The smart way to localize with translation memory software

Translation memory software (or TM software) helps translators save time by storing previously translated words, phrases, or sentences they can reuse. If it can save you from repeating the job, it will.

It’s essentially an intelligent filing system for translations. The memory’s translated text snippets are known as segments or translation units.

While machine translation (MT) engines autonomously create brand new versions every time, TM systems reuse text that real people have already reviewed and approved.

For example:

• Using MT, your team translates ‘Contact us for a free consultation’ into German (the target language) for your website
• The translator memory stores both versions (the source language and ‘Kontaktieren Sie uns für eine kostenlose Beratung’)
• Later, the exact phrase shows up in a brochure project, in English
• The system instantly suggests the same German translation, so the translator can apply it with confidence and quickly move on

Most TM software pairs saved words, sentences, phrases, or just strings of text with notes about where they came from and how good they are (metadata).

Next, they evaluate how closely new text matches stored segments. Here are the main match types you’ll encounter:

As your translation memory database grows with this precise knowledge, it helps users work faster. Costs go down as quality and consistency shoot up, resulting in much happier stakeholders.

Meanwhile, TM alignment helps you build databases from previous translation projects. The system scans existing translated documents and figures out which sentences match up between versions.

In the XTM Cloud platform, TM alignment is called Memory Builder, and the super-easy setup looks like this:

You only need to fill in the required information and attach your files. Then, click “Align” and watch XTM Cloud save you months.

Translation memory tools work alongside the other systems professional translators use every day.

Computer-assisted translation (CAT) tools give them a place to work, while translation management systems (TMS) track and organize bigger projects with multiple people.

In our suite, XTM Workbench is the CAT tool. It’s built into the XTM Cloud TMS and looks like this:

Translation memory software feeds approved translations into this workflow, ensuring everyone uses the same terms.

Adding a machine translation engine (MT) creates an even smarter, faster-moving setup.

The system looks for exact matches from previously translated content. MT becomes the starting point if nothing is relevant in the memory. Linguists then review and polish the MT’s output to guarantee high-quality translations every time.

The more machine translations those linguists approve, the stronger the memory gets. The database grows in value, streamlining each new content localization project to make it cheaper and better than the last.

For example, a life sciences company might use TM to manage clinical trial documentation. 

Segments like ‘adverse event reporting’ or ‘patient consent form’ appear across materials. When a translator localizes a new study, the system pulls approved versions of these common phrases. This saves time while ensuring consistent terminology across all documents. Win-win.

TM software directly impacts your business’s performance in global markets. It’s more than just a time-saver.

Here’s what we mean:

Let’s say you run a cloud-based software company’s localization process. 

Your first user guide translation costs $10,000. Six months later, you update it and need to re-translate. You find that 60% matches existing translations, so you only pay to translate the new 40%.

As a result, that update costs closer to $4,000, with a 60% lower chance of human error or inconsistent messaging. All because of translation memory software.

The glossary is even bigger the next time you update the user guide, having picked up more new translations. Higher match rates reduce the work and investment needed even further.

So, translation memory software isn’t just a function. It’s your edge over all the companies that still rely on manual processes and scattered files. While those laggards drown in duplicate work and avoidable errors, you’re launching faster and scaling at speed.

Running complex localization projects with various teams and guidelines? You’ll need an enterprise-ready TM system to keep pace. One that fits your way of working now and scales easily as needs change.

Standalone TM tools exist, but they’re pretty niche. Most are built for freelancers working on small projects, so they prioritize low pricing and simplicity over automation and integration. It’s not exactly practical for teams juggling lots of deadlines and markets.

“Lesser tools will probably not be able to meet your demands, whether they are your current ones or those you will use in the future, since growth is always something that’s around the corner.” — John Weisgerber, Senior Solutions Engineer, XTM

Most enterprise-ready TM software sits inside broader TMS or CAT products that connect people and content in one smooth flow. You get all the key functions — translation, memory, quality assurance, project management, and more — without switching contexts.

XTM Cloud nails this all-in-one approach, although some teams use memoQ, SDL Trados (Trados Studio), or an alternative.

So with all that in mind, here’s what to prioritize in your TM tool and the software that houses it:

If you’re serious about scaling localization, treat the features in both columns as essential. Teams with access to these can work faster and maintain quality at any scale, outperforming all competitors who settle for less.

Just ask the team at Ariel Corporation. By integrating XTM translation memory software with its preferred CMS (Adobe Experience Manager) and MT engine (SYSTRAN), the industrial manufacturer cut human translation by 31% and doubled MT quality.

Here’s what the resulting workflow looked like, with TM software at steps two and three:

Ariel’s Content Systems Administrator, Ronald Egle, explained the win:

This is a grade-A example of how no single TM app can meet every enterprise localization need at once. However, with the right features and integrations, you can build a translation workflow that saves your business serious time and money.

Set a schedule to review and remove entries that no longer reflect your brand tone or product offering. This will keep suggestions sharp and prevent confusion during review.

Say you’ve rebranded ‘Customer Success Team’ as ‘Client Services.’ Update or remove segments using the old name so your team doesn’t accidentally use outdated language.

In XTM Cloud, you can filter out segments tied to discontinued products or seasonal promotions using metadata. That way, they’re still there but don’t interfere with live work.

Metadata adds context to every entry in your TM to automatically deliver more relevant suggestions. Tag segments by product, brand, region, content type, tone — anything that will help the system choose the best match in context.

Here’s an example of metadata for the term ‘castle’:

For example, a phrase like ‘check your balance’ might need a formal tone for banking apps in Germany and a more casual version for a US fintech audience. Region and tone tags ensure the TM serves the right one.

Make it clear who can add or update segments and how approvals for new entries work. This will stop duplicate or conflicting translations from cluttering your TM and causing confusion.

You can adjust what each user can access by choosing the appropriate role in their settings:

For instance, a clear policy might state that only senior reviewers can approve new entries and that all updates must have content type and date tags for consistency. Or limit changes to in-house translators who work closely with your products.