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Overview

Naming discipline is one of the simplest ways to improve model quality and reporting clarity. When labels are inconsistent, teams lose time reconciling rows, fixing mappings, and explaining what should have been obvious.

What good taxonomy should do

A good taxonomy should help you:
  • distinguish channels clearly
  • separate meaningful campaign structures
  • preserve interpretation across time
  • support cleaner mapping and designation workflows

Best practices

  • Keep channel names stable
  • Use campaign names that reflect real strategic differences
  • Avoid unnecessary renaming midstream
  • Preserve a consistent hierarchy when possible
  • Separate brand-search and affiliate logic when those distinctions matter

Why this matters in Provalytics

Taxonomy affects:
  • data layer mapping
  • designation workflows
  • campaign reporting clarity
  • composite-layer stitching confidence
  • interpretability of results over time
If the same thing is named three different ways, the model may still run, but the human reading experience gets much worse.