Learn
What is Data Drift?
Understanding how marketing data quality silently degrades over time and how to detect it.
Page Metadata
- Meta Title
- What is Data Drift? | Marketing Data Guide
- Meta Description
- Learn about data drift in marketing - why data quality degrades over time and how to detect and prevent it.
- Primary Keywords
- data driftdata quality degradation
- Secondary Keywords
- schema driftdata monitoringquality degradation
Definition of Data Drift
Data drift occurs when the statistical properties, structure, or semantics of your data change over time. In marketing, this manifests as gradual quality degradation that can go unnoticed until it causes significant problems.
Types of Data Drift
Schema drift
Distribution drift
Semantic drift
Volume drift
Different types of drift affect marketing data in different ways, from structural changes to subtle shifts in meaning.
Common Causes in Marketing
Platform API changes
Team turnover
Vendor updates
Process changes
Marketing data is particularly prone to drift due to frequent platform changes and distributed ownership.
Impact on Marketing Decisions
Attribution errors
Misallocated spend
False confidence
Undetected drift leads to decisions based on inaccurate data, potentially wasting significant marketing budget.
Detection and Prevention
Implementing monitoring and validation to catch drift early before it impacts decisions.