X上有个作者andrew chen分享了一段有价值的内容，下面是英文配中文的翻译。最后面的部分是总结。BRAINDUMP ON VIRAL LOOPS #3
关于病毒式循环的思维导图 #3
ok -- so here's the case against all the fun/dumb viral techniques you're seeing on social media right now. When people talk about "going viral" these days the state of the art -- if you can call it that -- is a hodgepodge of shitpoasting and social media videos. This includes:
好的——所以这里是对你现在在社交媒体上看到的所有有趣/愚蠢的病毒技术的反对意见。当人们谈论“病毒传播”时，如今的技术水平——如果你能称之为技术的话——是一堆垃圾帖和社交媒体视频。这包括：
- ragebaiting and shitpoasting by startups - beautifully shot cinematic launch trailers - tiktok video clipping - billboards for social media coverage - influencers astroturfing your app - founders turning themselves into influencers - etc etc
- 初创公司通过激怒诱饵和垃圾帖 - 精美拍摄的电影风格发布预告片 - TikTok 视频剪辑 - 社交媒体报道的广告牌 - 网红为你的应用程序造势 - 创始人将自己变成网红 - 等等等等
These are fun, but I predict they will not stand the test of the time -- not the way that classic viral techniques like referral programs, sharing links, invites, and so on have proven themselves over multiple eras.
这些很有趣，但我预测它们不会经受住时间的考验——不像推荐计划、分享链接、邀请等经典的病毒式传播技术在多个时代中证明了自己。
One quantitative way to talk about this is -- do these techniques scale signups as a function of active users?
一种量化讨论这个问题的方法是——这些技术是否能随着活跃用户的增加而扩大注册量？
That is, if you tracked this as a ratio: new users / daily active users
也就是说，如果你将其作为一个比率来跟踪： 新用户/每日活跃用户
... would you be able to scale new users as you scaled daily active users? If not, naturally, new users will stay constant and even with strong retention, your DAUs will grow linearly but not exponentially.
……当你扩大每日活跃用户时，你能否同时扩大新用户？如果不能，自然地，新用户将保持不变，即使有很强的留存率，你的每日活跃用户也会线性增长而不是指数增长。
One core reason is that these techniques generate one-time traffic. Good for creating a single spike of new users in your app. However as you grow and need a repeatable source of user acquisition, you simply can't repeat these over and over again. If you drop in an amazing cinematic launch once a year, people may pay attention but if you start doing it monthly and then weekly, there's just diminishing returns. Similarly there's no defensibility in shitposting. If you shitpost and other founders shitpost, eventually you just won't stand out as much anymore. As your customers acclimate and become less responsive to the novelty, these techniques will fade over time.
一个核心原因是这些技术产生了一次性流量。对于在你的应用中创造一次性的新用户高峰是有好处的。然而，随着你的增长并需要一个可重复的用户获取来源，你根本无法一遍又一遍地重复这些。如果你每年推出一次惊人的电影级发布，人们可能会关注，但如果你开始每月甚至每周这样做，回报就会递减。同样，shitposting 也没有防御性。如果你发 shitpost，其他创始人也发，最终你就不会再那么突出。当你的客户适应并对新奇事物反应不再那么敏感时，这些技术将随着时间的推移而消退。
But! But! I admit they are still useful
但是！但是！我承认它们仍然有用
Here's why. (But allow me to diverge to a short history lesson here from the Web 2.0 days)
原因如下。（但请允许我在这里插入一个关于 Web 2.0 时代的简短历史课）
The end of Web 2.0's viralityIn my previous brain dumps on the Viral Loop topic, I talked about how during the Web 2.0 days (~2005-2010) there was insane innovation in email invite loops, content sharing, virality, Facebook apps that went from zero to millions of users overnight, etc. Then it ended.
Web 2.0 时代病毒传播的终结 在我之前关于病毒循环主题的思维倾泻中，我谈到了在 Web 2.0 时代（大约 2005-2010 年），电子邮件邀请循环、内容分享、病毒传播、Facebook 应用程序等方面的疯狂创新，这些应用程序一夜之间从零增长到数百万用户。然后这一切结束了。
What killed it? Mobile did.
是什么终结了它？是移动设备。
The "golden age" of viral loops was possible because for the first time during the Web 2.0 era, there was so much novelty in getting an email or notification from a friend who is inviting you to something or sharing a piece of content to you via an app, etc. This made response rates very high, viral factors were able to go >1, and you saw a ton of products grow overnight -- including Facebook, Linkedin, YouTube, Spotify, Pinterest, and many other products that got their start with clever viral loops.
