What’s the risk of demographic bias in targeting?

You notice that your highest-value customers are homeowners in suburban zip codes, so you focus your sends there. Problem? You've just created a proxy for race and income.

Demographic bias happens when your targeting criteria,whether intentional or not,disadvantage people based on protected characteristics like age, gender, race, or income. The sneaky part is proxy variables. Homeownership, postal code, purchase history, and credit score all correlate with protected classes. Fair lending, housing, and employment laws don't care if you didn't mean to discriminate. They care about the outcome.

Fair lending, housing, and employment laws can impose real penalties. That's the legal side. There's also the subscriber side: people notice when they're excluded for reasons that feel unfair. You lose trust.

How to audit your segments for bias? Start simple. List every segmentation criterion you use. For each one, ask: am I segmenting on behavior (opened emails, bought something) or demographics (zip code, age, credit score)? If it's demographics, dig deeper. Does this criterion correlate with a protected class? Can you achieve the same business goal with behavioral data instead?

Behavioral targeting is your safer play. It works better anyway because it's based on what people actually do, not assumptions. Your next step: pull a sample of your recent sends, document your segment definitions, and run that proxy check on each one.