When leaders push back on localization time, resources, or AI, the strongest answer is not to defend every step of the process. It is to reframe the conversation around risk.
In this post, I explore why explaining Localization from a quality perspective, with too many process details, may not always be the best strategy when speaking with senior stakeholders.
This post explores the key differences between working on the buyer versus the provider side of the localization industry. While there are some tasks common to both, others vary significantly in areas such as people management, operations, strategy, and metrics. The article breaks these tasks into four categories, providing examples for each to highlight these distinctions
LLMs don’t learn your brand style just because you use them more. They improve when someone guides them, feeds them with examples, corrects them, and owns the outcome. In this blog post I reflect on how we can create a strategy to do that
Several factors affect the duration of localization for a digital product, including translators' availability and the technology setup level. This blog post explores the various elements that impact the amount of time needed for product localization.
In some RFPs today, it is no longer so clear what buyers really value from LSPs. This post explores why. Based on my experience on the buyer side, I share why the real need may be shifting from pure execution toward something harder to explain, but often more useful in practice.
What do you do when someone asks for the ROI of localization and you know the question is too narrow from the start? In this post, I reflect on why I stopped trying to prove isolated ownership and started talking more honestly about contribution.
Reading The Myths of Happiness reminded me of the arrival fallacy: the belief that once we reach a certain goal, everything will finally feel solved. In localization, that can look like waiting for the day when people will finally understand what we do. But organizations keep changing, so that moment may never fully come. And maybe accepting that is exactly what helps us stay grounded, avoid frustration, and keep moving forward.
In many companies, the localization budget does not sit with the localization team. At first, that may seem like a small detail. But over time, it changes how localization influences strategy
Defining localization metrics is relatively easy. In many cases, a team can write a reasonable list during a workshop, like the ones I mentioned above, or during a strategy session. The conceptual part of what to track and why rarely takes long. The real difficulty appears later: HOW you actually obtain those metrics.
“Welcome to my blog. The space where I document my passion about Localization, Project Management and Leadership”
Several factors affect the duration of localization for a digital product, including translators' availability and the technology setup level. This blog post explores the various elements that impact the amount of time needed for product localization.
I'm passionate about Localization metrics, but it can be frustrating. We live in a data-rich world, allowing us to measure our impact better. However, this data abundance brings challenges when building a Localization metrics system.
In my experience, two main pitfalls emerge (but they are not the only ones 😅). One is overemphasizing Localization ROI, which can lead to unproductive discussions. The other is tracking effort-related KPIs without translating their impact on company success into terms that matter to leadership and product owners.
In this blog post, we explore 3 ideas on how to assess the quality of your localization content with the help of ChatGPT
A major challenge in Localization is defining quality. There's confusion around perceived quality, linguistic/grammatical quality, and clients' tolerance for low-quality translations. Some clients accept minor errors, while others are horrified by poor translations on product labels.
Models like J2450, LISA, and TAUS measure quality but often don't convince product owners or teams to support localization programs. Localization teams focus on quality, while product teams focus on revenue and user engagement.
User feedback can align both teams. Poor feedback can jeopardize a product's future, but explaining how poor linguistic quality impacts long-term growth is challenging. Gathering feedback from international users is crucial for aligning goals.
Analyzing feedback is often overwhelming due to the volume and qualitative nature of the data. Feedback comes from various channels, requiring careful reading and interpretation.
ChatGPT can help by automating and streamlining feedback analysis. It handles large volumes of feedback, interprets qualitative data, filters noise, and bridges language barriers, leading to actionable insights and better decisions.
Ever found yourself juggling the complexities of localization solo?
What happens when the need for expansion knocks on your door? It's time to build your tribe!
This blog post covers the phases of transitioning from a one-person localization department to a functional localization team. From pitching the need for expansion to laying the foundations for continuous improvement,
Chain of Thought (CoT) Prompting is a method in AI models like ChatGPT that breaks down questions into smaller, logically ordered sub-prompts. This step-by-step approach helps the AI generate more accurate and coherent responses, making its reasoning transparent and easier to trust. Among the different CoT techniques, the Zero-Shot Chain of Thought is my favorite.
