Data decay

Data decay is the natural process by which a once-accurate database drifts out of date. Every record captures a snapshot of reality at the moment it was created, and reality keeps moving. People change jobs, get promoted, or leave; companies relocate, rebrand, merge, or shut down; phone numbers and email addresses are retired. None of that updates itself in your CRM, so accuracy erodes month after month. In B2B the rate is steep because professional contact data is tied to employment, and job changes are common. Industry estimates often put the annual decay of a B2B contact database in the range of 20 to 30 percent, which means a list left untouched for a couple of years can be mostly wrong. The consequences are practical: bounced emails that hurt sender reputation, calls to disconnected numbers, reps preparing for the wrong job title, and segmentation built on figures that no longer hold. Teams fight decay in two ways. They reduce how fast it accumulates by validating data at the point of entry, and they reverse it by re-enriching records on a schedule, often through an enrichment waterfall that checks several sources. The goal is not a permanently perfect database, which is impossible, but a maintenance habit that keeps error rates low enough to act on with confidence.