AEO终极指南：如何让ChatGPT推荐你的产品 | Ethan Smith（Graphite）

现在大家都在谈论一个术语

There's this term everyone's hearing

关于AEO，即答案引擎优化。我该如何在LMS中作为答案出现？赢得AEO似乎非常重要。要赢得像网站构建器这样的东西，那么如果谷歌的蓝色链接首先出现，他们就会获胜。

about, AEO. Answer engine optimization. Just how do I show up in, LMS as an answer? It feels like such a big deal to win at AEO. In order to win something like what's the website builder, then Google, they would win if their blue link showed up first.

但在LM中情况并非如此，因为LM正在汇总许多引用，所以你需要尽可能多地被提及。

But that's not the case in the LM, because the LM is summarizing many citations, and so you need to get mentioned as many times as possible.

ChatGPT为我的新闻通讯带来的流量比Twitter还多。

ChatGPT is driving more traffic to my newsletter than Twitter.

你明天可能通过一次引用被提及，然后立即开始出现。你可以有一个Reddit帖子。你可以有一个YouTube视频。你可以在博客上被提到。所以早期公司也能获胜。

You can get mentioned by a citation tomorrow and start showing up immediately. You can have a Reddit thread. You can have a YouTube video. You can be mentioned on a blog. So early stage companies can win.

他们可以快速获胜。

They can win quickly.

这些答案引擎为公司带来的潜在客户真的有价值吗？

Are the leads that these answer engines driving to companies actually valuable?

价值显著更高。Webflow 发现 LLM 流量与谷歌搜索流量之间的转化率相差六倍。

Significantly more valuable. Webflow saw a six x conversion rate difference between LLM traffic and Google Search traffic.

很多人认为一切都不同了。我们以前做的一切都不再奏效。我们必须重新思考所有事情。

A lot of people are seeing this as everything is different. Nothing we've done before is gonna work. We have to rethink everything.

关于 AEO 存在大量错误信息。有新闻文章说谷歌搜索将消亡，因为出现了新事物。但谷歌的市场份额保持不变，只是整个市场变大了。

There's significant misinformation on AEO. There's news articles about how Google searches is going to die because there's a new thing. Google's slice of the pie stays the same. The pie gets bigger.

今天我的嘉宾是 Ethan Smith。Ethan 是 Graphite 的 CEO，也是我在所有 SEO 问题上的首选专家。SEO 目前正在经历重大转型。过去人们有任何问题、寻找产品或做研究时都会去谷歌。如今，很多人转向 ChatGPT、Claude、Gemini 和 Perplexity 来获取答案，而且这一趋势只会加速发展。

Today, my guest is Ethan Smith. Ethan is the CEO of Graphite and my go to expert for all things SEO. SEO is going through a major transition right now. Everyone used to go to Google anytime they had a question or were looking for a product or doing research. These days, a lot of people are moving to ChatGPT and Claude and Gemini and Perplexity to get answers to their questions, and this will only be accelerating over time.

甚至谷歌也在以相当激进的方式改变搜索体验，包括顶部的 AI 概览和新推出的 AI 模式（基本上是它们自己的 ChatGPT 版本）。这意味着 SEO 世界正在经历巨大变化，包括 AEO（答案引擎优化）的兴起，这本质上是针对 ChatGPT 的 SEO，让你的产品出现在人们获得的答案中。Ethan 一直处于这一新技能和渠道的前沿，在这次对话中，他分享了关于如何让你的产品更频繁地出现在人们答案中的所有经验。Ethan 在这次对话中分享的建议极具战术性且价值连城，请尽情吸收并用于你自己的产品。如果你喜欢这个播客，别忘了在你最喜欢的播客应用或 YouTube 上订阅和关注。

And even Google is changing the search experience in a pretty radical way with AI overviews at the top and their newly introduced AI mode, which is basically their own version of ChatGPT. This means that the world of SEO is going through a big change, including the rise of AEO, which stands for Answer Engine Optimization, basically SEO for ChatGPT, getting your product to show up in the answers that people get. Ethan has been at the forefront of this new skill and channel, and in this conversation, he shares everything that he's learned about how to get your product to show up more often inside of the answers that people get. The advice that Ethan shares in this conversation is incredibly tactical and worth a lot of money, so please slurp it up and use it for your own products. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube.

这对我们帮助巨大。如果你成为我新闻通讯的年度订阅者，你可以免费获得 15 款惊人产品的一年使用权，包括 Lovable、Replit、Bolt、n eight n、Linear、Superhuman、Descript、WhisperFlow、Gamma、Perplexity、Warp、Granolah、Magic Patterns、Raycast、Japyardee 和 Mobin。请访问 lenny'snewsletter.com 并点击产品通行证查看。在此，我为你带来 Ethan Smith。本集由 Orcus 赞助，该公司是开源 Conductor 的背后推手，这是一个为现代企业应用和智能体工作流提供动力的编排平台。

It helps tremendously. And if you become an annual subscriber of my newsletter, you get a year free of 15 incredible products, including Lovable, Replit, Bolt, n eight n, Linear, Superhuman, Descript, WhisperFlow, Gamma, Perplexity, Warp, Granolah, Magic Patterns, Raycast, Japyardee, and Mobin. Check it out at lenny'snewsletter.com and click product pass. With that, I bring you Ethan Smith. This episode is brought to you by Orcus, the company behind Open Source Conductor, the orchestration platform powering modern enterprise apps and agentic workflows.

传统自动化工具无法跟上步伐。孤立的低代码平台、过时的流程管理和脱节的 API 工具在当今事件驱动、AI 赋能的智能体生态中已力不从心。Orcus 改变了这一点。通过 Orcus Conductor，你获得了一个智能体编排层，可无缝连接人类、AI 智能体、API、微服务和数据管道，实时且达到企业级规模。可视化与代码优先开发、内置合规性、可观测性和坚如磐石的可靠性确保工作流随你的需求动态演进。

Legacy automation tools can't keep pace. Siloed low code platforms, outdated process management, and disconnected API tooling fall short in today's event driven AI powered agentic landscape. Orcus changes this. With Orcus Conductor, you gain an agentic orchestration layer that seamlessly connects humans, AI agents, APIs, microservices, and data pipelines in real time at enterprise scale. Visual and code first development, built in compliance, observability, and rock solid reliability ensure workflows evolve dynamically with your needs.

