The monetization paradox of multilingual audiences

In India, the same reader is worth a dollar in English and 25 cents in another language. The advertising industry prices by language rather than by person, creating a fundamental disconnect between audience scale and commercial value. For global businesses, that raises a bigger question about how well they really understand multilingual customers.

Every boardroom presentation about international expansion includes a slide with a big number on it, folding market size and internet penetration into a total that is always impressive. It also almost always leads to the same mistake, where teams treat the market as though the people inside it think and buy as one.

As Teja Chekuri, founder of Fullstack Ventures, wrote in Forbes this year, most brands that fail internationally do so because they mistake replication for expansion. Replication assumes that what worked in one context will transfer to another, while expansion requires learning what each new context demands on its own terms.

Nowhere is that lesson more expensive to learn than in India.

Why proximity is a risky assumption in content strategy

India’s internet population has crossed 900 million and is heading toward 1.5 billion by 2032. The instinct for any global content or product leader looking at that number is to build for scale. But scale in India is dozens of levers, each operating on different mechanics.

Nandagopal Rajan, CEO of The Indian Express Digital, has spent more than a decade navigating this complexity. He runs a 550-person digital news operation that reaches over 100 million monthly visitors across five languages, and he is blunt about the foundational error that trips up almost every outsider and more than a few insiders. 

“If you consider India as one homogeneous unit, you’re going to fail, whatever be your product.”

That failure tends to follow a pattern. A team builds a product or content strategy that performs well in one Indian language or region, assumes the model will transfer to a neighboring market, and watches it collapse. Nandagopal experienced this firsthand when he launched Indian Express’ first regional language edition in Malayalam, his mother tongue. It was reasonably successful. The next edition was Tamil, a language spoken in the neighboring state, with cultural similarities and even some linguistic overlap. 

“I thought a lot of my learning there could be used in Tamil. It didn’t work at all.”

Tamil has a different relationship with its own identity. It is one of the oldest living languages in the world, with a literary tradition that predates most European ones, and its readers have expectations that cannot be imported from a neighboring market, no matter how geographically close. Proximity, it turns out, can be particularly misleading because it creates a false sense of familiarity that delays the harder work of understanding audiences on their own terms.

Where the economics of attention fall apart

The fragmentation runs deeper than editorial preferences. It reaches into the economics of attention itself. English-language digital content in India commands CPM rates three to five times higher than Hindi content in the same category, and five to eight times higher than content in regional languages like Tamil or Malayalam. Those figures vary by platform and category, but they illustrate the scale of the disparity. On paper, that creates a straightforward incentive to prioritize English. In practice, it creates a distortion that most global operators never fully grasp.

As Nandagopal points out, the readers are often the same people. 

“Most of us are multilingual. If I’m reading in Malayalam, I’m also reading in English. So I’m the same audience. But if I am targeted on a Malayalam page, I’m targeted at 25 cents instead of a dollar in English.” 

Language can therefore materially affect the commercial value assigned to the same person depending on which tab is open in their browser.

For any business building a multilingual content strategy in a complex market, this is a structural challenge that no amount of audience growth can resolve on its own. The numbers will always look extraordinary, but reach alone says surprisingly little about the economics underneath them. Nandagopal puts it simply. 

“An American publisher with 10% of our audience would be making 10 times more money than us.”

Language as intelligence

The temptation, naturally, is to throw technology at the problem. AI-powered translation and content personalization at scale are both getting better, but they carry their own version of the same assumption, that a system trained or configured in one context will perform well in another.

Freddie Braun, who has led global content at Klarna, Net-A-Porter, Condé Nast and now Monzo, described this dynamic on the In Other Words podcast earlier this year.  “People can tell when something wasn’t made for them”.

His argument is that translation alone rarely creates the familiarity that builds trust or engagement, and that automated systems tend to replicate the assumptions of whoever designed them. 

When content feels borrowed, audiences disengage, regardless of how accurate the language is. Freddie argues

“Translation is necessary but it’s the cultural orchestration of language, visuals, and journeys that makes a product feel native and safe to use.”

The monetization paradox points to a larger problem. Most businesses still treat language primarily as something to deliver rather than something to learn from.

The market has already been selected, the audience defined, and the customer journey designed. Language then enters the process as a means of making that experience available elsewhere.

But multilingual markets expose the limits of that model.

The underlying problem is that most content operations treat language as a delivery mechanism, something to be converted from one form to another, when it is closer to a form of intelligence. Which language a reader chooses, how they navigate between languages, and what they expect in each one all carry signals about context, relevance, and preference that a pure translation workflow discards.

The same customer moving between English and Malayalam is not simply creating two translation requirements. They are generating information about how they consume content, what they expect in different contexts, and potentially how they move through a customer journey.

This is the distinction behind language intelligence. Language should not sit only at the end of the content process. The knowledge embedded within it should inform the decisions businesses make about audiences and markets.

That observation applies with particular force in markets like India, where a single user might consume content in four languages before lunch and evaluate each experience against a different cultural expectation. 

AI makes that understanding more important. It is becoming dramatically easier to produce multilingual content at scale, but the ability to create more versions does not mean a business understands more about the people receiving them. AI can scale assumptions just as efficiently as it scales content.

Organizations that operate across genuinely fragmented markets have started building differently. One global travel services company working across 40 markets and 20 languages restructured its entire content operation around automated workflows that could be configured by local project managers rather than centralized developers, using the Phrase Platform. Within three months the company had doubled its multilingual content output while improving quality.

The more interesting change was structural. Local teams could make more decisions closer to their audiences while still operating within shared standards and infrastructure. Instead of forcing market knowledge through a centralized production model, the organization could combine local context with the governance needed to operate globally.

That balance is becoming harder to achieve as multilingual content creation spreads beyond specialist teams. Employees, applications, and AI agents can increasingly create content themselves. The challenge is ensuring that the language knowledge surrounding the brand, customer, and market can travel with them.

That is where a Language Intelligence Platform becomes fundamentally different from traditional translation technology. It provides a common layer through which terminology, quality expectations, brand context, automation, and local knowledge can inform multilingual decisions wherever they are being made.

When relevance becomes the strategy

The assumption that a big market is a single audience sits in the strategy deck and in the org chart that puts one regional lead in charge of a territory with more linguistic and cultural variation than the whole of Western Europe.

India is the most visible proof case because its scale makes the consequences impossible to hide. But the same dynamic plays out across Southeast Asia and Latin America, and increasingly in multilingual European markets where audiences expect content that reflects how they think, not simply the language they speak.

For executives building a global content strategy, this changes the question. It is no longer enough to ask how many markets, languages, or customers the organization can reach. They need to understand what those languages are telling them about the audiences behind the numbers.

Where are customers moving between languages? Where does a message that performs globally stop working locally? Which market differences should alter the experience itself rather than simply the words used to describe it? And which signals should feed back into the next business decision?

In India, Nandagopal has seen the consequences of those assumptions wrong for a decade, and the publishers who invested in understanding each audience, language by language and market by market, are the ones still growing.

AI will make multilingual reach easier than it has ever been. The advantage will come from understanding what happens after that reach is achieved.

The monetization paradox makes the point unusually clearly. The same person can carry a different commercial value simply because they switched languages. For businesses, language cannot remain the only the mechanism used to reach an audience. It has to become part of the intelligence used to understand one.