If we want to position Localization as a product, how do we measure its value?
In my last post, I talked about shifting our mindset from localization as a service to localization as a product. Not as something that replaces it, but as something that complements it to expand the scope of our Globalization activities as Localization professionals. A lot of people connected with that idea. Some people reached out to say they often feel stuck reacting to requests and want to move toward building something more scalable and impactful. They found the post interesting in exploring what localization might look like if it were treated as a product. I received an email that I found quite interesting. While I was reflecting on the question, I realized it might be a good idea to write a second part to that previous post, going deeper into that question.
The question was about metrics, a topic that usually gets a reaction from anyone working in this field. Measuring what we do has become something necessary if we want to elevate the impact of our work.
The actual question was: if we want to treat Localization like a product, what kind of metrics should we be exploring? I honestly thought it was a very interesting question, because if we want to treat Localization like a product, we also need to measure it differently. We need to go beyond the usual metrics and add a new layer that reflects the systems, tools, and workflows we’re building to support the business. Because those three elements system, tool, and workflow are what help us evolve Localization from a service into a product.
The traditional metrics aren’t going away
That said, classic localization metrics still matter. They’re our internal compass; they remind us that we need to ensure the basic localization work is running as expected. Typical metrics like translation volume, cost per word, delivery turnaround times, bug counts, or LQA scores by language or vendor are not something we can (or should) ignore because they’re important. These give us the visibility we need to track quality and efficiency and to know that we’re moving in the right direction.
While these metrics are necessary, they don’t show the full picture, particularly the new picture we are trying to build, which is Localization as a product. These traditional metrics only show what’s happening inside the localization ecosystem. If we’re evolving our role and building scalable solutions for the company, we also need to track how others are using and benefiting from what we’ve built.
That’s where product-style metrics come in.
Below are four metric categories we can adopt to measure how our journey is going in turning Localization into more than just a service, and closer to a product.
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Adoption
Adoption is one of the clearest signs that our product mindset is working. It’s not enough to create workflows, portals, or documentation. We need to know if stakeholders are actually using them. If we set up a self-service portal and nobody uses it, that’s a signal. If we publish a glossary but teams still ask the same terminology questions, something’s missing. But if more content requests are coming in through standardized workflows, if teams are referring to the materials we created, or if they’re using a custom GPT that we trained with our guidance, then we’re seeing adoption. And that’s something to be happy about; it’s a clear sign that what we built has value. It’s working and being integrated into other teams’ ways of working.
Metrics that matter aren’t always one-size-fits-all. Each localization team works in a different context, and what’s meaningful for one product or company might not apply the same way somewhere else. That’s why we need to be a bit creative when thinking about how to measure adoption. The key is to adapt the metrics to reflect how your team operates, the tools you use, and the type of collaboration you have with other teams. That said, if you’re looking for a starting point, here are a few adoption-focused metrics that can help you begin to understand how well your systems and resources are being used across the company.
Adoption metrics:
Number of content requests submitted through self-service workflows instead of email or chat
Number of teams actively using shared glossaries, style guides, or localization portals
Frequency of use of custom GPTs or automation tools built by the localization team
Number of new stakeholders onboarded through your localization starter kit or intro sessions
Automation impact
Automation helps in different ways. It helps save time, but it’s also a shield that protects our focus. When we automate tasks like formatting fixes, intake steps, or ticket creation, we’re freeing ourselves from repetitive work so we can spend more time on what really needs our input. We start to see the impact when those same problems no longer land on our desk, or when we notice we’re spending more time building and less time fixing. When that starts to happen, it’s a clear sign that we’re working smarter. And when we can show how many hours or steps we’ve saved thanks to automation, it becomes clear that we’re fast and we’re effective!
Automation helps us save time and reduce repetitive work. It gives the team more room to focus on important tasks. Every team is different, so the results may look different too. These example metrics can help you see where automation is helping and how to track it.
Automation impact metrics:
Number of repetitive tasks automated (e.g. ticket creation, formatting cleanup)
Estimated hours saved per month through automation or AI-assisted workflows
Percentage of localization requests that no longer require manual follow-up
Reduction in time-to-launch for projects that used automated components
Strategic influence
This one is harder to measure, but it tells you that the role of localization is growing. These metrics are about when and how your team is involved in decisions. It shows whether localization is shaping product or content choices, not just reacting to them. It’s about the impact on decisions.
When we’re involved earlier in the process, like during MVP planning or UX design discussions, it’s because people see our input as important. Maybe a team changed how they handled dates or formats based on our feedback. Maybe we helped adjust a feature to work better for more languages. These are examples of influence. We’re not only asked to translate but also we’re being asked to contribute. That’s a sign of trust, a sign that we’re starting to be seen as partners, not only as a service.
It’s not always easy to measure influence, but there are signs that show when localization is becoming more strategic. One of them is being involved earlier in the process when decisions are still being shaped. These example metrics can help you track that shift and show how your team is helping shape product decisions, not just support them.
Strategic influence metrics:
Percentage of product teams involving localization at the MVP or design stage
Number of product or UX decisions influenced by localization feedback
Inclusion of localization input in planning docs or kickoff decks
Number of projects where localization was consulted before launch planning
Internal visibility
Internal metrics are about who sees your work and how much they understand or rely on it.
Visibility is about helping people understand what we do without always having to explain it. When teams attend our Localization onboarding sessions, use our documentation, or reference our Globalization analytics dashboards in meetings, it shows that our work is visible and useful. Even small things count, like a stakeholder saying, “I followed your Localization guide and it helped,” or a product manager thanking you for a tool that saved them time. These little signals build trust. They help others see our value more clearly, and that trust leads to earlier involvement and stronger partnerships.
Internal visibility metrics:
Number of teams attending localization onboarding, demos, or training
Page views or downloads of internal documentation or dashboards
Mentions or links to localization resources in other teams’ wikis or presentations
Stakeholder feedback on ease of collaboration with localization
Adoption Metrics Tracking Summary
To make things more practical, I’ve summarized a few key adoption metrics and how you can track them using tools you likely already have access to. This isn’t meant to be a complete list, but it should give you a good starting point to assess whether your effort to position Localization as a product is gaining any traction.
Final thoughts
We still need our traditional metrics. They help us run localization with quality and efficiency. But if we’re serious about Localization as a product, we also need to measure how others are using those things and how they help the company scale.
Tracking these signals, adoption, automation, influence, and visibility, helps us show that we’re localizing content and building infrastructure that makes global work easier, faster, and better. And if we want our role to grow, that’s exactly the kind of story we need to tell.
@yolocalizo
If we want to treat localization like a product, we need to measure it like one. Traditional metrics like cost per word and delivery time still matter, but they don’t capture the full picture. In this post, I share four categories of product-style metrics: adoption, automation impact, strategic influence, and internal visibility that they can help you track the real value your localization team is creating across the company.