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Understanding Translation Metrics

To help you track your translation activity and make informed decisions, Taia provides several key metrics across your projects, usage, and billing.

This guide explains what these metrics mean, where to find them, and how to use them to optimize your localization process.

📊 Project-Level Metrics​

Each project includes detailed insights such as:

Word Count​

  • Source word count per file and total
  • Helps estimate effort, cost, and delivery time

Status Indicators​

  • Not translated, AI translated, human translated, edited, delivered
  • Helpful for tracking where your project stands

Language Pairs​

  • Source and target language(s)
  • Useful for multi-market tracking

Delivery Date​

  • Estimated or actual date depending on workflow
  • Important for scheduling publishing, campaigns, etc.

📁 File-Level Metrics​

Inside each project, you’ll see metrics per file:

  • Word count
  • Status (AI-only, edited, MTPE, reviewed)
  • Assigned task (if part of a workflow)
  • Editor or linguist activity (for team-based work)

These help team managers assign work and track quality assurance steps.

📈 Organization Usage Metrics​

Under the Billing or Organization section, you’ll see:

Monthly Word Usage​

  • Words translated by AI
  • Words processed via human services
  • Useful for quota tracking and plan optimization

User Activity​

  • Number of jobs created per user
  • Helpful for cost attribution and internal reporting

Language Distribution​

  • Most commonly used language pairs
  • Identify your top target markets and prioritize resources

📑 Glossary & TM Usage​

Track:

  • How often glossary terms were used correctly
  • Reuse rate from translation memory (100% / fuzzy matches)
  • Helps improve ROI by reinforcing consistency and reducing rework

💸 Billing & Cost Metrics​

On paid plans, you’ll also see:

  • Words included vs. overage
  • Quotes accepted and delivered
  • Human service costs per project

Available in your Billing dashboard and exportable via CSV.

🧠 How to Use These Metrics​

  • Spot trends: which languages, content types, or teams drive the most work
  • Optimize workflows: automate or standardize where volume is high
  • Improve consistency: monitor glossary usage and TM reuse
  • Make budget decisions: track ROI on AI vs human output

Need help making sense of your metrics?
Contact our team →

Last updated on by Taia Admin