病毒循环的“黄金时代”之所以成为可能，是因为在 Web 2.0 时代，第一次出现了从朋友那里收到邀请或通过应用程序分享内容的电子邮件或通知的新奇体验。这使得响应率非常高，病毒因子能够超过 1，你会看到大量产品一夜之间迅速增长——包括 Facebook、LinkedIn、YouTube、Spotify、Pinterest 以及许多其他通过巧妙的病毒循环起步的产品。
In the golden era this is where you saw hyper-simple hyper-viral products succeed. In the earlier part of the era, you had apps like BirthdayAlarm in 2001 (h/t Michael Birch, later the creator of Bebo) which would email you about a friend wanting to keep track of your birthday (how kind!), driving you to sign up, and then flipping that over to asking if you wanted to keep track of your friends' birthdays. Put in a bunch of emails or eventually import your email address book and you can now ask hundreds of friends. Repeat that over and over and you have an app that might be used by millions of people.
在黄金时代，你会看到极其简单且极具病毒性的产品取得成功。在这个时代的早期，你会看到像 2001 年的 BirthdayAlarm 这样的应用程序（致敬 Michael Birch，后来是 Bebo 的创始人），它会通过电子邮件通知你有朋友想要记录你的生日（多么贴心！），促使你注册，然后询问你是否想要记录朋友的生日。输入一堆电子邮件或最终导入你的电子邮件地址簿，你现在可以邀请数百位朋友。反复进行这一过程，你就会拥有一个可能被数百万人使用的应用程序。
Another example -- there were loops like Plaxo in 2002 (h/t Sean Parker, later the president of Facebook among many other adventures) that started with a friend asking if you wanted to maintain an up-to-date contact about yourself. Update the contact and then it asks you to add your friends and maybe a bunch of your other friends' contacts kicking off the loop again. Many of these were hyper simple but when they were paired with social profiles and eventually a feed, these were the underlying mechanics that eventually birthed the category of social networking apps. Importantly the Social Network category had real utility and retention and wasn't just a viral app on its own. We'll talk more about these dynamics in a second.
另一个例子是 2002 年的 Plaxo 循环（致敬 Sean Parker，后来成为 Facebook 的总裁，参与了许多其他冒险），它开始于一个朋友问你是否想保持关于自己的最新联系信息。更新联系信息后，它会要求你添加朋友，可能还会添加你其他朋友的联系人，从而再次启动循环。许多这样的循环非常简单，但当它们与社交档案和最终的动态消息结合在一起时，这些就是最终催生社交网络应用类别的基本机制。重要的是，社交网络类别具有真正的实用性和用户留存率，而不仅仅是一个病毒式传播的应用。我们稍后会详细讨论这些动态。
But the golden era of Web 2.0 virality eventually ended. Consumers got used to these techniques, response rates went down, spam filters kicked in, and importantly the whole world moved to mobile. When email virality was dominant, you had the ability to ask users to import their email contacts and often you'd get 200+ emails that could then be invited to the service. Before the Law of Shitty Clickthrough kicked in, you might get something like the following: - 50% of people would connect their contacts - 50% of people would invite friends - 200+ invite emails would be sent - 10% would open/click through - 50% of people would sign up - ... then repeat
但 Web 2.0 病毒传播的黄金时代最终结束了。消费者习惯了这些技术，响应率下降，垃圾邮件过滤器开始发挥作用，更重要的是，整个世界转向了移动端。当电子邮件病毒传播占主导地位时，你可以要求用户导入他们的电子邮件联系人，通常你会得到 200 多个可以邀请到服务中的电子邮件。在糟糕点击率法则生效之前，你可能会得到如下结果： - 50% 的人会连接他们的联系人 - 50% 的人会邀请朋友 - 会发送 200 多封邀请邮件 - 10% 的人会打开/点击进入 - 50% 的人会注册 - ... 然后重复
This would often generate viral factors of >2 or more (just multiple all the numbers above).
