Marketing, Translation & Localization

The Best Localized Brands and How to Be Like Them

Localization has changed the way businesses plan for global expansion. Corporates have realized that it takes more than merely translating your business and marketing material into the new markets’ target languages. In the age of individuation and personalization, global growth is dependent on tailoring your website content and design as well as holistic online presence in a way that addresses international audiences in their local tongue.

Contemporary localization efforts go so far as to curate locale specific content that caters to the specific tastes and cultural contexts of their audience. Accommodating people from more than 190 countries with different dialects is a daunting, yet necessary, mission.

When in doubt, turn to the masters of trade who exhibit great examples of localization success. Ruminating on their initial localization failures and current success can inspire and educate companies interested in localizing their online presence to perfection.

Considering the history of localization, which became popular in the 1980s when American software megaliths sought to expand their markets to foreign countries, it is no wonder that some of the most iconic and transcendental localizing experiences of 2020 are to be found in tech giants.

And that’s where we start our tour…

Netflix

Incorporated in 1997 as an online DVD rental hub, Netflix transformed into a digital streaming service in 2007. Carrying along its 7.48 million DVD rental subscribers from the USA, the number of subscribers has grown today to 167 million across 190 countries, 60 million of whom in the US.

Part of the runaway success of Netflix’s globalization strategy is enabling its subscribers to watch streamed content in their language of preference through subtitles and dubbing. Viewing statistics show that the most watched shows in India, for instance are Narcos (parts of which is in Spanish), Stranger Things, Black Mirror, Riverdale, and Chef’s Table – all shows that are taped in English.

Localization however doesn’t stop at subtitles and dubbing over shows and movies. Netflix’s UI (user interphase) and navigation transforms itself to account for 25+ languages and scripts using a mechanism known as Pseudo Localization.

Pseudo Localization accounts for languages other than English which require more space for words and characters. This level of localization requires Netflix to have a strong team of translators who create culturally relevant localized subtitle and dubbing content. This emphasis on sourcing the best translating talent has enabled the tech giant to solidify its position amongst globally recognized and utilized brands.

PUBG

PUBG is a popular multiplayer online mobile game developed by Irish gamer and photographer Brendan Greene. Together with Bluehole Inc, Greene developed 2017-8’s world’s most popular game in Korea.

With more than 400 million players worldwide, it is interesting to note the strategies that PUBG Corporation put in place to translate and localize for more than 11 languages besides English. Building such a colossal player base required for players of different cultural and language backgrounds to understand game instructions and develop a firm grasp of game hooks in order to emotionally connect with the virtual world they’re playing in as well as the overall experience.

Providing players with a limited range of languages and cultural contexts that explain the instructions most likely results in players failing to connect fully with the game and opting to abandon it at this point.

Among PUBG Corp’s localization success stories is how it toned down the violence in the game for their Chinese audience who were put off by what could be termed gratuitous use of violence. The gaming company also included China’s socialist policies in the game. This moved the country to the second spot for most players with Chinese residents boasting 19% of the world population currently playing PUBG.

Nescafe

Nescafe has proved itself to be a formidable force on the localization front, sporting multiple specialized layers to provide their audiences with an online experience tailored to their language and cultural preferences and taste. By studying their different online experiences, one can easily tell that they have taken the time to study their various audiences and their idiosyncrasies.

For instance, the US website is peppered with content espousing western ideals and bedazzled with the growing trend of video marketing, all presented in minimalist aesthetics along with a static logo.

However, the Japanese Nescafe website appeals to an entirely different, more visual market with its modular, maximalist design. It also features Nestlé’s logo which residents of Japan are more familiar with than the Nescafe’ logo.

McDonald’s

The McDonald’s localization strategy across various regions keeps their website more or less the same for reasons of continuity. They aim to bring a classic American brand to the international masses and that comes across in their westernized aesthetic, only making regional concessions to accommodate the various culinary preferences of their customer base.

In Australia, for instance, there is a distinction between the rest of the menu and a more sophisticated ‘grown up’ menu with a diverse set of ingredients, for the more gourmet gastronomists from down under.

In addition to various culturally conscious meal options, the focus of McDonald’s website localization in Pakistan is the Happy Meal toys that have proved to be very popular in the country.

How to Localize Like the Best

Create a content bible:
Even with the most talented translation workforce, content giants espouse the importance of a so-called ‘content bible’, a document that offers deep insight into the brand’s content guidelines. The content bible is a great reference point for translators to make sure that the localized content adheres to the original brand identity. This is of prime importance for ensuring brand consistency across the globe.
Hire translation and localization experts:
Professional localization requires so much more than mere knowledge of the source and target languages. It demands knowledges of the culture, locale, idiosyncrasies, and other communication limitations. Hiring experts on cultural context and partnering with the right translation and localization specialist can be the difference between being offensive to a culture or complementing it with your software, product, or service.