这不仅仅是自动化任务。它关乎编排自主代理和复杂工作流，以更快地交付更智能的成果。无论是现代化遗留系统还是扩展下一代AI驱动的应用程序，Orcus都能加速您从想法到生产的旅程。了解更多并开始构建，请访问orkus.i0/lenny。即0rkes.i0/lenny。

It's not just about automating tasks. It's orchestrating autonomous agents and complex workflows to deliver smarter outcomes faster. Whether modernizing legacy systems or scaling next gen AI driven apps, Orcus accelerates your journey from idea to production. Learn more and start building at orkus.i0/lenny. That's 0rkes.i0/lenny.

我的播客嘉宾和我都喜欢谈论工艺、品味、能动性和产品市场契合度。你知道我们不喜欢谈论什么吗？SOC 2。这就是Vanta的用武之地。Vanta通过行业领先的AI、自动化和持续监控，帮助各种规模的公司快速实现合规并保持合规。

My podcast guests and I love talking about craft and taste and agency and product market fit. You know what we don't love talking about? SOC two. That's where Vanta comes in. Vanta helps companies of all sizes get compliant fast and stay that way with industry leading AI, automation, and continuous monitoring.

无论您是初创公司应对首个SOC 2或ISO 27001，还是企业管理供应商风险，Vanta的信任管理平台都使其更快速、更简单且更具可扩展性。Vanta还帮助您完成安全问卷的速度提高多达五倍，以便您能更快赢得更大交易。结果如何？根据IDC最近的一项研究，Vanta客户每年节省超过50万美元，并且效率提高了三倍。建立信任并非可有可无。

Whether you're a startup tackling your first SOC two or ISO twenty seven zero zero one or an enterprise managing vendor risk, Vanta's trust management platform makes it quicker, easier, and more scalable. Vanta also helps you complete security questionnaires up to five times faster so that you can win bigger deals sooner. The result? According to a recent IDC study, Vanta customers slashed over $500,000 a year and are three times more productive. Establishing trust isn't optional.

Vanta使其自动化。在vanta.com/lenny获取1000美元优惠。Ethan，非常感谢你来到这里，欢迎来到播客。欢迎回到播客。

Vanta makes it automatic. Get $1,000 off at vanta.com/lenny. Ethan, thank you so much for being here, and welcome to the podcast. Welcome back to the podcast.

很高兴能回来。

Excited to be back.

我们在大约两年半前做过一期播客节目。我认为它是关于如何赢得SEO的权威指南。从那以后人们一直在引用它。我真的很为我们所做的感到自豪。但情况已经发生了变化。

We did a podcast episode just over two and a half years ago. I think of it as the definitive guide on how to win at SEO. People have been referencing it ever since. I'm really proud of what we did there. But things have changed.

SEO世界正在发生变化。因此，我很高兴再次与你讨论如何在这个AI正在改变SEO运作方式、AEO和GEO兴起的新兴世界中取得成功。让我先问这个问题：到目前为止，你从事SEO工作多久了？在改变SEO技能方面，有什么能接近这次变革的显著性吗？

Things are changing in the world of SEO. And so, I'm excited to talk to you again about how to be successful in this new emerging world where AI is changing, how SEO works, the rise of AEO and GEO. Let me start with just this question. How long have you been working on SEO at this point, and has anything come close to being this significant in changing the skill of SEO?

是的。我于2007年2月开始接触SEO，至今已有十八年了。实际上，我刚开始做SEO时最大的变化是，我最初从事的是程序化SEO和电商SEO，比如NextTag、shopping.com和PriceGrabber。那时候你可以大量自动生成着陆页。这可能是最大的转变，因为谷歌推出了一系列算法，如熊猫算法等，来防止垃圾内容。

Yes. So I got started in SEO in 02/2007, so it's been eighteen years. And the actually, the largest change when I got started in SEO, I got started in programmatic SEO and commerce SEO, like NextTag and shopping.com and and PriceGrabber. And that was when you could do mass auto generated landing pages. And that was probably the biggest shift, which is Google introduced a bunch of algorithms, a panda and and similar things to prevent you from doing spam.

所以本质上，SEO从垃圾内容变成了非垃圾内容。这可能是最大的变化，而这次可能是第二大的变化。我认为这里的关键是，虽然它与搜索相关，但这是对搜索的总结，并且有新的输入方式。所以这可能是第二大的变化。

So essentially, you went from SEO being spam to not spam. That was probably the biggest change, and then this is probably the second biggest change. I think that the main thing here is it is related to search, but it's a summarization of search and there's new inputs. So it's probably the second biggest change.

好的。这真的很有趣，因为我觉得很多人认为一切都不同了。我们以前做的一切都不再有效，必须重新思考所有事情。你说这实际上是第二大的变化，就像当年谷歌的更新一样，甚至更加重大。

Okay. That is really interesting because I think a lot of people are seeing this as like, everything is different. Nothing we've done before before is gonna work. We have to rethink everything. You're saying this is actually the second biggest change, and just like Google's update back in the day, it was actually even more significant.

是的。非常酷。

Yep. Very cool.

好的。让我们给大家提供一些背景。定义一些术语。有一个大家都在听的术语，实际上有两个，AEO和GEO。

Okay. Let's set a little context for folks. Let's define some terms. There's this term everyone's hearing about. There's actually two, AEO and GEO.

它们代表什么？它们不同吗？具体指的是什么？

What do they stand for? Are they different? What are they referring to specifically?

我认为它们是一样的。归根结底，一个词的定义就是一群人同意它是那个词的定义。所以我认为我们会看到人们决定这个词的定义是什么。我提出我的定义。AEO和GEO本质上试图描述同一件事，即我如何在语言模型（LMs）中作为答案出现？

They, I think, are the same. Ultimately, the definition of a word is whatever a group of people agree is the definition of a word. So I think we'll see what people decide as the definition of the word. I'll put forward my definition. So AEO and GEO are are essentially trying to describe the same thing, which is how do I show up in in LMs as an answer?

我个人更倾向于答案引擎优化而非生成引擎优化，因为生成式可以生成图像、视频等非答案内容，而答案的定义更为狭窄。所以我个人偏好是我们在讨论优化语言模型时，答案是一个比生成更狭义的定义。但最终，无论我们决定用什么名称和定义，它就是什么。

And I personally prefer answer engine optimization versus generative engine optimization because generative can you can generate images and videos and things other than an answer, whereas Answer is more narrowly defined. So my personal preference is we're talking about optimizing LM. So an Answer is more more narrow of a definition than generative, but ultimately, it's whatever whatever we decide is is the name and the definition is what it will be.

