Data Hygiene & Tracking

What is data hygiene?

Data hygiene refers to maintaining clean, structured, and consistent data across systems. This includes naming conventions, event tracking, and data integrity.

Why data hygiene matters for small brands

Poor data quality leads to misleading metrics and ineffective automation. As tools and channels multiply, data hygiene becomes increasingly important.

When you should care (and when you shouldn’t)

Data hygiene matters when:

• Multiple tools are in use

• Decisions rely on reporting

• Automations depend on data signals

At very early stages, lightweight tracking may be enough.

How data hygiene is typically maintained

Brands establish conventions, audit data periodically, and limit unnecessary tracking. The goal is usefulness, not completeness.

Common mistakes or misconceptions

• Tracking everything without purpose

• Ignoring inconsistencies across tools

• Assuming tools enforce data quality

FAQs

What causes poor data hygiene?
Inconsistent naming, duplicated tools, and unplanned tracking additions are common causes.

Is data hygiene the same as analytics?
No. Data hygiene focuses on data quality, while analytics focuses on interpretation.

When should brands audit their data?
Audits are useful after major tool changes or when metrics stop aligning with reality.