How Network Effects and Platform Economics Are Reshaping the Retail Trading Tool Market

A key concept of academic economics at the university level and in the area of digital markets is the principle of network effects. It’s the idea that the more people use a product or service, the more valuable it becomes. Factor in platform economics and network effects help explain the dominance of early digital platforms— and equally, their eventual vulnerability as markets mature.

TradingView is a great example, as it’s a popular charting and analysis platform and is essentially the de facto standard for retail traders. TradingView achieved heavy network effects with its early, intuitive and wide system integrations. The traders would exchange custom indicators, chart layouts, and ideas on the platform. The more users, the more content; the more content, the more users it attracted. Broker integrations and API extensions enabled TradingView to transform itself from a tool to a hub—a textbook example of flywheel effects in platform economics.

But as the retail trading market exploded — accelerated by meme stock mania, crypto adoption, and the global digitization of finance—the dynamics began to change. The overwhelming growth of the market started to chip away at TradingView’s dominance and make space for new, niche-focused platforms to take hold. Now, a growing number of traders use not just TradingView, but apps like TradingView that specialize in a specific asset class, use case, or user need.

The Economics Behind This Shift

The first major force is the expansion of the market. According to Statista, the number of retail traders in the world soared from around 35 million in 2017 to over 135 million by 2023. This rapid growth also facilitated a divergence of user’s tastes, and thus provided enough room for niche platforms to come in. For instance: 

CoinGlass and TensorCharts are directly targeted at crypto traders—with features like liquidation heatmaps or funding rate tracking.

Bookmap offers desktop and mobile users access to advanced depth-of-market and order flow analytics for high-frequency trading (HFT).

TrendSpider is an unusual tool that uses machine learning to automatically apply technical analysis to the chart of your choice–and it’s certainly interesting for algorithmic traders.

Each of these platforms are chipping away at TradingView’s monopoly by delivering markedly different value. The result is a classic example of multi-homing: users interact with all of the platforms at the same time because each of has unique value to add.

Second, network effects change over time. User-generated content on TradingView (such as Pine Script strategies and public chatrooms) was, until recently, a moat. But, as newer platforms bring the same kind of social features (or even better integrations with Discord, Telegram, or mobile apps), the marginal benefit of TradingView’s community decreases. Now, instead of one dominant platform, there is fragmentation.

This is all part of a larger transition in platform economic. At the early stage, platforms benefit from a winner-take-most dynamic such that the biggest platform gets the most developers, users, and integrations. But as markets mature, and users become more sophisticated, the desire for feature depth exceeds desire for one-stop convenience. Nowhere is this truer than in the world of trading, where different asset classes — stocks, options, crypto, foreign exchange—requires different data sets and tools.

Real-World Ramifications

For Users: Traders now have multiple products designed specifically for their strategies to choose from. This leads to better user welfare and an across-the-board quality rise.

For Platforms: Established players such as TradingView need to innovate or risk losing mindshare. It’s not enough to just be the default anymore.

For the Market: Data consistency and cost can be an issue with fragmentation. Traders might have to shell out for a number of subscriptions to remain competitive.

Conclusion

Network effects help explain how TradingView became the top player in retail trading tools—and why that dominance is no longer unassailable. With the booming and fragmenting retail marketplace, more traders are adopting apps like TradingView that cater to specific needs much more accurately. What was once a monopoly over trader attention is now turning into a competitive ecosystem thanks to the same economic principle that built TradingView in the first place: the network effect.