韩国 KBW 会后指南:从交易所到 KOL,一文掌握关键玩家

深潮Опубліковано о 2024-09-10Востаннє оновлено о 2024-09-10

不要仅仅因为韩国交易量高就加以利用。

作者:Ash

编译:深潮TechFlow

韩国的加密货币交易所处理了高达 20 亿美元的交易量,这为项目带来了独特的机遇。

在今年的 @kbwofficial 大会上,我有幸与当地的利益相关者进行了交流,并总结出了一些关键见解,帮助你更好地制定策略。 内容包括:

  • 韩国生态系统概况

  • 营销活动策划

  • 理解韩国普通用户市场

  • 其他注意事项

请保存这份指南!

韩国生态系统概览

这一部分介绍了韩国的本地生态系统,包括中心化交易所 (CEX)、媒体、研究和咨询、投资、项目以及关键意见领袖 (KOL)。根据多方信息,大约 10-15%(约 600-900 万)的韩国人使用中心化交易所进行交易。

a) 中心化交易所

韩国有三大主要的中心化交易所:Upbit、BitThumb 和 Coinone,其中 Upbit 和 BitThumb 占据了 95% 的市场份额。

有趣的是,这些交易所都与各自的银行相连接,以实现法币的出入金:

  • UpBit 连接 KBank

  • BitThumb 连接 Nonghyup Bank

  • Coinone 连接 KakaoBank

在这些中心化交易所中,韩元 (KRW) 的交易对拥有最高的交易量,因此大多数项目应该努力争取让他们的 Token 以此为交易对进行上市。

我注意到本地中心化交易所之所以交易量巨大,是因为:

  • 当地的赌博文化*和韩国消费者的强大购买力

  • 韩国人不偏好自我托管,因此更倾向于在中心化交易所进行交易

  • 韩国人将加密货币视为一种投机性资产类别(类似于股票),其炒作效应往往比基本面更受关注(例如,与知名企业或人物的关联,如 Ondo 和 Blackrock,Doge 和 Elon Musk)

  • 通过与一些人的交流,我了解到这是韩国社会的一个阴暗面,因为当前的经济状况(如房地产市场高涨、低工资、疲软的股市以及经济垄断)迫使人们通过过度赌博来试图摆脱贫困。

b) 媒体

由于语言障碍,韩国用户通常依赖本地出版机构来获取最新的新闻和动态。除了 @official_naver 的博客,主要的媒体平台还包括 @eBlockmedia@CoinnessGL@bloomingbit_io@FACTBLOCK@tokenpostkr。 对于非韩国项目来说,直接与这些媒体公司沟通可能会有一定难度,这时下一个利益相关者可能会提供帮助。

c) 研究和咨询

韩国拥有一个活跃的研究和咨询公司生态系统,许多公司在项目与用户之间,以及国际项目与韩国受众之间起到中介作用。

要在韩国市场取得成功,与一家信誉良好的公司合作是至关重要的。我将这些公司分为两个主要类别:

i. 顾问

@Xangle_official

@DeSpreadTeam

@0xundefined_

@INF_CryptoLab

@Edward__Park

@EncodingLabs

@Whitewater_Labs

@071_labs ii. 研究

@FourPillarsFP

@Tiger_Research_

明确目标可以帮助创始人更轻松地选择合适的合作公司,例如:

d)投资

韩国的资本市场规模不大,只有少数几个主要参与者,可以分为两类:

i. 风投基金

@hashed_official

@nonceclassic

@LECCAVentures

@blocore_vc

@ROKCapital

@SamsungNext ii. 做市商 (MMs)

