7 Ways DeepL Outperforms Other Machine Translators

Using DeepL for Business: Tips to Improve Multilingual Workflows

1) Choose the right plan and secure setup

• Pick DeepL Pro (Team or Business) for glossaries, translation memory, SSO, and document editing limits.
• Enable SSO and enforce enterprise admin controls.
• Use on-premises or private-cloud options (or the API with appropriate agreement) if you require stricter data residency.

2) Standardize terminology and brand voice

• Create and maintain centralized glossaries with preferred translations, product names, legal phrasing, and tone rules.
• Apply glossaries automatically via the API or DeepL’s team settings to ensure consistent output.

3) Integrate into the tools teams already use

• Connect DeepL to Microsoft 365, Google Workspace, Zendesk, Slack, CRM systems, CMS, and your localization platform so translators and agents don’t switch apps.
• Use browser extensions and desktop apps for quick in-context translation and editing.

4) Automate repetitive steps with the API and workflows

• Use the DeepL API to auto-translate incoming tickets, customer emails, and user-generated content, then route for human review when needed.
• Build pipelines that: detect language → apply glossary & translation memory → send for role-based review → publish.
• Combine with task automation (Zapier/Make or internal queues) to reduce manual handoffs.

5) Balance machine translation and human post-editing

• For high-volume, low-risk content (UI strings, knowledge-base drafts), rely on MT + spot QA.
• For marketing, legal, and high-stakes communications, require human post-editing with clear review SLAs.
• Use translation memory to reduce reviewer effort and keep consistent edits.

6) Use style guides and quality checks

• Publish short style guides per language (formality, punctuation, units, date formats).
• Implement automated checks for terminology use, named-entity fidelity, and mandatory disclaimers; flag exceptions for human review.

7) Leverage translation memory and versioning

• Store approved translations in a translation memory ™ so future content reuses vetted phrasing.
• Version glossaries and TM entries to track changes in product names or legal terms.

8) Monitor metrics and feedback loops

• Track throughput and quality: turnaround time, post-edit rate, revision ratio, customer satisfaction by language.
• Routinely review low-quality segments and update glossaries/TM or retrain internal style rules.

9) Enable accessible meeting and voice workflows

• Use DeepL Voice / meeting integrations (Teams, Zoom) or meeting transcript translation for multilingual calls; attach translated transcripts to tickets or project notes.

10) Data governance and privacy best practices

• Limit what is sent for automatic translation (mask PII where possible).
• Route sensitive documents through controlled review or use dedicated secure deployment options.

Quick implementation checklist

1. Select DeepL plan and enable SSO/admins.
2. Build primary glossaries and a lightweight style guide.
3. Integrate with 1–2 core apps (e.g., CRM, Zendesk).
4. Set up API pipeline: language detect → glossary → TM → QA.
5. Define human-review rules for content types.
6. Monitor metrics monthly and iterate.