In the last 4 weeks, there were 42.2 million views! Every month, bonuses are given to the company's editors based on views and comprehensive data 💰

Today, let's talk about how we efficiently publish high-quality content and the costs behind it.

Focused on valuable content + data examples + plain language! When we were working on Twitter, we first analyzed some high-quality accounts in the financial category within the market, not limited to Twitter. One such account was '招财大牛猫' on WeChat, which has now been banned. Another is '小小辛巴' on Xueqiu, which has now sold its account. On YouTube, there's the 'Financial Education' channel discussing US stocks, etc. They all share a common feature: focused on valuable content + data examples + plain language! And they can periodically help you make money!

After breaking down these different top accounts on social media, you can take their highest-traffic piece of content or video to create a content framework structure and then imitate it wildly. With the assistance of #AI, you can download their content, feed it to AI, and collaborate to complete it. However, one thing that needs to be accumulated is: data acquisition websites! Many times, we express a piece of content, but having data 📊 versus not having data creates a vastly different sense of authenticity and credibility for users. Common data sources we use include: Wind, IFind database, The Wall Street Journal, Bloomberg, etc. There are likely even more Web3 data websites, such as #Messari, #Nansen, #Defillama, #Dune, etc. We will share more over time!

Next, digging into daily and weekly hot topics is crucial, as finance is time-sensitive, and trending topics will definitely attract traffic. Our company has developed a public opinion monitoring system that effectively retrieves daily and weekly topics discussed on Twitter, Reddit, and other social platforms. Even if you don't have public opinion monitoring, there's a very useful website, the #lunarcrush platform, which can summarize the traffic of trending topics daily. R always tells us the trick: keep an eye on the trends!

Finally, it's important to consistently output content daily and then use data to summarize which types of copy and styles are more popular. Deliberate practice, tracking data, and continuous correction are essential!

Regarding KOL cost issues:

To create relatively high-quality content in the long term, the costs are not low. For example, #Messari, #Nansen, and #Wind all require payment, and the costs are significant. However, due to corporate operations, the marginal cost decreases. R's blue ocean capital focuses on #Web3 research and fund allocation, not limited to the crypto market, and adopts an organizational structure similar to that of a brokerage. Each niche track is assigned 1-2 researchers, such as #AI, #RWA, #public chain, #on-chain data, #macro data, etc. They share the latest insights and discoveries with the editor group immediately. We filter themes based on public opinion heat and write articles, so every day, we basically have no shortage of themes, leading to stable long-term output, regardless of market conditions!

So, to be a good KOL, don't just look at the surface glamour; the effort and costs behind it are also significant. We will gradually share some good strategies and methods, explaining how to be a good KOL from a methodological perspective. Recently, we are working on a matrix MCN account and welcome self-media players with ideas to join us! Grateful 🙏

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