@presto_labs

@alphanonce

@hyperithm

*请注意,由于法规限制,做市商无法在韩国的中心化交易所 (CEXes) 开设公司账户

e) 项目

*我肯定还有很多遗漏的地方,请多包涵。

f) KOLs

@Edward__Park

@kimyg002

@0xProfessorJo

@delucinator

策划营销活动

许多项目希望进入韩国市场,因为他们看中了韩国普通投资者的高交易量和强大购买力。

然而,这种狭隘的思维方式对韩国的参与者是一种不尊重,因为他们并不是可以被轻易操控以提供退出流动性的人群。韩国的投机者非常谨慎,并且在 Terra Luna/Anchor 事件后变得更加理性和成熟。

韩国人非常重视营销活动中的透明度和真实意图。

那些拥有魅力但又谦逊的创始人,能够激发信任,类似于韩国文化中宗教或团体的影响力,往往能吸引大批追随者。

在进入韩国市场之前,应该制定一个全面的营销计划,包括:

  • 明确的关键绩效指标 (KPI)

  • 用户可以执行的具体行动项目

  • 清晰的未来路线图(涵盖 TGE 前后的计划)

一个简单的营销活动可以这样展开:首先,设定营销目标,并为用户提供明确的行动指引 → 与媒体公司和咨询公司合作进行 SEO 优化,并提供韩文翻译的研究报告 → 策划一个 KOL 活动来扩大影响力。

在这个竞争激烈的市场中,传统的营销策略已不再足够。韩国投资者对无休止的问答活动和 Token/节点销售感到厌烦。要脱颖而出,需要有创造性的思维,并提供真正的价值,比如吸引人的激励措施或财务收益机会。

了解韩国普通用户市场

众所周知,韩国人是潮流的引领者,并且热衷于追逐最新的热点,这可以从他们活跃的时尚界、对奢侈品牌的狂热以及对 K-Pop 的不懈追求中看出。因此,各项目必须不断更新其营销材料,并提供创新且吸引人的故事情节,以保持普通用户的关注。

在韩国,用户可以分为三类:

  • 空投爱好者:需要有具体的操作步骤

  • 机会主义的交易者:追随市场叙事和热点

  • 技术基础设施用户:这类用户较少,因为韩国人更倾向于信任第三方解决方案

采用一刀切的方法注定不会成功,因此根据目标受众量身定制营销活动至关重要。通过透明和开放的沟通建立信任,同时使用韩语,是在韩国市场取得成功的关键。

其他信息

a) 韩国的主要消费应用

  • Naver

  • Coupang(电子商务)

  • Kakao(包括 KakaoTalk 和 Kakao Taxi)

  • Samsung Pay(Apple Pay 在韩国无法使用,原因显而易见)

b) 韩国的开发者主要毕业于 SKY 或 KAIST

SKY 是对韩国三所顶尖大学的非正式统称和缩写:

  • 首尔大学

  • 高丽大学

  • 延世大学

而 KAIST(韩国科学技术院)是一所国家级研究型大学。

c) 我了解到的其他有趣信息

  • Aptos 和 Sui 在韩国非常受欢迎。

  • 许多生态系统已经开始招聘韩国负责人,包括 Monad 和 Chromia 等公司。

  • 没有遇到任何来自 Upbit 或 BitThumb 的人,这些交易所的上市极其困难且随机。

  • 电子烟店遍地都是。

  • 下次去韩国旅行时:用 Naver Map 和 KakaoMap 导航;用 Uber 和 Kakao Taxi 出行;用 Catch Table 找餐厅;用 Coupang eats 叫外卖;用 Papago 翻译。

