Where Does India’s Largest Listed Ad-Tech Firm Generate Its Revenue From?

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Synopsis: Affle 3i, India’s largest listed ad-tech firm, derives nearly all its revenue from its performance-based CPCU model, where it earns only when user conversions occur. Supported by vertical diversification and AI-driven consumer intelligence, the company monetises measurable user actions rather than ad impressions, distinguishing it from traditional advertising players.

The largest publicly listed ad-tech firm in India, Affle 3i Limited (previously known as Affle India), has based its operations on performance-driven digital advertising. Unlike conventional advertising agencies, which charge based on impressions or media buying, Affle’s business model is centred on measurable results. The earnings presentation for Q3 & 9M FY26 gives a precise understanding of where the company is getting most of its revenue from. 

With a market cap of Rs 19,354 crore, the shares of Affle 3i Ltd have closed at Rs 1,375 and are trading at a PE of 44.1 compared to its industry PE of 25.1. The shares have given a return of about 32% in the last 5 years.

Performance-Driven CPCU Model Drives Revenue

The major source of revenue for Affle comes from its Cost Per Converted User (CPCU) model. As per the company’s Q3 FY26 earnings presentation, 99.5% of the revenue from contracts with customers comes from the CPCU business model.

How the CPCU model works

The company generates revenue only when a specific user action occurs, such as app installs, registrations, purchases, in-app transactions, or even offline conversions (O2O). The performance-driven approach ensures that its incentives are directly linked with advertisers, making results rather than impressions the key revenue drivers.

The CPCU revenue calculation is straightforward: CPCU Revenue = Number of Conversions × Average CPCU Rate. As evident from the 9M FY26 performance trend, the conversion and stable CPCU rate are the key drivers of revenue.

Vertical Diversification Across High-Growth Categories

Affle’s revenue model is not industry vertical-dependent. Rather, it is verticalised across E, F, G, and H categories, which cumulatively account for 100% of the revenue. The categories include e-commerce, EdTech, entertainment, fintech, FMCG, foodtech, gaming, government services, groceries, healthtech, hospitality & travel and home utilities. 

This helps to mitigate risks associated with sectoral concentration while enabling the company to scale in high-growth consumer internet verticals. The company’s operations also highlight the broad-based geographic revenue growth, which is categorised into India & Emerging Markets and Developed Markets.

AI-Driven Consumer Intelligence & Platform Ecosystem

Affle is a consumer intelligence-driven global technology company. The company’s platform combines the functionality of demand-side platforms (DSPs), supply-side platforms, OEM partnerships, data management, and AI/ML algorithms to maximise user acquisition and retargeting.

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The company also points out that it has reached 3.9 billion connected devices in the last 12 months, which clearly indicates the size of its addressable ecosystem. AI-driven optimisation, fraud detection solutions (mFaaS), patented technology, and real-time predictive algorithms work together to improve conversion efficiency, which further fuels revenue growth through CPCU.

Apart from performance advertising, Affle also shows robust operating statistics with steady growth in conversions across quarters. The CPCU business is further growing with new user acquisition, retargeting, and offline-to-online conversion use cases, thereby reiterating revenue visibility. 

In conclusion, the revenue of the company is primarily driven by its performance-based CPCU business model, with diversified industry exposure and AI-driven consumer intelligence infrastructure. It does not sell advertising space but monetises user actions, which makes it distinct from the traditional media and advertising industry in India.

Disclaimer: The views and investment tips expressed by investment experts/broking houses/rating agencies on tradebrains.in are their own, and not that of the website or its management. Investing in equities poses a risk of financial losses. Investors must therefore exercise due caution while investing or trading in stocks. Trade Brains Technologies Private Limited or the author are not liable for any losses caused as a result of the decision based on this article. Please consult your investment advisor before investing.

  • Leon is a Financial Analyst at Trade Brains with experience of writing 500+ finance and stock market-related articles, supported by an MBA in Finance and Marketing. He brings a strong understanding of financial analysis, along with insights into the securities market. Experienced in analysing financials and business data, supporting research-driven decision-making, and presenting insights in a clear and structured manner



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