evaluate performance over a longer period instead of focusing on short-term results. Segmented Data: Analyze results across different customer segments to see if certain groups are disproportionately affecting outcomes.