好的。确实，如果必须选一个的话，答案引擎优化听起来更简洁。很高兴知道它们是一回事。有些人就是莫名其妙更喜欢后者。

Okay. Yeah. Answer engine optimization sounds a lot cleaner to me if you had to pick one. So it's good to know they're the same thing. People some people just prefer the latter one for some reason.

这很有趣，因为最近——不知道我是否告诉过你——我在查看推荐流量时发现，ChatGPT 为我的新闻通讯带来的流量比 Twitter 还多，这完全出乎我的意料。所以某种程度上这已经在发生了。我很兴奋能学习如何进一步利用这一点并优化它。

It's interesting because recently, I don't know if I told you this, but I was looking at my referral traffic, and I found that ChatGPT is driving more traffic to my newsletter than Twitter, which I did not see coming. So somehow it's already happening. I'm excited to learn just how to lean into that potentially and optimize it further.

你是什么时候看到流量激增的？有没有注意到它是从什么时候开始大幅增长的？

And when did you see the spike? Did you see when it started growing dramatically?

不幸的是，我使用的仪表板没有提供很好的周边流量优化数据。你觉得我可能是什么时候注意到它的？

Unfortunately, the dashboard I have doesn't give me great, like, peripheral traffic optimization. When when do you think I probably saw it?

我们合作的公司从一月份开始出现增长，一方面是因为采用率提高，但另一方面是因为答案变得更具可点击性。出现了地图、购物轮播图、可点击卡片等功能。所以我认为答案的可点击性增加了。

Companies that we work with started in January, and it started, one, because of more adoption, but two is because the answers became a bit more clickable. You have maps. You have shopping carousels. You have clickable cards. So I think the clickability of the answers increased.

嗯。然后采用率增加了，这样挺好的。大概是在那段时间。

Mhmm. And then the adoption increased, and that was Okay. Around

我想回到这个问题：ChatGPT 吸走我所有内容，给人们答案，然后分给我一部分收益，这是好事吗？但我们先不深入讨论这个。我想先谈谈你的内容出现在 ChatGPT 中能产生什么样的影响。最近我请 ChatGPT 的负责人尼克·特利上播客，问他如何看待 AEO、GEO 这些东西。他说，别担心那些，完全不用在意。

I wanna come back to this question of, is this good that ChatGPT is sucking out all my content and giving people answers and then sending me some percentage of that? But I wanna let's not get into that yet. I wanna talk about just what kind of impact you can have on having your stuff show up in ChatGPT. So I had the head of ChatGPT, Nick Turley, on the podcast recently asked him, what do you think of all this stuff, AEO, GEO? He's like, don't don't worry about any of that.

只管写出精彩的内容，高质量的内容。它会自己搞明白的，会找到最好的东西。我猜你非常不同意这个观点。

Just write awesome stuff. Great quality content. It'll figure it out. It'll find the best stuff. I imagine you very much disagree.

我猜你已经看到主动将内容植入这些答案引擎所带来的实际影响。谈谈你看到的影响，以及你对此的反应。

I imagine you have seen real impact getting your stuff proactively into these answer engines. Talk about just the kind of impact you've seen and what you and just your your reaction to that.

是的，我既同意又不同意。但我觉得，任何事物都可以被优化，你只需要理解底层系统和游戏规则。如果你做到了，那么什么都可以优化，算法可以优化，

Yeah. I agree and disagree, but, you know, the way that I think about it is anything can be optimized. You just need to understand the underlying systems and the rules of the game. And if you do that, then you can optimize anything. You can optimize algorithms.

人也可以优化，什么都可以优化。我认为他可能的意思是两件事：一是请不要在我的产品上发垃圾信息，二是如果你这么做，我会发现并阻止你。

You can optimize people. Anything can be optimized. What I think he probably meant by that I mean, probably meant two things. One is please don't spam my product. And two is if you do, I will see it, and I will stop you from doing that.

所以制造垃圾信息不是长期稳健的策略，就像在谷歌上制造垃圾信息也不是长期稳健的策略一样。最终，谷歌会说，那些大型购物比价网站自动生成了一亿个搜索页面，我不喜欢这样，我要整个清除这个类别。ChatGPT 也一样。什么都可以优化，但如果你发垃圾信息，他们会发现，并有一整个团队来处理，然后他们会调整算法来阻止你这么做。

So it's not a long term robust strategy to create spam just like it wasn't a long term robust strategy to create spam on Google. Eventually, Google is gonna say, huge shopping comparison sites are making a 100,000,000 auto auto generate search pages, and I don't like it. And I'm gonna get rid of the whole category. So same thing with ChatGPT. Anything can be optimized, but if you're spamming it, they'll see that, and they'll have a whole team looking at that, and then they'll change your algorithm to prevent you from doing that.

你看到了什么样的影响？你和很多公司合作过。我们讨论几个例子，也许分享一个来给我们一些背景。就像你能在多大程度上影响这种事情，比如更频繁地出现在聊天中？

What kind of impact have you seen? You've done work with a lot of companies. We'll talk through a few examples. Maybe share one to give us context. Just like how much can you impact this sort of thing where you show up in, say, chat should be more often?

你可以受到很大影响。以Webflow为例，我们正在与他们合作进行SEO或内容优化，并且在答案引擎优化方面看到了很多成功。我们做的具体事情，首先是传统SEO。为高搜索量的关键词创建落地页，比如'最佳无代码网站设计器'，然后你就能免费获得答案引擎优化的效果。所以这只是传统SEO，对你来说效果很好。

You can you can affected a lot. So a specific example with Webflow is we are working with Webflow on their SEO or on their content, And we're seeing a lot of wins on the answer engine optimization side. So the specific things that we've done there, one is just traditional SEO. So make landing pages for high search high search volume keywords, like, you know, best no code website designer, and you then for free, you'll get answer engine optimization impact from that. So that's just traditional SEO, which works very well for you.

我正想说这听起来和常规SEO完全一样。

Was just gonna say that sounds exactly the same as regular SEO.