总结

了解本地生态系统和市场环境 → 与本地咨询公司合作 → 制定本地化的营销策略 → 了解韩国的普通用户市场 → 不要仅仅因为韩国交易量高就加以利用。

Пов'язані матеріали

Google CEO Admits Lagging Behind in Coding

Google CEO Sundar Pichai acknowledged in a recent interview that Google's Gemini AI models are currently "lagging behind" in coding capabilities, particularly for complex, long-horizon tasks requiring advanced developer expertise. He noted the field is advancing at an "unprecedented" pace, where 30-60 days now brings changes equivalent to five years in the past. Pichai expressed that achieving Artificial General Intelligence (AGI) now seems closer than previously imagined due to rapid progress. While highlighting strengths in text, multimodal, and reasoning tasks, Pichai admitted competitors like Anthropic and OpenAI have focused more intently on coding. He emphasized Google's commitment to catching up, citing internal tools like Antigravity 2.0 and the newly released Gemini 3.5 Flash, which aims to address previous shortcomings. Regarding Google Search's AI-driven overhaul, Pichai stated changes will be gradual to align with user needs, not disrupt the core search experience or its advertising model. He addressed public AI anxiety as understandable, given the technology's potential to reshape jobs and society, but remained optimistic about AI augmenting human capabilities and creating new opportunities. Pichai stressed the need for broad societal dialogue and responsible development as AI approaches more advanced, potentially recursive self-improvement stages. He affirmed Google's long-term commitment to leading in AI while navigating its profound implications responsibly.

marsbit1 год тому

Google CEO Admits Lagging Behind in Coding

marsbit1 год тому

The Paradox of Automation: The Stronger the AI, the Busier Humans Become

The Paradox of Automation: The more powerful AI becomes, the more work humans have to do. This article, based on observations from AI-heavy company Every, argues that while AI agents automate tasks like coding, writing, and customer service, they don't eliminate human jobs. Instead, they transform work and create *more* demand for human expertise. AI commoditizes "yesterday's human capabilities" by cheaply generating code, text, and images from past data. This leads to an abundance of similar, generic outputs. Consequently, what becomes scarce and valuable is human judgment in the present moment: knowing *what* is worth doing, *why*, and *how* to do it well. The article identifies two collaboration models: "Agent employees" for delegated tasks and "human-AI collaboration" within tools like Claude Code for complex work. In both cases, humans are essential to set direction, judge quality, and maintain systems. As AI makes execution cheap, human roles shift from executors to designers, reviewers, and meaning-makers. The author addresses "benchmark anxiety" by explaining that AI excels within specific, human-defined problem "frames." As AI masters one frame (e.g., code rewriting), new, more complex frames emerge (e.g., deciding *when* to rewrite). This creates an ongoing cycle where AI chases the frames, but humans remain the "framers." Even with advanced AGI, this dynamic may persist as long as AI lacks true human-like agency and self-directed purpose. The core paradox holds: automation amplifies the need for the very human judgment it seems to replace.

marsbit2 год тому

The Paradox of Automation: The Stronger the AI, the Busier Humans Become

marsbit2 год тому

a16z: 7 Charts to Understand How Tokenization is Changing the Nature of Assets

"a16z: 7 Charts on How Tokenization is Changing the Nature of Assets" Tokenized Assets (or Real-World Assets - RWA) are transforming asset forms, liquidity, and financial system construction. The market recently surpassed $30 billion, stabilizing around $34 billion (excluding stablecoins), representing a tenfold increase in less than two years, driven by clearer regulations, mature institutional infrastructure, and increased financial institution adoption. The primary driver of recent growth is tokenized U.S. Treasury bonds. These offer investors efficient, flexible digital access to yield-bearing assets and improve institutional operations like settlement and collateral management. Other asset classes show varied growth: asset-backed credit leads, followed by niche financial assets (e.g., reinsurance, mining notes), while venture capital took longer to scale. Market segmentation shows high concentration. In commodities, tokenized gold dominates (~$5 billion), as its standardized, storable nature fits tokenization well. Bonds are the largest category ($15.2B), but only ~5% are used in DeFi protocols. Conversely, smaller niches like reinsurance tokens see high (~84%) on-chain utilization, highlighting a core industry divide: most current tokenized assets are merely digitized records for easier holding/transfer, lacking the "composability" (free combination/interaction) that is key to blockchain-native finance. The ecosystem is distributed across multiple blockchains, with Ethereum hosting over half the value ($15.7B), followed by BNB Chain, Solana, and others. Future market size predictions vary widely (e.g., $2-$30 trillion by 2030+), but all indicate massive potential from the current small base. Tokenized assets currently represent minuscule fractions of their global counterparts (e.g., 0.01% of global bonds). The current phase focuses on digitizing straightforward assets. The next challenge is to bring more complex financial components on-chain and deeply integrate tokenized assets into composable, internet-native financial infrastructure.