Every decision a team makes affects not only a digital product's accessibility but also how easily it can be adapted to different markets. Therefore, everyone involved in creating software can help improve both accessibility and localizability. Accessibility is a core consideration in software development and must be integrated into the entire process. The same applies to localization. The best time to consider localization is during the product's ideation phase. The sooner we start thinking about adapting experiences for different markets and making the product usable for as many people as possible, the better. Taking advantage of this week's Accessibility Awareness Day, this post explores how accessibility and localization can join forces to remove barriers.
The power of positive and negative together: The science of mental contrastingThe sweet spot for achieving something is when there is tension between the positive and the negative. And that's a model we can use in this moment where AI is in the spotlight
We move between three approaches when considering how to reach a desired outcome.
1.- INDULGING
2.- DWELLING
3. -ACTIVE CONTRASTING
Localization is all about adapting content from one culture to another, from one market to the next. The tricky part is the thin line separating appropriation and appreciation. The challenge is to adapt content respectfully and give proper credit. It's easy to blur the line between appreciation and appropriation. My post this week reflects on that.
Much is said about AI's threat to professionals in the localization industry. But the truth is that the AI + human combo has a lot of potential. In this blog post, you can learn about the role of an internal Localization team in the AI era.
Creating quality online content adapted to different markets is more important than ever. Our world revolves around content. These days, buying decisions are often based not only on experiences with products, but with information about products. Naturally, with the growing importance of content, a lot of attention is being paid to content strategy. This is a good thing. Companies need to stop throwing content out to the world without a good reason. They need to manage content strategically.
But what about global content? What about all the content that your company produces for people in other parts of the world?
What areas should a localization team consider when collaborating efficiently with a game publisher operating on a GaaS model?
This blog post covers the main elements you cannot ignore when considering implementing a Localization strategy to support developers operating under the GaaS framework.
We all live our particular Groundhog Day; regardless of what we do, some things come back again and again.
Translators and AI: A PartnershipIn this post you can find a list of ideas, areas in which a translator can rely to be more efficient in their day-to-day tasks.
The basic principle of strategic decision-making is based on understanding the impact of our decisions on the future in the decisions we make today.
But, of course, that's more complex than it seems because of cognitive biases. The topic of cognitive biases is fascinating; we all have cognitive biases, and to make matters worse, we don't know we have them. Identifying them is vital since overcoming cognitive biases helps us think more critically and objectively, and we end up making better decisions as a result.
But how can we identify a bias if we don't know we have it? chatGPT to the rescue!"
ChatGPT is a fantastic tool, and in this post, I explain things I have discovered after a year of use
There's a reason that I started observing last year and have consolidated this year as another reason for questioning the impact of localization, and that is Unfamiliarity with how Localization supports DEI (Diversity, Equity, and Inclusion):
It’s really important to check how well our creative work is doing. Even though measuring the quality and efficiency of our localized content isn't easy, that doesn't mean we should give up! We use KPIs to see how our content is performing—whether it's catching people's attention, encouraging them to do something, or influencing how they see our brand. Each KPI tells us something different, and when we look at them all together, it helps us figure out what's working well and what needs a little tweaking. This blog post is all about how to measure KPI creative efforts!
In this post I look at how we can embrace AI, particularly chatGPT to stay relevant !
Usually, when we want to improve something in our Localization strategy, we first set an ambitious goal. From there, we design a strategy to reach it as quickly as possible. If we don't see rapid changes, we feel like we're not improving. To break this cycle, we can try changing the way we set goals—smaller, but consistent objectives that, when we look back, show us that we are indeed making progress. This progress can be the driving force for us every week, every month, every year.
Here are some ideas on how we could apply this Kaizen methodology in the Localization world.
AI promises faster localization, and that message is attractive. But in many teams, the real issue is not speed. The work gets delivered. The harder question is how much hidden coordination, unclear ownership, and workflow complexity it takes to get there.