Localisation is Strategy, Not Semantics
In India, content must reflect the language of trust, identity, and belonging.
India is a linguistic giant. The 2011 Census recorded 121 languages spoken by 10,000 or more people, and over 19,500 distinct mother tongues were reported. The people’s linguistic survey of India estimates more than 780 actively spoken languages, making India one of the most linguistically diverse countries in the world.
For global brands, this diversity represents both an incredible opportunity and a daunting challenge In a market, where regional marketing is on the rise, the “one-size-fits-all” approach is no longer an approach that works. Content strategies must now balance the intersection between language, culture, and context to connect with India’s polyglot audience.
Yet, localisation falls short. Brands equate it with mere translation, overlooking the importance of cultural nuance, emotional resonance and context. Youtube ads in Mumbai assume Marathi is the preferred language, ignoring the region’s multi-lingual demographics. Similarly, platforms like Netflix and Prime offer subtitles in multiple languages but often miss the subtleties that make content truly relatable.
This failure to localise deeply has its consequences. Poorly adapted content or over-reliance on the assumption of widely spoken language can alienate audiences, erode trust and harm brand loyalty. For instance, Google Assistant’s initial limitations in supporting Indian languages reduced its usability among non-English speakers.
Localisation in India is an evolving process and it requires continual support and investment. It cannot truly be “complete” because it is complex and nuanced. This article explores why localisation matters for content strategy, how it must evolve, and the lessons brands can learn.
Localisation Beyond Translation:
Localisation is more than just translation. It is adapting content to reflect cultural and contextual nuances. While translation converts words, localisation ensures that you understand your target audience.
For instance, transcreation, which creatively adapts content to evoke specific emotions or persuasive effects, is critical in a market like India. This process is costlier than traditional translation. However, it pays off in the long run by building stronger connections with diverse audiences.
So why do brands fall short of true localisation?
One reason being, rigid reliance on formal language fails to reflect code switching habits in India, where users seamlessly shift between languages. The other is inconsistent language integration where product interfaces are translated but it neglects crucial touchpoints like FAQs and customer support. This alienates users and diminishes trust.
Cultural relevance directly impacts audience engagement. ShareChat thrives by delivering vernacular content in over 15 Indian languages, dominating tier-2 and tier-3 markets. Similarly, Spotify’s regional language music curation helped it compete with established players like JioSaavn and Gaana.
Conversely, LeEco’s failure to adapt its content strategy for India demonstrates the high cost of overlooking cultural nuances.
True localisation integrates language, culture, and context to create content that connects, engages, and retains audiences.
Gaps in Technology for Indian Localisation:
Despite India’s vast multi-lingual diversity, AI powered localisation tools remain limited in their ability to handle the country’s full range of languages and dialects. While AI models like ChatGPT have improved their multilingual capabilities, they still struggle with critical distinctions, such as differentiating between Bengali and Assamese. This lack of precision affects automated content strategies, making it difficult for brands to scale localised content effectively.
One of the biggest barriers to AI-driven localisation is data scarcity. Many Indian languages, particularly those classified as low-resource languages (such as Bodo and Sindhi), lack sufficient digital data for effective AI training. Building datasets requires collaboration with linguists, local institutions, and native speakers: a resource intensive process that is often overlooked.
The consequences of excluding lesser-spoken languages extend beyond accessibility. It prevents technological advancements in Indian linguistic AI, leading to digital marginalisation. Furthermore, neglecting these languages threatens cultural preservation, as fewer people can access digital content in their native tongue. For content strategists, this gap represents an untapped opportunity: one that brands willing to invest in deeper localisation can leverage for competitive advantage.
Lessons from Duolingo and Music Metadata:
Duolingo introducing English for Tamil speakers is a strong step towards linguistic inclusivity.
Even better? They’ve woven in cultural touchpoints, making lessons feel familiar and engaging. From everyday phrases to locally relevant contexts, it’s a nudge in the right direction.
But there’s still room to grow. Imagine Tamil-to-Hindi, Tamil-to-Telugu, or other regional pairings: acknowledging India’s multilingual reality. Expanding beyond English would truly unlock the full power of language learning for Indian users.
Similarly, music streaming platforms rely on metadata tagging to power discovery, yet they still operate within a Western classification system. Indian music is often miscategorized, with diverse regional genres lumped under broad labels like ‘Pop’ or ‘Folk.’ Platforms that refine their metadata to recognize linguistic and genre fluidity such as bilingual tracks or fusion genres will gain a stronger foothold in India’s competitive music landscape
For true localisation, platforms must move beyond translation and integrate cultural intelligence, ensuring that learning feels relatable and content discovery is intuitive, inclusive, and reflective of India’s linguistic and cultural depth.
Conclusion:
Localisation in India is not a one-time effort but an ongoing process that requires continuous adaptation. A simplistic translation approach fails to engage diverse audiences. Brands must invest in regional datasets, collaborate with linguists, and embrace community driven localisation to ensure authenticity.
Open source initiatives can further democratise language technologies, making localisation efforts scalable and inclusive.
To succeed, brands must move beyond translation and treat localisation as a dynamic, participatory strategy. Crowdsourcing efforts, such as user submitted slogans, regional storytelling, or interactive ad campaigns, can deepen cultural resonance. Amul’s iconic user generated ads exemplify how co-creation strengthens trust.
Hindi and English maybe considered India’s default business languages, but they do not represent the full spectrum of the country’s linguistic reality. Millions of users prefer consuming content in their native tongue.
Brands that thrive will be those that listen, adapt, and co-create, treating localization not as a value-add but as a foundation for a successful long term strategy.
Words matter, but context matters more and in India, content strategy demands both.