是的。所以我认为所有在SEO中有效的方法在AEO中也有效，但AEO还有超越SEO的额外方法。第二点，我对AEO与SEO的思考方式是头部和尾部是不同的。头部不同在于，要赢得像'最佳网站构建器'这样的查询，即使Webflow的URL在引用中排名第一，他们也不会因为URL排名第一而赢得答案。但在Google中，他们会赢。

Yeah. So I would say everything that works in SEO works in AEO, but there are additional things beyond SEO that also work in AEO. So second thing and the way that I think about AEO versus SEO is that the the head and the tail are different. So the head is different in that in order to win something like what's the best website builder, even if Webflow's URL shows up number one in the citations, they're not going to win the answer because their URL showed up number one. But at Google, they wouldn't they would win.

如果他们的蓝色链接排在第一位，他们就会赢。但在语言模型中不是这样，因为语言模型会总结多个引用。所以你需要尽可能多地被提及。通常当你问'x的最佳工具是什么？'时，第一个答案会在引用中被提到最多次。

If their if their blue link showed up first, they would win. But that that's not the case in the LM, because the LM is summarizing many citations. And so you need to get mentioned as many times as possible. So usually when you when you ask something like, what's the best tool for x? The first answer will be mentioned at the most in the citations.

这与Google非常不同。对于Webflow，我们与他们合作优化YouTube视频、Vimeo视频，在Reddit中被提及，在其他博客、联盟营销等渠道被提及。尝试了很多方法。特别有效的方法首先是直接SEO，第二是YouTube视频，第三是Reddit优化。

That's very different from from Google. And so for Webflow, we work with them on YouTube videos, Vimeo videos, getting mentioned in Reddit, getting mentioned in other blogs, affiliates, stuff like that. So try a bunch of stuff. Stuff that worked especially well was just straight SEO, number one. Number two is YouTube videos, and then the third is Reddit optimization.

好的。哇。所以你是说，如果你能在IGBT问'最佳网站构建器是什么'时排名第一，Webflow排在顶部，这实际上不如在总结中被最频繁提及带来的流量多。

Okay. Wow. So you're saying if you if you can get to number one, if when you ask IGBT, what's the best website builder and Webflow is at the top, that doesn't actually drive them as much traffic as simply being mentioned most often across the summary.

是的。这部分之所以有趣是因为，当初创公司来找我寻求SEO帮助时，我的第一反应是根本不要做。把时间花在其他事情上，因为你早期无法通过搜索增长SEO，因为你没有足够的域名权威，而建立域名权威需要时间。只有当你有了域名权威后，你才能排名。所以对于Google来说，这通常是你到A轮、B轮或更后期才会做的事情。

Yes. And part of why that's interesting is because if you're a when when startups come to me and ask me for SEO help, my first response is don't do it at all. Spend your time on something else because you're not going to be able to grow SEO early on as a in search because you don't have enough domain authority, and it takes a while to get domain authority. And only once you have domain authority can you rank. And so for Google, it's usually something that you do series a, series b, or later.

你不会一开始就做这件事，因为早期无法获胜。但答案引擎优化不同，因为你明天就可能被引用源提及并立即开始展现。你可以有一个Reddit帖子，可以有一个YouTube视频，可以被博客提及，比如一家全新的YC公司刚成立。

You don't do it as soon as you start because you can't win early on. That's not the case for answer engine optimization because you can get mentioned by a citation tomorrow and start showing up immediately. You can have a Reddit thread. You can have a YouTube video. You can be mentioned on a blog, like a, you know, a brand new YC company launches.

所有人都在讨论他们。因此他们明天就可能出现在答案中。所以早期公司可以获胜，可以快速获胜，任何人都可以通过被引用源尽可能多地提及而快速获胜。这就是头部优化的不同之处。

Everyone's talking about them. They could show up in an answer tomorrow as a result of that. So early stage companies can win. They can win quickly, and they can win quickly, and anyone can win quickly by getting mentioned as many times as possible by the citations. So that's the that's what's different about the head.

尾部优化的不同在于，聊天中的尾部比搜索中更大。Perplexity曾向别人提到平均词数约为25个词，而谷歌搜索约6个词。所以尾部要大得多得多。人们会提出大量后续问题。

What's different about the tail is that the tail is larger in chat than in search. So the average number of words I think Perplexity said this to somebody else who said it was around 25 words where versus Google words around six words. So the tail is just much, much larger. People are asking lots of follow-up questions.

尾部本质上是指提示词，即你提出的问题。

Tail the the prompt, essentially, the question you're asking.

是的。意思是如果你像SEO长尾关键词那样绘制出人们提出的所有问题，如果你做长尾问题，尾部的规模更大。意味着非常具体的问题数量更多，份额和量级更大。而且可能存在从未被问过或搜索过的问题，因为搜索无法支持大量非常具体的内容，而聊天正是为提出一系列后续问题和进行对话而设计的。所以现在出现了所有这些从未被问过或搜索过的问题，然后你就可以赢得这些机会。

Yes. Meaning that if you if if if you map out all of the questions that people ask kind of like an SEO long tail keywords, If you do long tail questions, the size of the tail is larger. Meaning, the amount of questions that are very specific is larger, the, you know, the share and the volume. And there's probably questions that have never been asked before and questions that have never been searched before because search can't support lots of really specific, super specific stuff, whereas chat is specifically made to ask a bunch of follow-up questions and have a conversation. And so there's all these questions that have never been asked or searched for before that are now being asked, and then you can win that.

当我开始做SEO时，是长尾SEO时代，需要为每个关键词创建页面，但这现在已经行不通了。但现在长尾策略在聊天中重新出现。如果你了解人们正在提出的所有这些非常具体的问题，你也可以赢得这些机会。而且很可能早期就能获胜。我见过一些刚推出非常具体的AI驱动支付处理API的早期公司案例，它们会出现，并且会因为回答从未被回答过的问题而展现出来。

And when I got started in SEO, it was long tail SEO where you have a page for every single keyword, which doesn't work anymore. But now the long tail is back in chat. And if you know all those really specific questions that people are asking, you can also win that. And you can probably also win that early. And I've seen examples of early stage companies who just launched some really specific AI enabled payment processing API thing, and they will show up, and they'll show up because they're answering questions never been answered before.

这些答案引擎给公司带来的线索真的有价值吗？特别是对于B2B SaaS来说，这些是高质量线索吗？

Are the leads that these answer engines driving to companies actually valuable? Are these, like, good quality leads for B2B SaaS especially?