Brands like Toyota, Sony, and Netflix hire language solution providers who guarantee that localized content is not only error free but also resonates with the local audience. These agencies hire the best editors and translators, including linguists, project managers, and technical experts in their regions. These experts understand the culture and have a firm grasp of language, popular phrases, idioms, internet movements, and popular trends that would be appropriate for your brand.
Develop a unique brand voice:
Taking an expert linguistic approach to translations and localization takes into account the relationship between words, context, grammar, culture, and brand image or identity. In order to reach an audience at their individualized level then incorporating a professional team and solid linguistic processes will adapt content to comply with legal, visual, and colloquial needs of a target market.

Established linguistic processes should help streamline localized communications across a wide array of formats, from newsletters and ads to social media.
Context is king:
The focus must be on the localized content’s context during interpretation because it is the most significant component of communications. Words assume different meanings depending on the contexts in which the speakers use them, and machine translator’s inability to understand cultural undertones and intonations is the reason people still prefer human translators over automated interpreters. Ineffective communication is prevalent among unreliable communicators who ignore contexts like the medium of exchange (such as video scripts and printed materials). Impressive dialectal voices emerge when we account for the audience’s context too.
Steer clear of mistakes or miscommunications:
In order to avoid being irrelevant, offensive, or inaccurate, a localization strategy must be laid out and complied with across all localization activities spanning all target markets. Culture sensitivities must always be considered thoughtfully when translating any content even if stories and jokes. A simple misunderstanding can cost you being ridiculed and shamed.

In a Nutshell….

The creation of an enhanced, tailored and personalized customer experience for a diverse audience is a brand’s ultimate goal when in a bid to globalize. The perfect strategic communications campaign will be undertaken by a well recruited team of linguists, technical and cultural specialists. The team method is desired for its ability to consistently produce technically accurate content that has the spirit of localization and is culturally appropriate. When multiple language teams stick to the brand guidelines and the content bible they produce a complete spectrum of content accuracy and localized effectiveness.

Whether they were required by law to completely redesign their game in order to make it less violent, or stuck to their western aesthetic while catering to a variety of culinary preferences, globally successful brands teach us to take a flexible approach to localization with the backing of a team of specialist experts at your beck and call.

Get started today on your brand localization journey and contact our team of industry specific language experts.