这通常会产生大于 2 或更多的病毒因子（只需将上述所有数字相乘）。
But mobile was a whole other thing. Apple made mobile contacts widely available, but you have to invite numbers one by one. Who's going to do that? Response rates were high, but the # of invites was small. Some folks tried to build around this, using services like Twilio to deliver invites from the server. But that led to SMS spam, and the CAN-SPAM Act and resulting millions of dollars of fines convinced people to avoid all this. Between the platform change from email virality to SMS virality, and the declining novelty of invites, the response rates (and viral factors cratered)
但移动端是完全不同的事情。苹果让移动联系人广泛可用，但你必须一个一个地邀请号码。谁会这样做呢？响应率很高，但邀请的数量很少。有些人试图围绕这一点进行构建，使用像 Twilio 这样的服务从服务器发送邀请。但这导致了短信垃圾邮件，而《CAN-SPAM 法案》和由此产生的数百万美元罚款让人们避免了这一切。在从电子邮件病毒传播到短信病毒传播的平台变化之间，以及邀请的新鲜感下降，响应率（和病毒因子）大幅下降。
The era of hypersimple hyperviral apps ended here
超简单超病毒式应用的时代在此结束
And to this day, it's basically impossible to create loops where the viral factor is >1 in the first session
直到今天，基本上不可能在第一次使用时就创建病毒因子大于 1 的循环
Retention is king for viralityThe modern app isn't obnoxiously hyperviral -- prompting to invite and invite, as prior generations of products did. Instead it's driven on a few components: 1) multiple top of funnel channels 2) great retention that drives virality
留存率是病毒传播的关键 现代应用程序并不是像以前的产品那样令人厌烦地过度病毒式传播——不断提示邀请和邀请。相反，它依赖于几个组件： 1) 多个漏斗顶端渠道 2) 优秀的留存率推动病毒式传播
Here's what I mean:
我的意思是：
First you need multiple acquisition channels that are diversified and can be as spiky as you want. This is where social media, video launches, press mentions, SEO, and even paid marketing techniques can all feed into your signups. It's fine if this doesn't scale or grow as long as you get some kind of consistent top-of-funnel dripping users into your product at all times.
首先，你需要多个多样化的获取渠道，可以根据需要进行调整。这是社交媒体、视频发布、媒体报道、SEO，甚至付费营销技术都可以为你的注册用户提供支持的地方。即使这些渠道不能扩展或增长，只要你能始终如一地将用户引入产品的漏斗顶端，这样的结果也是可以接受的。
For a product like the Uber app -- when I was there -- it was something like 50% of first trips might be from paid marketing. Then 10-20% from referral programs, and the remainder from word of mouth, SEO, and so on. We'd buy activated mobile users, with broad base and untargeted advertising, for $10-20 and the math all worked. For other products, you might have a different acquisition mix depending on how aggressively you pushed paid versus SEO and so on. A high-intent product category like travel might have a lot more from SEO and referrals, since you need to be near transactions. Either way, you just need some set of top of funnel sources that work.
对于像 Uber 应用这样的产品——当我在那里时——大约 50%的首次行程可能来自付费营销。然后 10-20%来自推荐计划，其余的来自口碑、SEO 等。我们会以 10-20 美元的价格购买激活的移动用户，采用广泛且无针对性的广告，所有的数学计算都能成立。对于其他产品，您可能会有不同的获取组合，具体取决于您推动付费与 SEO 等的力度。像旅游这样高意图的产品类别可能会有更多来自 SEO 和推荐，因为您需要接近交易。无论哪种方式，您只需要一些有效的漏斗顶端来源。
Second you need the product to generate a bunch of user sessions, so that you can grow virality over time -- that's another way to say, you need strong retention. Oftentimes the viral factor is described simplistically, as:
其次，您需要产品生成大量用户会话，以便随着时间的推移增加病毒性——换句话说，您需要强大的留存率。通常情况下，病毒因子被简单地描述为：
invites x conversion rate
邀请 x 转化率
... but that implies that all the virality is generated in one session. In a highly retentive product instead you get a whole bunch of sessions and you might be able to ask users to share, or invite, or refer every single time. So instead you can think of it as the following:
……但这意味着所有的病毒性都是在一个会话中生成的。在一个高留存的产品中，您会获得大量的会话，您可能能够每次都要求用户分享、邀请或推荐。因此，您可以将其视为以下内容：
the sum of: session 1's viral factor + session 2's viral factor + ...
总和为： 会话 1 的病毒因子 + 会话 2 的病毒因子 + ...
And I'll leave it up to an exercise to the reader but you can think of this as the infinite sum of each of the points on the retention curve of which each session can generate a little bit of viral factor. Each session's viral factor is then based on the % of users that interact with the viral features, multiplied by the resulting shares or invites, conversion rate, etc.
