All tagged Localization

But .. how do we move to the left!?

Localization is often seen as an afterthought, focused on translating content late in the process. This post looks at how Globalization teams can step in earlier by identifying invisible tasks and using AI tools like to influence decissions from product teams to create products designed for global audiences. It’s about rethinking localization as a strategic partner instead of a support function

What localization tasks are different when working on the buyer side?

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

How the Globalization Team Creates Alignment

Words have the power to shape perceptions and influence actions, which is why reframing is such a powerful tool. In localization, we can reframe our role from simply translating to driving alignment across the company. By ensuring content is consistent, culturally relevant, and strategically aligned with business goals, localization professionals play a key role in helping businesses grow globally. This post explores how we create that alignment and why our work is much more than just translation.

After the Launch 7 Post-Localization Activities to Keep in Mind

Post-localization activities are crucial for maintaining high-quality localized content even after a product launch. These include collecting user feedback, monitoring translation consistency, and ensuring legal compliance, all of which aim to improve the user experience. Continuous efforts in localized SEO, metrics tracking, and stakeholder alignment keep your localization strategy strong and relevant across global markets—and this post covers all that!

Key Ingredients for a Localization Strategy in a Changing World

In this post, I compare the excitement of discovering the internet to the rise of AI in localization today. With tools like LLMs and GPT, we’re at a turning point, and staying curious, planning carefully, and aligning efforts are key. Missing any crucial element, as shown in the infographic, could hinder progress. A "slow and steady" approach is essential as we navigate this change.

Dealing with change: overcoming resistance in Localization strategy execution

We’ve all heard the saying that “change is always good,” right? Wrong. We don't like change; we don't like to step out of our comfort, but still, change must happen. I've been studying "Change management and resistance to change" in the last weeks because change is the norm in our #localization industry. In this post, I summarized my learnings so far! I hope you find it useful ☺️

Common Localization KPIs pitfalls!

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.

 

Optimizing Localization User Feedback with 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.