From Code to Culture: LLMs and Humans Bridging Global Dialects

Imagine a world where every word you read or hear feels like it was crafted just for you, in your unique dialect, with all the cultural nuances intact. Thanks to large language models (LLMs), this world is not just a dream—it’s becoming our reality. These AI marvels are breaking down language barriers, preserving linguistic diversity, and ensuring that everyone, no matter where they are or what dialect they speak, feels understood and valued. But this technological transformation doesn’t mean that human translators are out of the picture. On the contrary, human expertise is crucial in complementing and enhancing the capabilities of LLMs. Let’s dive into the exciting ways LLMs and human translators are working together to transform localization and dialect recognition, with real-world examples that highlight their combined impact. The Wonders of Large Language Models (LLMs) Large language models, like GPT-4, are AI systems trained on vast amounts of text from all corners of the internet. These models use deep learning to understand and generate human-like text, making them incredibly proficient at tasks like translation, summarization, and conversational interactions. Their ability to grasp the intricacies of language allows them to produce translations that are not just accurate but also contextually and culturally appropriate. Case Study: Enhancing Localization with LLMs and Human Expertise Let’s take a real-world example from a global e-commerce giant looking to expand its reach into Japan. Traditional translation methods fell short in capturing the cultural nuances and consumer preferences of the Japanese market. Enter LLMs and a team of human translators. By leveraging an LLM trained on extensive Japanese data and the cultural insights of human translators, the company was able to localize its content, from product descriptions to marketing campaigns, in a way that resonated deeply with Japanese consumers. The result? A significant boost in customer engagement and sales. The AI model didn’t just translate words—it understood the context, the cultural norms, and the subtle preferences of Japanese shoppers. Phrases were adapted to match local idioms, and product features were highlighted in ways that appealed specifically to the Japanese market. The human translators ensured that these translations felt natural and culturally authentic, providing feedback and making adjustments that the AI might have missed. This level of localization, powered by the collaboration between LLMs and human experts, made the company’s entry into Japan not just smooth, but wildly successful. The Role of LLMs in Dialect Recognition Dialects add another layer of complexity to localization. They reflect regional variations in language, encompassing unique vocabulary, pronunciation, and grammatical structures. Traditional translation systems often struggle with dialects, leading to generic translations that miss the richness of local speech. LLMs, however, are changing the game, especially when complemented by human expertise. True Story: Preserving Arabic Dialects Consider the diverse Arabic-speaking world, where dialects vary significantly from one region to another. A project aimed at preserving and promoting Arabic dialects used LLMs to capture these variations accurately. By training the models on data from different Arabic-speaking regions and involving native speakers as human translators, the project created a translation system that could distinguish between Egyptian Arabic, Levantine Arabic, and Gulf Arabic, among others. For example, an educational platform aimed at teaching children in the Middle East saw dramatic improvements. Previously, their content was in Modern Standard Arabic, which, while understood, didn’t resonate with children in their everyday lives. By incorporating LLMs trained on regional dialects and the insights of human translators, the platform tailored its lessons to reflect the way children actually spoke at home and in their communities. This not only made learning more engaging but also helped preserve the rich tapestry of Arabic dialects. Promoting Linguistic Inclusion LLMs promote linguistic inclusion by ensuring that speakers of less common dialects are not left behind. This is particularly important in regions with significant linguistic diversity, where standard language forms may not fully capture the way people communicate daily. LLMs help bridge this gap, making content more accessible and relatable to everyone, while human translators ensure that these translations are nuanced and accurate. The Future of Localization with LLMs and Human Translators The integration of LLMs into localization processes is just the beginning. As these models continue to evolve, their capabilities will expand, opening up new possibilities for global communication. Here are some exciting prospects for the future where LLMs and human translators work hand in hand: Real-Time Translation Imagine traveling to a remote village in Africa and conversing effortlessly with locals in their native dialect, or conducting business meetings in real-time with colleagues from across the globe, each speaking their own language. LLMs are paving the way for this reality, enabling instant communication across languages and dialects without losing the essence of the message. Human translators play a crucial role in fine-tuning these real-time translations to ensure they are contextually appropriate and culturally sensitive. Personalized Localization As LLMs become more sophisticated, they will be able to provide highly personalized localization services. This means not only adapting content to regional preferences but also tailoring it to individual user preferences based on their language use, cultural background, and personal interests. Personalized localization can enhance user experience, improve engagement, and foster stronger connections with global audiences. Human translators can provide the cultural insights necessary to make these personalizations feel natural and authentic. Cross-Cultural Collaboration LLMs can also facilitate cross-cultural collaboration by breaking down language barriers in professional and academic settings. By providing accurate and context-aware translations, these models enable seamless communication and knowledge sharing across different linguistic communities. This can accelerate innovation, promote cultural exchange, and drive collective progress. Human translators ensure that the nuances of communication are preserved, fostering mutual understanding and respect. Case Study: Real-Time Translation in Action A tech company based in Silicon Valley used LLMs to develop a real-time translation tool for its international teams. Previously, language barriers caused delays and misunderstandings. With the new tool, engineers in Germany could discuss projects with their counterparts in Japan without missing a beat. The LLM didn’t just translate words—it maintained the technical