我将其留给读者作为一个练习，但你可以将其视为保留曲线上每个点的无限和，其中每个会话都可以产生一点病毒因子。每个会话的病毒因子基于与病毒功能交互的用户百分比，乘以由此产生的分享或邀请、转化率等。
I like to use a rule of thumb where about half the viral factor is generated in the first session and then the rest is generated in all of the sessions after. The reason for this is that in the first session the user is in the mindset of "setting up" their account. This is where you can ask them to set up their workspace and invite their colleagues or to invite their friends, etc. They're often coming in with a high degree of intent and those set up steps can generate a ton of reality. In the second or third sessions, the problem is not only has have many of the users dropped off but also they are sort of in a different mindset where they're expecting value from the product at that point. So while you can take them into viral flows, you don't have the excuse that it's for setting up.
我喜欢使用一个经验法则，即大约一半的病毒因子是在第一次会话中产生的，然后其余的在之后的所有会话中产生。原因是，在第一次会话中，用户处于“设置”他们账户的心态。这时你可以要求他们设置工作区并邀请同事，或者邀请他们的朋友等。他们通常带着很高的意图进入，这些设置步骤可以产生大量的现实。在第二或第三次会话中，问题不仅在于许多用户已经流失，而且他们的心态也有所不同，此时他们期望从产品中获得价值。因此，虽然你可以将他们引入病毒流程，但你没有借口说这是为了设置。
The other thing that you're seeing is that in reality apps will have multiple loops that are all generating different types of viral factor. A product like Dropbox might have several, such as: - sharing a folder with a coworker - inviting people to share - referrals program - using other Dropbox apps that have their own viral loops
实际上，你会看到应用程序通常会有多个循环，每个循环都会产生不同类型的病毒因子。像 Dropbox 这样的产品可能会有几个，例如： - 与同事共享文件夹 - 邀请他人共享 - 推荐计划 - 使用其他拥有自身病毒循环的 Dropbox 应用程序
Each one might work at varying levels of performance but the important thing is that you might be able to convince a user to engage in all three at varying levels across multiple sessions
每种方法可能在不同程度上有效，但重要的是，你可能能够说服用户在多个会话中以不同程度参与所有三种方法。
This was the case at Uber, which I saw first-hand. People were introduced to Uber in many ways. You had loops like the referral program or you could earn dollars by inviting friends and they would receive dollars too. But you also recruited users naturally simply because you would often invite friends IRL to come take a ride in your Uber. Or engage in functionality like "Share ETA" that would expose friends to Uber, driving them to eventually download it.
在 Uber 就是这种情况，我亲眼见证了这一点。人们通过多种方式了解 Uber。你可以通过推荐计划这样的循环，或者通过邀请朋友赚取美元，他们也会收到美元。但你也可以自然地招募用户，因为你经常会邀请朋友在现实生活中乘坐你的 Uber。或者使用像“分享预计到达时间”这样的功能，这会让朋友接触到 Uber，最终促使他们下载。
A product might have three or four major loops that all work in concert and are ideally all completely useful based on the context of the usage. That way you're not asking people to invite over and over again but instead there's a loop for inviting on your first session, then maybe a referral program that you introduce to them in session number two, then you might have some embedded functionality where they share some content or otherwise with friends in a later session and so on.
一个产品可能有三到四个主要循环，它们协同工作，并且理想情况下在使用的上下文中都完全有用。这样你就不需要一遍又一遍地邀请人们，而是在第一次会话中有一个邀请的循环，然后在第二次会话中可能向他们介绍一个推荐计划，然后你可能在后续会话中有一些嵌入的功能，让他们与朋友分享一些内容或其他东西，等等。
To nerd out a bit: The viral factor is not generated by how many invites you send in one session. The viral factor is generated by the sum of all the viral features that you engage with over all of your sessions. The more loops you have, the more useful across more sessions because of great retention, the more viral your product is over time. And the more novel and exciting your product is to users (as AI products are now), the easier it is for the entire system to work together.
稍微深入一点：病毒因子不是由你在一次会话中发送多少邀请生成的。病毒因子是由你在所有会话中参与的所有病毒特性的总和生成的。你拥有的循环越多，由于出色的留存率，在更多会话中越有用，随着时间的推移，你的产品就越具病毒性。而且你的产品对用户越新颖和令人兴奋（如现在的 AI 产品），整个系统就越容易协同工作。
Low retention apps need to be spammy. Sticky apps do not.Naturally if your product is highly retentive then you get many sessions to be able to ask the user to share or invite. You can have a small and unobtrusive viral sharing feature. As long as you get a large number of sessions, you'll eventually have a viral loop that's >1. On the other hand if you have a low retention product where you only get two or three sessions on average, then you'll need to be very prominent and spammy to push the user towards viral features. This is why sticky, high retention apps can be more viral over time.