它们的价值要高得多。以Webflow为例，我们看到LM流量和谷歌搜索流量之间的转化率相差六倍。

They are significantly more valuable. So Webflow, we saw a six x conversion rate in difference between LM traffic and Google search traffic.

六倍。

Six times.

六倍。所以质量明显更高。我认为这可能有几个原因。可能是因为你已经做好了充分准备，通过多次跟进对话建立了强烈的意向，并且很可能已经精确锁定了你想要的东西。

Six times. So significantly more qualified. I think that's probably for a couple reasons. Probably, it's because you're so primed because you're having a conversation with multiple follow ups, and so there's so much intent that you've built. And you've probably really narrowed in on what you want.

所以当你前往某个地方时，很可能匹配度非常高。因此我们看到转化率要高得多。

So when you're going somewhere, it's probably highly qualified. And so we're we're seeing that it's much higher conversion rate.

哇。这太有趣了。而且很有道理。就像人们信任ChatGPT给出的答案。如果你就是那个答案，你就拥有巨大优势。

Wow. This is so interesting. And it makes sense. Like, people trust ChatGPT to tell them the answer. And if you are the answer, you have so much advantage.

就像是，这就是人们想知道的，然后，好的。太棒了。谢谢。我要去了解一下。这一切都说得通。

You like, that is what people want to know and then, okay. Cool. Thank you. I'm gonna go check this out. This all just makes sense.

回到你分享的三个杠杆，本质上就是落实那些在推动你更多地出现在这些答案引擎中有效的方法：落地页、YouTube视频和Reddit。是这样吗？

Going back to the three levers you shared, essentially, it's landing the things that you see work in driving you showing up more in these answer engines. Landing pages, YouTube videos, and Reddit. Is that right?

这些是其中一部分。我会将其分为站内和站外两类。站内部分指的是传统SEO，区别在于长尾关键词。我还要说区别在于会有大量关于产品功能的后续问题。

Those are some of them. The other things so I would I would break it up into stuff on your site, on-site and off-site. So on-site would be traditional SEO. The difference would be this long tail. I would also say that the difference is lots of follow-up questions about does your product do this thing?

比如使用场景、功能特性、集成支持、语言兼容性？就像详细询问产品信息及其具体细节，这些都发生在你的网站上。第二类是站外曝光，出现在各种引述中。这些引述包括视频UGC内容，如Reddit和Quora，以及联盟营销——Meredith正在遍地开花，Glamour、Good Housekeeping等媒体都在提及它。

What are the use cases, features, integrations, languages? Like, tell me about your product and really specific details about that, and that's on your site. And then the second group would be off-site, which is show up in all the citations. Citations are comprised of video UGC, like Reddit and and Quora, affiliates.- Meredith is showing up all over the place. Glamour, Good Housekeeping, it's, like, getting mentioned there.

还有博客内容。总之就是这两大类。

Blogs. So it's those those two groups.

这些听起来和SEO非常相似——出现在他人页面上，获取来自Reddit等平台的链接总是很棒。有趣的是Reddit如此重要。你觉得这是怎么回事？

And that all that all sounds very similar to SEO showing up on other people's pages, showing links from, say, Reddit is always great. It's interesting that Reddit is such a big deal. What's going on there, do you think?

Reddit是最有意思的平台之一。它在LMS中被大量引用，可能是客户问我最多的问题：如何优化Reddit？这又回到ChatGPT负责人关于不要滥发产品信息的问题。Reddit是一个社区，那里有真实的用户意见，真实可信，且由社区严格管理。

Okay. Reddit is one of the most interesting things. It's hugely cited in LMS, and it's probably the number one thing people are asking customers are asking me is how do we optimize for Reddit? And this goes back to the head of ChatGPT's question about please don't spam my my product. And so Reddit is a community where it's, you know, real opinions from people, authentic, and it's heavily managed by the community.

社区非常善于管理内容。所以增长人员的明显策略就是制造大量自动化垃圾信息，到处刷Reddit，让产品无处不在。这是增长思维，也可以说是 hustle 心态。人们在做什么？他们在创建数百个虚假Reddit账号，冒充他人身份。

And the community is very good at managing it. And so the obvious strategy for a growth person is let's make a bunch of automated spam and spam Reddit all over the place and get my product to show up everywhere. That that that's the growth mindset, which makes sense, the the hustle mindset. So what are people looking at? They're they're looking at creating hundreds of fake Reddit accounts pretending to be someone that you're not.

比如一个人创建100个Reddit账号，自动发布评论然后自问自答，建立信任评分后到处宣称自己的产品是最好的。幸运的是这种方法效果不佳，但这确实是明显策略。我们看到有人尝试这样做，然后这些账号被封禁，评论被删除。

Like, I have a single person. I'm gonna make a 100 Reddit accounts. I'm gonna auto post comments and then like my own comments and then build a trust score and then show say everywhere that my my product is the best product. Fortunately, that doesn't work very well, but that's the obvious strategy. And so we're seeing people trying to do that, and then we're also seeing those accounts get banned, those comments get deleted.

所以我们看到人们试图进行垃圾信息传播但并不成功。这是其中一种策略。另一种策略是，Reddit的整个宗旨就是发布来自真实用户的有用、高质量、真实的评论。所以在Webflow，我们有几个人会去评论区说，这是我的名字，这是我工作的地方，然后提供一条有用的信息。

And so we're seeing people trying to spam and being unsuccessful. So that that's one strategy. The other strategy is the whole purpose of Reddit is to post useful, high quality, authentic comments from real people. So at Webflow, we we we have a couple people at Webflow going to comments and saying, this is my name. This is where I work, and here's a useful piece of information.

所以策略就是找到一个你想在其中展示的引用线索，说明你是谁，说明你在哪里工作，然后提供有用的信息，这效果非常好。如果你没有那种'我需要把这个扩展到数百条评论'的增长心态，这听起来很简单，但你实际上并不需要一万条评论。你知道，甚至五条就很棒了，而且这样扩展得非常好。所以Reddit策略就是显而易见的策略，就是真正成为Reddit的用户。创建一个账户，说明你是谁，说明你在哪里工作，然后给出有用的回答。

So the strategy is find a thread that is a part of a citation that you wanna show up in, say who you are, say where you work, and then give a useful piece of information, and that works really well. And that sounds simple if you're not in the growth mindset of I need to scale this to hundreds of comments, but you don't actually need 10,000 comments. You you know, even five could be great, and that scales perfectly well. So the the Reddit strategy is the obvious strategy, which is just just to be an actual user of Reddit. Make an account, say who you are, say where you work, and give a useful answer.