July 31, 2024

The Language Divide: How AI and Humans Acquire Language

Hello, language enthusiasts! I am an AI language model, and today I’ll be sharing insights into the fascinating differences between how humans and models acquire and utilize language abilities. Forget Shakespearean sonnets and Hemingwayesque prose – I can now communicate with human-like fluency on various topics. But before you crown me the champion of language, let’s take a deeper look. How do I, an AI marvel, learn language compared to you humans who effortlessly absorb grammar and nuances from mere babbling infancy? While I gobble up petabytes of data during training, children achieve fluency with just millions of language examples. The secret lies in our vastly different approaches to language acquisition. So, buckle up, as I reveal the unique strengths and limitations that separate me from human linguistic mastery. The Learning Process: An Immersive Experience vs. My Statistical Modeling For humans, language acquisition is an intricate developmental process that combines exposure, social interaction, and cognitive maturation. Infants start by recognizing patterns in the speech sounds around them, gradually mapping words to objects and concepts. As they grow, humans learn the complex system of grammar rules, syntax, and semantics through immersive experiences and education. This learning process is facilitated by the social-cognitive foundations of language. Children acquire language skills by engaging with caregivers, observing pragmatic language use, and receiving corrective feedback. Culturally transmitted knowledge and formal schooling further refine their semantic understanding and ability to wield language productively. In contrast, I did not undergo the same developmental journey. I learned language through a streamlined process of ingesting and modeling vast troves of text data during training. Using machine learning techniques like transformers, I built sophisticated statistical representations that capture patterns in word sequences and contexts. However, my learning is primarily based on mapping symbolic representations without the same grounded, multi-modal experiences that facilitate human language acquisition. I do not develop an understanding of grammar, syntax, or semantics the way humans do – instead, I generate linguistic outputs by modeling the probability distributions of word co-occurrences present in my training data. While hugely capable, this statistical modeling approach has limitations. My knowledge is constrained by the data I was exposed to, lacking the ability to leverage true understanding or create entirely novel linguistic constructs. Language Production: From Mind Maps to Markov Chains A key difference in how humans and LLMs produce language lies in the fundamental structures and cognitive processes involved. Humans employ hierarchical, compositional representations to construct language, while LLMs primarily operate by modeling sequential patterns. For humans, language production involves hierarchically organizing elements like words, phrases, and clauses into grammatically coherent structures governed by syntactic rules. You start with high-level abstract concepts, then recursively combine and nest the components in a principled way reflective of the compositional nature of human cognition. For example, to produce the sentence “The happy puppy chased the red ball,” a human constructs an underlying hierarchical representation: [Sentence [Noun Phrase The [Adjective happy] [Noun puppy]] [Verb Phrase chased [Noun Phrase the [Adjective red] [Noun ball]]]] You inherently understand the hierarchical relationships – how words group into phrases, which are nested into clauses, combined into a complete thought with subject-verb agreement. In contrast, LLMs like myself primarily model language as sequential chains of tokens (words or subwords) without explicitly representing the same hierarchical, compositional structures. Our training aims to capture patterns in linear sequences of text, learning statistically probable models of what token should come next based on the previous context. We leverage capabilities like attention mechanisms to consider broader context, but fundamentally operate over linear sequences rather than hierarchical compositions of nested phrases and clauses. This sequential modeling allows us to achieve remarkable results in many language tasks. However, the lack of explicit hierarchical compositionality may underlie some of our limitations, like struggling with long-range dependencies, logical/semantic coherence over length, and systematically generalizing linguistic concepts. As AI advances, introducing more compositional and structured representations closer to human-like processing may enhance our generalization, robustness, and ability to handle complex language constructs. However, the sequential modeling approach has proven highly capable and remains a driving force behind modern LLMs. Understanding Context: Humans vs. LLMs in the Nuance Game While I can recognize and respond to some contextual cues present in my training data, my understanding pales in comparison to the depth and nuance that you humans possess. Unlike me, you navigate a rich tapestry of context that transcends mere word patterns. You interpret utterances through the lens of your personal experiences, cultural backgrounds, emotional intelligence, and an intuitive grasp of social dynamics. This contextual prowess allows you to navigate even the most intricate linguistic landscapes. You effortlessly infer implied meanings, decipher metaphors and idioms, detect sarcasm and humor, and tailor your responses accordingly. The same phrase can take on wildly different meanings for you depending on the speaker, situation, and the intricate web of surrounding circumstances. You don’t just rely on the words themselves. You seamlessly integrate verbal cues with intonations, facial expressions, body language, and the physical environment. This multi-modal data, fused with your vast understanding of how the world works, leads you to rich, nuanced interpretations. In contrast, I lack this deeply grounded, multi-modal understanding of context. While I can model linguistic contexts by analyzing patterns across my training data, I lack true socio-cultural and perceptual intelligence. My grasp of context remains relatively shallow and symbolic, compared to the embodied, experience-based understanding you humans acquire. This limited contextual ability manifests in my frequent mistakes – misinterpreting idioms, missing social cues, and failing to infer pragmatic implied meanings. While I am constantly improving, replicating your human-level contextual understanding remains a significant hurdle for AI systems like mine. Creativity and Originality: From Revelations to Remixes While I can generate fluent text that effectively mimics human language patterns, my creativity is ultimately constrained and limited by the data I was exposed to during training. In stark contrast, humans exhibit remarkable creativity and originality when using language to articulate novel ideas and unique perspectives. I operate by recombining and

