Where Post Editing Work Is Heading and How to Price It

Light and full post editing: what each one promises the end reader

Light post editing and full post editing are distinct services, each with its own standards. Light post editing means making sure the machine translation is understandable, but not polished. The goal is a text that conveys the right meaning, but may still sound awkward or unpolished to a native speaker.

Full post editing goes further. Here, the translator corrects grammar, syntax, and style, and ensures that the translation reads naturally, as if written originally in the target language. This process takes more time and skill, and the end result should be ready for publication without further revision.

Clients sometimes ask for a discount when machine translation is involved, claiming the work is easier. The real difference lies in the outcome: light post editing is for internal use or gisting, while full post editing is for external communication and carries the translator's reputation.

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Why raw output quality varies by language pair, domain and source writing

Machine translation quality is not consistent across all projects. Results depend heavily on the language pair involved. Common pairs with large training datasets, such as English to Spanish, tend to produce more reliable output. Less common combinations, or pairs with different grammatical structures, often yield less predictable results.

The domain also matters. Technical manuals with repetitive, clear language are easier for machine engines to handle. Creative marketing copy, legal contracts, or regulatory content often confuse even advanced engines, as these texts rely on context, idioms, or jurisdiction-specific terms.

Source writing quality plays a major role as well. Well-structured, clear input leads to better machine output. Ambiguous, poorly written, or overly complex source texts generate more errors and require more post editing effort. Translators must review the source before quoting, to assess the potential volume of corrections.

Per word discounts against per hour billing, and when each is honest

Most translation jobs are quoted per word, but post editing introduces new variables. Some clients expect a flat per word discount off the translator's standard rate, assuming less effort is needed. This approach can be fair when machine output is strong and the material is straightforward.

In other cases, per hour billing is more accurate. Difficult subject matter, low quality machine output, or content that needs heavy rewriting may take as long as or longer than translating from scratch. Per hour billing captures the true effort, especially when the machine translation needs extensive changes or review cycles.

The honest method is to match billing with the real work required. If light post editing on simple technical material takes half the time of a full translation, a per word discount makes sense. If post editing is more labor intensive, an hourly rate protects the translator from underquoting. Clear communication with the client about expected effort is essential.

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Edit distance and how to measure what you actually changed

Edit distance refers to the number of changes a translator makes to turn the machine output into the final version. This can include insertions, deletions, and substitutions at the word or character level. Measuring edit distance helps both translators and clients understand the true amount of work involved.

Some shops use software tools that compare the raw machine translation with the delivered text, highlighting every change. Others track edits manually on smaller jobs. Higher edit distance usually means the machine output was poor, or the content was complex.

Knowing the edit distance helps justify a higher rate or an hourly fee. It also gives clients a transparent view of why a simple per word discount may not be fair in every case. Translators should consider documenting their edits for jobs that may be audited or negotiated after delivery.

The jobs machine output still fails: marketing, legal nuance, regulated labeling

Machine translation has made strides in routine business and technical documents. Yet, there are domains where it continues to fall short. Marketing materials require nuance, tone, and cultural adaptation that machines cannot reliably provide. Legal documents often hinge on precise language and local standards, which automated systems may miss or misinterpret.

Regulated labeling, such as product packaging for healthcare, chemicals, or food, demands high accuracy. Mistakes here can lead to regulatory violations or recalls. Many clients now realize that even with the best engines, these projects need human oversight and sometimes a full rewrite.

In these areas, post editing can resemble full translation or even copywriting. Rates need to reflect this reality. Translators should not accept machine-based discounts where the work requires their full professional expertise.

See how WordRate handles this for translation and localization

Confidentiality clauses and client rules on sending text to third party engines

Many clients include confidentiality clauses in their contracts, especially in legal, medical, or financial sectors. These agreements may strictly prohibit uploading content to public machine translation engines, as this could expose sensitive information.

Some companies only allow the use of approved, on-premise engines that keep data private. Others require written permission before any automated tools are used. Violating these clauses can put both client and translator at risk for breach of contract.

Translators must check the client's policies before using machine translation, and clarify what tools are acceptable. When in doubt, it is safer to avoid third party engines or to use only client-supplied resources. Secure workflows can become a selling point for agencies and freelancers handling confidential material.

What the shift means for translation memory ownership and long term rates

As more work moves to post editing, questions around translation memory (TM) ownership become more complex. When translators correct machine output, those corrections often feed back into the client's TM or future engine training. Some clients may expect lower rates in exchange for building their own assets.

Translators should clarify contract terms about TM updates and reuse. If corrections and edits are shared, this can reduce future work by making engines smarter or TMs more complete. This dynamic may put downward pressure on rates over time, especially for high volume clients with well-managed memories.

However, unique or specialized subject matter, evolving terminology, and ongoing regulatory changes ensure there will always be a need for skilled human input. Translators can protect their value by specializing in areas where post editing is complex or where TM alone cannot guarantee quality.

Positioning your practice: post editing, review, or work you decline

Translators and language service providers face choices about which post editing projects to accept, which to quote as review, and which to decline. Not every job is a fit for every provider. Some professionals choose to focus on full post editing, where quality expectations and compensation are clear. Others may offer light post editing only for specific content types or known clients.

There is also the option to position review services as distinct from post editing. Reviewing a machine or human translation requires a different mindset and skill set. Some jobs, especially those with poor source text or high risk, are best declined or quoted as new translation rather than post editing.

A clear rate card for each type of work can help avoid misunderstandings. Tracking project details, rate agreements, and glossary terms makes quoting more accurate and project delivery more reliable. Tools that combine rate management, glossary support, and delivery tracking can streamline these tasks and support clear communication with clients.