低留存率的应用需要具有垃圾信息性质。粘性应用则不需要。 自然地，如果你的产品具有很高的留存率，那么你会有很多会话可以请求用户分享或邀请。你可以有一个小而不显眼的病毒分享功能。只要你获得大量的会话，你最终会有一个大于 1 的病毒循环。另一方面，如果你的产品留存率低，平均只有两到三个会话，那么你需要非常显眼和具有垃圾信息性质，以推动用户使用病毒特性。这就是为什么粘性、高留存率的应用可以随着时间的推移变得更具病毒性。
I remember in Facebook's early days it was amazing how less spammy they were compared to other social networking tools. While they had email invite capabilities, they existed just on the right railing of the website. Small and unobtrusive. If you didn't have any friends, it would be quite prominent but for most users it really was not a big thing to push people to invite as many friends as possible. I think this is because the product was very sticky and well made from day one and so the viral factor was gained over a really long period of time rather than some of the spammier social network competitors that had to use invites to grow but ultimately a lower retention rate and user frustration given the spamminess caused Facebook to eventually win.
我记得在 Facebook 的早期，他们比其他社交网络工具的垃圾信息要少得多，这一点令人惊讶。虽然他们有电子邮件邀请功能，但它们仅存在于网站的右侧栏。小而不显眼。如果你没有任何朋友，它会相当显眼，但对大多数用户来说，推动人们尽可能多地邀请朋友并不是一件大事。我认为这是因为产品从一开始就非常吸引人且制作精良，因此病毒因素是在很长一段时间内获得的，而不是像一些垃圾信息较多的社交网络竞争对手那样必须使用邀请来增长，但最终由于垃圾信息导致的较低留存率和用户挫败感使得 Facebook 最终胜出。
Is viral factor useful when it's <1?The funny thing about viral factors is that although people often love the idea of exceeding 1.0, as far as I can tell those unique windows only last in very short periods of time when there's a new platform or some new novel mechanic that ultimately allows hyper simple viral apps to succeed. Most of the time, you see viral factors that are 0.2 or 0.3 or below.
当病毒因素小于 1 时，它有用吗？ 关于病毒因素有趣的是，尽管人们通常喜欢超过 1.0 的想法，但据我所知，这些独特的窗口期只在非常短的时间内存在，当时有一个新平台或一些新的新颖机制最终允许超简单的病毒应用程序成功。大多数时候，你会看到病毒因素是 0.2 或 0.3 或更低。
This is still valuable! A viral factor of 0.2 means that when you have 1000 users sign up, you get 200 users "for free" and that discounts CAC in a meaningful way. In this way viral loops have ended up playing more of a support role because they help stretch the dollars that you're putting into marketing. A highly-retentive product will over time grow signups in proportion to the active user base even if it's not doing it in a super quick way.
这仍然很有价值！一个 0.2 的病毒因子意味着当你有 1000 名用户注册时，你会“免费”获得 200 名用户，这在一定程度上降低了客户获取成本。因此，病毒循环最终更多地扮演了支持角色，因为它们有助于延长你在营销上投入的资金。一个高留存率的产品即使没有以非常快速的方式增长，随着时间的推移也会按活跃用户基数的比例增加注册量。
The "speed" of a viral loop is an important concept here. Virality may not manifest itself quickly, particularly when it's a high-retention/low-spamminess product. When viral factor is generated slowly over many sessions, you can understand why viral loops have a speed of how fast they generate invites. If you have a product that users engage with every day like a social network app, then they may send off a bunch of invites every day. This leads to an accumulating viral factor that is going to generate more sign-ups quickly. Contrast that to the referral program of a product like Dropbox, which might be high utility and you often use it in the background but you may not mess with the referral functionality more than once a month. This means that while the product is super sticky (by the way, it is -- Dropbox has signed up hundreds of millions of users), it might take years to generate viral signups simply because the loop speed is slow.