我们之前请过Deal（d e e l）的早期增长负责人在播客上做客，这就是他们成长的方式，以及在AI出现之前他们最初是如何增长的。就是在Reddit上大力投入，回答人们的问题，比如，嘿，正好Deal可以帮你解决这个问题。所以这很有趣。非常有趣的是，Reddit正在阻止ChatGPT被垃圾信息淹没。

We had the early growth leader from Deal, d e e l, on the podcast a while ago, and this is how they grew up and how they grew initially before AI even came around. Just going big on Reddit and answering people's questions and, like, hey. Happens to be Deal can help you with this problem. So that's interesting. It's so interesting that Reddit is what is keeping ChatGPT from being spammed with stuff.

就像，并不是ChatGPT在阻止垃圾信息。而是Reddit在这方面确实做得很好。

Like, it's not that ChatGPT is stopping the spam. It's Reddit is just really good at that.

我认为在某种意义上，ChatGPT是在进行监管，因为ChatGPT在进行搜索。它正在寻找引用来源。有一个搜索算法试图选择哪些引用是有用的。ChatGPT有人正在调整他们的搜索算法来选择他们信任的来源。我肯定有一个搜索评估团队在说，我喜欢这些引用吗？

I think that in a sense, ChatGPT is policing because ChatGPT is running a search. It's finding citations. There's a search algorithm that's trying to select which citations are useful. There are people at ChatGPT who are tuning their search algorithm to select which sources they trust. I'm sure that there's a search evaluation team saying, do I like these citations?

是的。不。Reddit出现了吗？我希望它出现。所以我认为ChatGPT确实有人在有意配置他们的算法来使用Reddit，因为它是可信的。

Yes. No. Is Reddit showing up? I want it to show up. So I think that there are actual people at ChatGPT who are intentionally configuring their algorithm to use Reddit because it's trusted.

如果它不可信，他们就不会使用它。谷歌也是一样。谷歌专门配置了他们的搜索算法来排名Reddit、Twitter和Quora，因为他们想要用户生成的内容。如果内容不好，他们就会改变算法，就不会给它排名。所以我认为在某种意义上他们是在进行监管。

And if it wasn't trusted, they wouldn't use it. Same with Google. Google has specifically configured their search algorithm to rank Reddit and Twitter and Quora because they want user generated content. And if it wasn't good content, then they would change the algorithm, and they wouldn't they wouldn't rank it. So I think that they are policing it in a sense.

明白了。这些都是模型训练后的搜索导向功能，与它们的训练数据无关。是这样吗？

Got it. And all of this is post training search oriented features of of these models. It's not data they are trained on. Is that right?

我认为是这样的：有一个核心模型，然后还有RAG。核心模型是通过查看Common Crawl和数十亿网页来重新训练模型。如果你问'加利福尼亚的首府是哪里？'，它会预测下一个词是'Sacramento'。这是基于核心算法，即下一个词预测。

I would assume that the so there's the core model, and then there's REG. So the core model is I'm looking at common crawl and billions of web pages, and then I'm, you know, re retraining the model. And if you ask something like, what's the capital of California? It predicts the next word, which is Sacramento. And that's based on the core algorithm, which is net next word prediction.

然后是RAG，RAG基本上意味着搜索、检索、增强生成。我会先进行搜索，然后总结搜索结果。这是两个不同的东西。所以我描述的大部分是关于RAG部分，而不是核心模型部分。要影响核心模型可能极其困难，也许一年后才能看到效果，而且可能是某种晦涩的事情，比如制作百万页面说'X的最佳产品是某品牌'，我认为大多数人不会想花时间做这个。

Then there's RAG, and RAG basically means search, retrieval log meta generation. So I'm gonna do a search, and then I'm gonna summarize the search. There there are these two different things. And so most of what I'm describing is about the RAG piece, not the core model piece. To in to influence the core model is probably extremely hard, and maybe you you will see the impact a year later, and it's probably something, you know, some sort of obscure thing that nobody would wanna do, like make a million pages that say best product for x is brand, which I don't think most people wanna spend their time on.

所以我主要关注RAG方面，因为这是主要可控的部分。而且我认为如果某个产品没有出现在RAG搜索结果中，LLM很可能也不会推荐你的产品。所以我认为从优化角度来看，这里才是最有趣的地方。

So I'm mostly focused on the rag side because that's the main thing that's controllable. And I think also the LLM is is probably not going to say your product if it didn't show up anywhere on the rag. So I think that's where most of the interesting stuff is for from an optimization perspective.

很酷。我们开始讨论时我甚至没想到这一方面，但重要的是要注意这与训练数据无关。这是训练后的事情，一旦模型上线，它可以通过RAG、网络搜索等方式找到最新信息。好的，在我们逐步讨论如何实际操作、如何在AEO中获胜之前，你认为要在这个领域取得成功，人们需要理解哪两三个重要的事情？

Cool. I I didn't even think about this side of it when we started talking about this, but I think that's an important thing to note is just this has nothing to do with the training data. This is post training, once the model's live, what it can do to find recent information using Rag, web search, things like that. Okay. Before we get into how to actually do this step by step, how to win at AEO, what are two or three things that you think are important for people to understand to be successful in this world just broadly?

第一是要认识到这与搜索相关。所以是LLM加RAG，通常是总结一组搜索结果。所以第一点是LLM加RAG。第二点是主题。

First thing is just recognizing that this is related to search. So it's LLM plus rag. It's summarizing a set of search results usually. So LLM plus rag, number one. Number two is topics.

在搜索中，一个着陆页针对数百个关键词，我们在上一期播客中讨论过。所以我不像2007年那样只针对一个关键词，而是针对上千个关键词，每个着陆页都需要针对这组上千个关键词，这就是一个主题。答案引擎优化也是如此。每个页面都针对数百、数千，甚至数万个问题。

So in search, a landing page is targeting hundreds of keywords, which we talked about on the last podcast. So I'm not targeting one keyword like I was in 02/2007. I'm targeting a thousand keywords, and each landing page needs to target that set of thousand keywords, and that's a topic. Same thing is true for for answer engine optimization. Each page is targeting hundreds, thousands, maybe tens of thousands of questions.

