What’s the danger of using stale or incomplete segmentation data?

Stale data reflects who subscribers were, not who they are. A "new customer" segment filled with people who purchased two years ago sends welcome-style content to long-time customers. An "engaged" segment based on opens from before Apple Mail Privacy Protection includes people who haven't genuinely engaged in ages. The segment label becomes fiction.

Incomplete data creates blind spots. If you segment by purchase history but 30% of subscribers have no purchase data (tracking gaps, offline purchases), you're making decisions about a third of your list based on absence of information. They might be your best customers—you just don't know.

Bad data leads to bad decisions compounded at scale. Sending "we miss you" to your most active customers is embarrassing. Sending aggressive promotions to customers who just purchased is annoying. Excluding high-value customers from VIP segments because data is missing costs revenue. Audit your segmentation data regularly: check recency, completeness, and accuracy. Segment quality depends entirely on data quality.