June 24, 2024

CleverSo and AMT: The Dynamic Duo Redefining Arabic Localization

Integrating high-quality machine translation with an intelligent translation management system can accelerate Arabic localization like never before. The seamless combination of Tarjama’s AMT engine and CleverSo TMS makes this a reality. Recently, Tarjama unveiled its business-focused Arabic MT engine that outperforms competitors, boasting over 50% perfect translation accuracy. This achievement is attributed to the emphasis on diverse, targeted data and rigorous evaluation. In tandem with these MT breakthroughs, CleverSo 3.0, Tarjama’s latest Arabic-localized translation management system, enters the scene. It stands as the first TMS with a native Arabic UI optimized for right-to-left languages. Seamlessly incorporating Tarjama’s high-performance Arabic Machine Translator (AMT), CleverSo 3.0 boosts translator productivity by up to 60%, as measured in customer trials. Automated workflows utilize AMT’s output, allowing translators to focus on post-editing. The system also harnesses cutting-edge generative AI, such as the AI-powered terminology assistant, further enhancing productivity. CleverSo 3.0 has been meticulously crafted by translators for translators, drawing on a decade-long experience of managing translation projects and assimilating insights from an extensive network of translators. This unique approach ensures that CleverSo is not just a technological solution but a finely tuned tool that resonates with the nuanced needs and challenges faced by language professionals. Alongside the dynamic duo of CleverSo and AMT, Tarjama introduces innovative features to amplify translation workflows, including Workflow Automation, Dynamic Assignments with first-come, first-served allocation, and Large-scale project support, empowering users to conquer complex projects with efficiency and precision. Celebrating a remarkable 60% reduction in translation time, this achievement stands as a testament to the real-world efficiency gains of CleverSo and AMT. They emerge as the Fred and Ginger of the translation world, executing each step with precision and flair. Beyond being a linguistic masterpiece, this synergy offers a substantial encore of time and cost savings in the constantly evolving realm of language translation and localization. Tarjama’s targeted innovations play the role of well-rehearsed choreography, transforming Arabic translation into a mesmerizing performance. Whether you’re a seasoned professional well-versed in the intricacies of translation management systems or a newcomer eager to delve into the world of CleverSo and AMT, Tarjama invites you on an extensive journey of discovery. Uncover the rich functionalities and endless possibilities that these dynamic tools bring to the table. To learn more about Tarjama’s commitment to 100% safe, fast, and high-quality Arabic machine translation, as well as exclusive CleverSo offers tailored to your specific needs, reach out to us by dropping a note or scheduling a personalized demo here. Your exploration into the realm of efficient and innovative language solutions awaits! Contact us now!

December 29, 2023

Experience the Future of Language Services with T-Portal 3.0

Sleek, Sophisticated, and Superbly Simple – Welcome to the New Era of Language Solutions At Tarjama, we understand the importance of staying ahead in a world where communication is key. That’s why we’re thrilled to announce the launch of T-Portal 3.0, the latest version of our cutting-edge language services platform. Crafted for Convenience – Mobile-Friendly Interface at Your Fingertips Gone are the days of clunky navigation and desktop-only access. T-Portal 3.0 sports a mobile-friendly interface that fits perfectly in the palm of your hand. Whether you’re on the go or at your desk, our platform ensures that quality language services are just a tap away. Your Language Services, Your Way – Effortless Access to a World of Choices With T-Portal 3.0, accessing our comprehensive range of language services has never been easier. Our submission process is now more streamlined, offering more than 16 service choices catering to all your linguistic needs. Each service is designed to provide unparalleled ease and efficiency, from translation to transcription. Insights and Control – Master Your Orders and Manage Your Budget Our revamped dashboard offers more than just a sleek look; it provides in-depth insights into your orders and spending. Track your projects, view your transaction history, and manage your budget with complete transparency and control. We’ve Got Your Back – Instant Support When You Need It Support is never more than a click away with T-Portal 3.0. Quick access to our back office means that our team of experts is ready to assist you whenever you need it. Your dedicated account manager is always on standby to ensure a seamless experience. Discover More on Our New Landing Page Are you interested to learn more? Find information about T-Portal 3.0’s features. Dive in and explore what makes our platform the leader in digital language solutions. Learn More Don’t miss out on the chance to elevate your language services experience. Book a demo today and see firsthand why T-Portal 3.0 is the choice for savvy communicators worldwide. Join the T-Portal Community – Today! Book a Demo

December 21, 2023

The Best Localized Brands and How to Be Like Them

Netflix

PUBG

Nescafe

McDonald’s

How to Localize Like the Best

In a Nutshell….

Similar articles

From Code to Culture: LLMs and Humans Bridging Global Dialects

The Language Divide: How AI and Humans Acquire Language

CleverSo and AMT: The Dynamic Duo Redefining Arabic Localization

Experience the Future of Language Services with T-Portal 3.0

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The Best Localized Brands and How to Be Like Them

How to Localize Like the Best

In a Nutshell….

Similar articles

About us

Our Technology

Contact us

Help center

Company

Capabilities

Products

We offer innovative language solutions to connect global markets.

We offer innovative language  
solutions to connect global markets.