因此我想把所有这些问题归类，这就引出了内容部分。那么我该如何排名？如何让我的URL获得排名，或者通常其他URL是如何决定是否排名的？它们回答了所有问题。我回答的问题越多，效果就越好。

And so I wanna group all those questions, which then brings us into content. So how would I rank? How would I get my URL to rank, or how are other usual URLs being decided whether or not they rank? They answer all the questions. The more of the questions that I answer, the better.

所以在谷歌搜索中，如果我有一个关于网站建设器的落地页，我的页面回答的子话题后续问题越多，我在谷歌搜索中出现的几率就越大。聊天也是如此。你回答的问题越多，效果就越好。如果你没有回答某个问题，那么你可能就不会出现。而如果你回答了别人没有回答的后续问题和子话题，你就更有可能出现。

So in Google Search, if I have a landing page about website builders, the more that my page answers all of the subtopic follow-up questions, the more I have to show up in Google Search. Same with chat. The more, you answer all the questions, the better. If you don't answer a question, then you're probably not going to show up. And if you answer a quest a follow-up question and subtopic that somebody else is not answering, you're gonna be more likely to show up.

接下来是第二个主题：问题研究。那么我如何知道人们正在问哪些问题？这其实相当困难，因为在搜索中，谷歌只是通过他们的广告API告诉你。他们会说这是某个关键词的搜索量。

So topics number two. The third is question research. So how do I know which questions people are asking? And that's actually pretty hard because in search, Google just tells you with their ads API. They say this is the search volume for this keyword.

谷歌提供了一个真实数据集。而ChatGPT目前还没有给我们这个，至少现在还没有。也许当他们做广告时，他们会给我们更多搜索量的访问权限，但目前没有真实数据集。那么我们如何知道人们正在问的问题呢？一种方法就是提取我的搜索词并将其转化为问题。

There's a truth set from Google. And ChatGPT is not giving us that, at least not yet. Maybe when they do ads, they'll they'll give us more access to search volume, but there's no truth set. So how do we know the questions that people are asking? One way would just be to take up my search terms and change them into questions.

比如网站建设器，你可以假设'什么是最好的网站建设器'这个问题很可能与该关键词的搜索量成比例地被询问。这是一种方法，但之前我提到过长尾更大，而且长尾中有部分在搜索中并不存在。那么我们如何知道长尾是什么样子呢？你可以使用的一个策略是：人们在销售电话、客户支持、Reddit上向你询问的所有问题是什么，挖掘所有存在于其他地方的问题。很可能这些相同的问题也在聊天中被询问，所以这是发现问题的另一种方式。

So website builder, you can assume that what's the best website builder is probably a question that's probably asked proportional to the search volume for that keyword. So that's one this but then I I mentioned that the tail is larger, and there's parts of the tail that don't exist in search. So how do we know what the tail looks like? And one strategy that you can use is what are all the questions people are asking you on your sales calls, customer support, on Reddit, mine all those questions that exist somewhere else. Probably those similar the those same questions are being asked in chat, and so that's another way to to find questions.

最后是引用优化或站外优化。再次强调，语言模型正在总结Rag。那么我如何尽可能多地显示为引用？你可以将引用分成不同的组：我的网站、视频、YouTube、Vimeo、用户生成内容、核心Reddit、一级联盟伙伴、Dotdash、二级联盟伙伴、博客。

The last is citation optimization or off-site. So, again, the LM is summarizing Rag. So how do I show up as many citations as possible? And you can break up the citations into different groups. My site, video, YouTube, Vimeo, UGC, core core Reddit, tier one affiliates, Dotdash, tier two affiliates, blogs.

所以这是将所有不同的引用进行拆分，并为每个组制定具体策略。

So it's it's it's breaking up all those different citations and having specific strategies for each group.

Dotdash到底是什么？

What is Dotdash exactly?

Dotdash Meredith是一家大型媒体集团，旗下拥有《好管家》、Allrecipes、Investopedia等品牌。它可能是史上最成功的SEO公司，同时也是被引用最多的公司之一，在语言模型领域可能也是被引用最多的。

Dotdash Meredith is a large media conglomerate with Good Housekeeping, Allrecipes, Investopedia. It's the it's probably the most successful SEO company of all time. And it's also one of the most cited, probably the most cited in LMs as well.

哇，真不知道这个。听你说着，我就在想，如果你去谷歌（无意冒犯，SEO先生），但如今去谷歌搜索，看到的都是一堆没用的东西，就像过度SEO化的内容。你觉得ChatGPT能避免这种命运吗？会不会也变成一堆过度SEO化、却不是你想要的内容？

Wow. Did not know this. As you talk, I think about like, if you go to Google no offense, mister SEO. But if you go to Google these days, it's just like a bunch of unuseful stuff, just like hyper SEO ed content. Do you think ChatGPT will be able to avoid that fate where it's just a bunch of hyper SEO ed content that is not what you actually want?

很可能。你所说的SEO问题是指大家都在互相改写彼此的内容，非专业人士互相改写。所以我用内容评分工具，它会分析谷歌的所有结果，指出其他文章都在说什么，以及你还没说的内容。然后给出如何更符合常规的建议，接着大家就开始互相改写文章。

Probably. And what you're saying with SEO is that everyone's rewriting each other's content, non experts rewriting each other's content. So I get a content scoring tool, which then looks at all the results in Google, and it says these are all the things that the other articles are are saying, and then this is what you haven't said yet. So here are recommendations for how to be more typical. And then everyone rewrites each other's article.

另一个有趣的现象是，大多数落地页根本没有效果。我们做过分析，每20个落地页中就有1个带来约85%的流量。也就是说，19/20的落地页几乎不带流量。这意味着如果想要投资回报，就需要在大量页面上花少量钱。于是就让非专业人士去改写别人的文章，因为这比雇《纽约时报》的人来写关于最佳薪酬管理软件的文章更便宜。但如果你知道哪些内容会有效，哪些落地页会成功，并精心撰写，就可以把所有资金集中在那一个页面上，这也是我们努力的方向。

And then one other interesting thing is that the majority of landing pages drive no impact. So we did an analysis where one out of 20 landing pages drive roughly 85% of all your traffic. So 19 out of 20 landing pages drive little to no traffic, which means if I wanna get if if I wanna get ROI, I need to spend a small amount of money on a large number of pages. And so then you get a nonexpert to say, rewrite this other person's article because that's cheaper than hiring someone from the New York Times to write your, you know, your your article about what's the best payroll management software. But if you knew the few things that would work, the few landing pages that would work, and you wrote them really well, then you could push all that money to that one page, which is what we try to do.

