Why aggregation theory doesn't work in India ?
Trust-Based Niches, Monetization Struggles, and a New VC Approach
Ben Thompson’s Aggregation Theory reshaped our understanding of digital success by explaining how companies like Google, Facebook, and Amazon leverage the internet to bypass traditional distribution and directly connect with consumers.
Aggregation Theory is built on three main pillars: direct consumer relationships, supply aggregation, and scalability with low marginal costs.
1. Direct Consumer Relationships: Aggregators build their power by directly engaging users, creating dependency through constant interaction, like social media feeds or product recommendations, which traditional businesses struggle to replicate.
2. Supply Aggregation without Ownership: Unlike traditional companies, digital aggregators don’t need to own the supply—they aggregate and control access to it. Google organizes web content, and Amazon aggregates retailers, while both companies maintain consumer control.
3. Scalability with Minimal Marginal Costs: Digital aggregators can add users at minimal cost, leveraging network effects that drive exponential growth. In doing so, they achieve scale and profitability faster than companies constrained by physical goods and infrastructure.
This model has been fundamental to Silicon Valley’s venture capital success, enabling VCs to back companies capable of dominating markets and yielding outsize returns.
The expectation has been that aggregators could monopolize consumer attention and create high-margin revenue streams, typically through ad-based models, subscriptions, or transaction fees.
These dynamics, however, have struggled to take root in India.
Why Aggregation Hasn’t Fully Worked in India
In India, digital adoption surged with Reliance Jio’s affordable data plans, bringing millions online and expanding the digital audience beyond urban centers. VCs anticipated that this massive user base would drive growth for aggregators in similar ways as it did in the U.S. Platforms like *ShareChat*, *Koo*, and *Chingari* capitalized on this, targeting Tier 2 and Tier 3 cities with culturally relevant content.
However, unlike in Silicon Valley, this rapid aggregation did not translate into strong monetization or profitability due to unique structural and economic barriers:
1. Low ARPU and Limited Monetization: While these platforms aggregated millions of users, they faced monetization challenges. The average revenue per user (ARPU) in India is a fraction of that in the U.S., limiting the ability of platforms to generate meaningful ad revenue. ShareChat, despite amassing 200 million monthly active users, saw ad revenues barely covering its operational costs, which stifles scalability and profitability. Indian users have a lower propensity to pay for digital services, making it difficult to sustain ad-based models at scale.
2. Market Fragmentation and Diverse Consumer Behavior: India’s market is deeply fragmented, with varying preferences, languages, and consumption behaviors across regions. This fragmentation dilutes the network effects that Aggregation Theory relies on, as user behaviors and preferences are too heterogeneous to drive the same scale of engagement that Silicon Valley companies can achieve. Broad consumer aggregation here does not naturally lead to the concentrated purchasing behavior seen in the U.S.
3. Cost Constraints and Profitability Challenges: Platforms like *ShareChat* and *Koo* incurred high operational costs in serving millions of users with limited returns. This stands in contrast to the Silicon Valley model, where high-margin ad revenue could sustain large-scale user acquisition.
In India, the infrastructure and user support costs often match or exceed revenues, limiting the ability to reinvest in growth and leading many companies to plateau rather than reach profitability.
Niche Successes in Indian Aggregation: Trust-Based and High-Engagement Sectors
Despite these challenges, some aggregation models have found success in India by focusing on specific, high-trust, high-engagement niches that lend themselves to monetization even with lower ARPU.
These platforms demonstrate that aggregation can succeed, but only under certain conditions that differ from those in Silicon Valley:
- Astrotalk has aggregated the astrology market, generating revenue through paid interactions with astrologers via chat, phone, or video calls. With this model, it has scaled to over $200 million in GMV, capitalizing on the repeat nature of consultations and the loyalty of high-value users. This model relies on user willingness to pay for one-on-one on demand video, akin to China's Bigo app model, where high-touch interactions generate sustainable revenue streams.
- Pocket FM and Shri Mandir tap into culturally specific interests like regional audio content and religious services. These platforms aggregate users based on highly localized needs, leading to consistent engagement and higher retention. By focusing on value-based, utility-driven models, these platforms have been able to cultivate loyal, paying audiences, even though they do not reach the scale of Silicon Valley’s aggregators.
Indian VC Strategy Shift: Capital Efficiency Over Aggressive Scaling
The challenges in monetizing broad aggregation models have prompted Indian VCs to pivot away from Silicon Valley’s high-risk, high-reward approach. Realizing that the power law dynamics—where a few winners offset the failures of many—have not materialized in India, VCs have turned to a more PE-like model that emphasizes capital efficiency, sustainability, and profitability:
1. Execution Risk Over Speculative Growth: Indian VCs are focusing on reducing mortality rates within their portfolios by backing companies with solid business fundamentals and clearer paths to profitability. This shift addresses India’s narrower Serviceable Obtainable Market (SOM), where even if there is broad potential, the realistically monetizable user base is smaller.
2. Sectors Aligned with Economic Structure: Investment focus has shifted to foundational sectors like consumer brands, healthcare, and omni-channel retail, which align with India’s economic landscape and offer more consistent, tangible returns. Unlike U.S. aggregators that rely on network effects and data aggregation, these businesses depend on operational efficiency and capital discipline.
3. Tech as a Process Enabler, Not a Differentiator: In India’s VC landscape, technology now acts as a process facilitator rather than the main growth driver. For instance, companies in consumer goods and healthcare may use tech to enhance operational efficiency, but the c
ore value lies in sustainable business practices, not in tech-enabled scale. This recalibrates VC expectations, moving from disruptive tech solutions toward resilient, execution-focused models.
Learning from Silicon Valley’s Mistakes: A Sustainable Approach to Aggregation
Indian VCs have also learned from the challenges faced by early investors who tried to replicate Silicon Valley’s models. Funds like ChrysCapital and Westbridge (formerly Sequoia) realized that many high-risk bets on consumer tech did not deliver expected returns, and instead found greater stability in public market investments and traditional sectors. This shift is not simply a reaction to poor performance but a strategic adaptation to India’s market realities.
The VC focus in India is now on companies that can generate consistent cash flows, manage costs, and scale incrementally rather than explosively. This approach mirrors mid-market private equity models more than traditional venture capital, emphasizing execution and revenue stability over speculative growth. It’s a path that recognizes India’s structural constraints while still allowing for growth in areas aligned with the country’s unique needs.
In India, Aggregation Theory must adapt to the country's economic realities. While the theory’s principles remain relevant, they require a nuanced application that recognizes local consumer behavior, economic diversity, and monetization constraints. Indian aggregators that succeed do so by focusing on high-trust, niche markets and optimizing for capital efficiency rather than scale at any cost.
India’s venture ecosystem, therefore, represents an adapted model of Aggregation Theory, where success depends on trust, utility, and sustainability. As VCs shift their focus from aggressive scaling to efficient, profitable growth, India’s digital economy may evolve along a trajectory that blends elements of Silicon Valley’s tech prowess with private equity’s emphasis on fundamentals, signaling a unique path forward for the world’s largest emerging market.
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