链捕手3 год тому

a16z: 7 Charts to Understand How Tokenization is Changing the Nature of Assets

链捕手3 год тому

a16z: How Tokenization is Transforming the Nature of Assets in 7 Charts

"Tokenized Assets: How Tokenization Changes the Nature of Assets" by a16z Crypto The market for tokenized assets, excluding stablecoins, has grown from under $3 billion two years ago to over $340 billion today. US Treasury bonds are the primary growth driver, allowing investors to hold yield-bearing assets digitally and enabling more efficient settlement. Other key sectors include private credit (growing fastest), commodities (dominated by gold), and niche financial assets. However, the market remains concentrated in tokenized US Treasuries and gold. A critical insight is that most tokenized assets currently lack "composability." While the total market is large, only a small fraction is actively used within DeFi protocols. For instance, only about 5% of tokenized bonds and a low percentage of tokenized gold are utilized on-chain. In contrast, assets like reinsurance and private credit tokens show much higher on-chain usage rates (84% and 33%, respectively). This highlights a divide: many tokenized assets are merely digital records on a blockchain without enabling new, programmable financial applications. The Pantera Capital Token Native Index indicates over 70% of tokenized assets have minimal on-chain native functionality. Ethereum remains the dominant blockchain for tokenized assets (over $150B), but the ecosystem is diversifying across chains like BNB Chain, Solana, and Stellar, based on factors like cost and compliance. Major institutions forecast massive future growth, with predictions for the tokenized asset market ranging from $2 trillion to over $30 trillion by the early 2030s. However, compared to the global financial system (e.g., ~$140T bonds, multi-trillion dollar gold market), tokenized assets currently represent a tiny fraction (0.01% or less). The conclusion is that while tokenization has begun by digitizing and streamlining settlement for simpler assets, the next phase involves bringing more complex financial instruments on-chain and deeply integrating them into composable, internet-native financial infrastructure.

Odaily星球日报3 год тому

a16z: How Tokenization is Transforming the Nature of Assets in 7 Charts

Odaily星球日报3 год тому

The Revived Codex, Carrying OpenAI's Hopes for IPO

This article analyzes the intense recent development of OpenAI's Codex, positioning it as a crucial component for OpenAI's impending IPO. Over the past two months, Codex has seen a rapid series of major updates focused on integrating into real enterprise workflows. Key new features include enhanced context capture (Appshots, file previews, built-in browser), long-running task execution ("Goal Mode"), remote operation (phone control, lock-screen access), and enterprise management tools (plugin sharing, access tokens, automated risk review). These updates aim to make Codex a comprehensive AI workbench that can "see the scene, push tasks, and manage risks." The author argues that while ChatGPT proves OpenAI's massive user base and API provides foundational revenue, Codex represents OpenAI's clearest path to demonstrating tangible, high-value commercial viability. It targets developers and engineering teams—a segment already accustomed to paying for efficiency gains in costly software development cycles. This is critical because, despite higher overall revenue, OpenAI's adjusted operating margins remain deeply negative, highlighting the challenge of outrunning immense compute costs. The pressure is amplified by competitor Anthropic's success with Claude Code, which has shown that a focused approach on high-value enterprise and developer workflows can lead to a path toward profitability. Codex's aggressive evolution is thus seen as OpenAI's strategic move to capture a similar enterprise-ready, revenue-generating narrative essential for its market debut. In essence, "ChatGPT proved OpenAI has users. Codex needs to prove OpenAI is a business that can make money."

marsbit4 год тому

The Revived Codex, Carrying OpenAI's Hopes for IPO

marsbit4 год тому

Торгівля

Спот
Ф'ючерси
活动图片