病毒循环的“速度”是一个重要的概念。病毒性可能不会迅速显现，特别是当它是一个高留存率/低垃圾信息的产品时。当病毒因子在多次会话中缓慢生成时，你可以理解为什么病毒循环有一个生成邀请的速度。如果你有一个用户每天都参与的产品，比如社交网络应用，那么他们可能每天都会发送大量邀请。这会导致病毒因子的积累，从而快速生成更多的注册。与此形成对比的是像 Dropbox 这样的产品的推荐计划，它可能具有高实用性，你经常在后台使用它，但你可能每月只使用一次推荐功能。这意味着虽然产品非常粘性（顺便说一下，确实如此——Dropbox 已经注册了数亿用户），但可能需要数年时间才能生成病毒注册，仅仅是因为循环速度慢。
In that way, viral loops can be slow, powerful, and make big userbases even bigger. And this is important particularly in later stages when you really don't want to use paid marketing extensively.
这样一来，病毒循环可以是缓慢的、强大的，并且可以使庞大的用户群体变得更大。这一点在后期阶段尤为重要，因为那时你真的不想广泛使用付费营销。
In markets like consumer or prosumer where the eventual goal of an app is to sign up hundreds of millions of users, you're not really wanting to use paid marketing to buy an audience of that size. After all, 200 million users * $10/install = crazy money. Instead you'd like to get there because you spend millions on marketing but you also get a lot of organic spread. You get a discount that comes from all of your viral loops, you have SEO and ASO, etc. (And GEO, or whatever comes next in the AI era)
在消费者或专业消费者等市场中，应用程序的最终目标是吸引数亿用户，你并不想通过付费营销来购买如此规模的受众。毕竟，2 亿用户 * $10/安装 = 天文数字。相反，你希望通过花费数百万在营销上，同时也获得大量的自然传播来实现这一目标。你通过所有的病毒循环获得折扣，还有 SEO 和 ASO 等。（以及 GEO，或在 AI 时代接下来的任何东西）
Long live ragebaiting and shitpoastingOK so let's wrap this up -- what's going on in today's viral marketing landscape?
长存的愤怒诱饵和垃圾帖 好吧，让我们总结一下——当今的病毒营销格局是怎样的？
If you believe my framework so far, it means that shitpoasting and ragebaiting and cinematic videos and so on, just serve to help generate random spikes of signups. They're not repeatable, but that's OK. But those signups are then amplified due to the nature of many of the AI tools out there.
如果你相信我到目前为止的框架，这意味着垃圾帖、愤怒诱饵和电影视频等，只是为了帮助产生随机的注册高峰。它们不可重复，但这没关系。但由于许多 AI 工具的特性，这些注册随后会被放大。
The current generation of AI tools often have a "create and share" viral loops that can amplify whatever top of funnel comes in. If you give your users a novel way to generate music, or video, or anything else using AI generative models, then naturally a high percent of users will do that. And then a high percent of users that interact with the generated result will want to share it with their friends and so that percentage will also be high.
当前一代的 AI 工具通常具有“创建和分享”的病毒循环，可以放大任何进入漏斗顶部的内容。如果你为用户提供了一种新颖的方式来使用 AI 生成模型生成音乐、视频或其他任何东西，那么自然会有很大比例的用户去这样做。然后，与生成结果互动的用户中也会有很大比例的人想要与他们的朋友分享，因此这个比例也会很高。
I think that's why we're seeing so many amazing highly visual AI tools becoming super viral because they not only use this "create and share" of our loop. Further, we're in the age of highly visual social media -- short form videos, embedded clips on posts, etc. And so the nature of gen AI output and what's working on social platforms is highly resonant. This means it'll spread far and wide.
我认为这就是为什么我们看到如此多令人惊叹的高度视觉化的 AI 工具变得超级病毒式传播的原因，因为它们不仅使用了我们循环中的“创建和分享”。此外，我们正处于高度视觉化的社交媒体时代——短视频、帖子中的嵌入剪辑等。因此，生成 AI 的输出和在社交平台上有效的内容具有高度的共鸣。这意味着它将广泛传播。核心总结：
现代产品的病毒增长依赖于"留存率+多循环"需要多元化的获客渠道（付费、SEO、推荐等）
>留存率是关键：病毒系数是跨多个会话累积的总和，而非单次爆发
>高留存产品可以温和地推动分享，低留存产品则需要激进spam
病毒系数<1仍然有价值
>0.2-0.3的系数意味着每1000个用户能"免费"带来200-300个新用户
>能有效降低获客成本
AI时代的机遇
>"创建并分享"循环天然适合AI生成内容
>与当前视觉化社交媒体完美契合
这解释了为什么AI工具能够快速传播。
病毒式营销不再是一次性爆发的魔法，而是通过优秀的产品留存率，
在长时间内累积多个病毒循环的结果。
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