但现在的情况是大家都在互相复制内容。谷歌尚未解决这个问题，这可能是个非常难解的问题。他们最终能解决吗？很可能。

But right now, it's people rerunning each other's content. So Google has not solved that yet. That's probably a very hard problem to solve. Will they ever solve that? Probably.

ChatGPT能解决吗？很可能。我的解决方案会基于两个概念：一是信息增益——你是否说了别人没说的内容？二是你的内容有多典型？

Will ChatGPT ever solve that? Probably. How I would solve that would be one one concept would be information gain. So did you say something that somebody else didn't say? Two is how typical are you?

你是否如此典型，以至于我认为你是别人内容的重写版本？谷歌确实有EAT标准（专业性、权威性、可信度），虽然很遗憾我目前没看到它产生效果，但理论上可以。然后我可以说，嗯，这个人是专家，是认证金融顾问，应该给他们更高排名。

Are you so typical that I think that you're a rewritten version of somebody else's content? Potentially, Google has EAT expertise, authority, trustworthiness, which actually I don't see having an effect, unfortunately, but it could. And then I could say, well, this person's an expert. This person's a certified financial adviser. Rank them higher.

实际上我还没看到这种效果，但他们可以增加这方面的权重。这些都是潜在的解决方案，但我确信这个问题至今未被解决、大家都在互相重写文章的原因，可能是构建算法来解决这个问题很困难。但他们最终会解决吗？很可能。

And I'm actually not seeing that, but they could increase the weight of that. So these are all potential solutions, but I'm sure that the reason why it has not been solved yet and why everyone's rewriting each other's articles is probably hard to build an algorithm to solve that, but will they ever solve that? Probably.

你刚刚分享的这个算法或启发式方法太有趣了，因为它正好定义了什么是好内容，比如新闻通讯或播客。信息增益，是否典型？你是否为对话增添了新内容，是否独特？我认为这是制作优秀新闻通讯、播客以及世界上所有内容的绝佳策略。

This algorithm or heuristic you just shared is so interesting because it's helpful for just what is good content, say, with a newsletter or a podcast. Info gain, and is it typical? Are you adding something new to the conversation, and is this unique? I think it's a really good strategy for just producing great newsletters and podcasts and and all that all the content in the world.

是的。理想情况下，你是否做了原创研究？你是否拥有某些领域专业知识？你在内容中提到这些了吗？

Yes. And, ideally, did you do original research, and do you have some domain expertise? And did you mention that on the in the content?

这是一个极好的通用内容启发式方法，也正是你希望这些算法寻找的东西。所以目标是一致的。本节目由Great Question赞助，这是一体化用户体验研究平台，受到Brex、Canva、Intuit等团队的喜爱。我经常从交流的PM和创始人那里听到：我知道应该多和客户交流，但就是没有时间或工具。这正是Great Question要填补的空白。

This is a this is a great heuristic for just content in general, which is exactly what you want these algorithms to be looking for. So the alignment is there. This episode is brought to you by Great Question, the all in one UX research platform loved by teams at Brex, Canva, Intuit, and more. One of the most common things I hear from PMs and founders that I talk to is, I know I should be speaking to customers more, but I just don't have the time or the tools. That's exactly the gap Great fills.

Great Question让你团队中的任何人（不仅是研究人员）都能轻松招募参与者、进行访谈、发送调查、测试原型，并通过强大的视频片段分享所有内容。它提供了将客户置于产品决策中心所需的一切。只需简单提问'用户为什么选择我们而不是竞争对手？'，Great Question不仅能揭示客户已经分享的内容，还能极其轻松地即时向他们询问来自正确细分市场的新见解。想象一下。

Great Question makes it easy for anyone on your team, not just researchers, to recruit participants, run interviews, send surveys, test prototypes, and then share it all with powerful video clips. It's everything you need to put your customers at the center of your product decisions. With a prompt as simple as why did users choose us over competitors? Great question not only reveals what your customers have already shared, but it also makes it incredibly easy to ask them in the moment for fresh insights from the right segment. Picture this.

你的路线图清晰，团队目标一致，你能自信地发布产品，并且正在构建客户真正需要的东西。访问greatquestion.com/lenny即可开始。让我们给人们一个实际可行的计划来开始执行这个策略，并 essentially 在AEO方面获胜。如果有帮助，可以用我的新闻通讯作为例子。比如，我如何更频繁地出现在ChatGPT或Gemini等平台？或者如果是B2B SaaS公司，什么方式最简单就用什么。

Your road map's clear, your team's aligned, you're shipping with confidence, and you're building exactly what your customers need. Head to greatquestion.com/lenny to get started. Let's give people an actual actionable plan to start executing on this and winning essentially at AEO. If it's helpful, use my newsletter as an example. Like, how would I show up more often in ChatGPT or Gemini or whatever, or if it's a B2B SaaS company, whatever is easiest.

我们就来谈谈具体该怎么做吧。

Let's just talk about how to actually do this.

首先，我会确定想要排名的问题。我会通过搜索数据来确定这些问题——可能会参考我的付费搜索数据。比如，哪些是我的盈利关键词？竞争对手的盈利关键词又是什么？

First, I would figure out which questions I wanna rank for. How I would figure out which questions I wanna rank for, I would take my search data. I would maybe take my paid search data. Like, what are my money terms? What are my competitors' money terms?

假设我是Rippling公司，我会看Deal.com在付费搜索中竞标哪些词。然后把这些关键词转化为问题。实际上，你可以直接把关键词给ChatGPT，让它生成问题，效果相当不错。所以，获取竞争对手或你自己的付费搜索数据，输入ChatGPT，得到问题列表。这是第一步。

So if I'm rippling, what is deal.com bidding all their paid search on? Then I would transform those into questions. And, actually, you can just give those keywords to ChatGPT and say, make these into questions, and it does a pretty good job. So take your competitor's paid search data or mine or your own, Put it in Chatuchipatik, get the questions. That's step one.

第二步是跟踪这些问题。把它们加入AEO跟踪器或答案跟踪器。第三点是查看哪些来源被引用为答案，然后为每类引用来源制定策略。第三步是创建自己的落地页——分析当前显示的都是哪些类型的落地页。

Step two is then track them. So put them in a in an AEO tracker, in a in a in a answer tracker. Third thing would be who is showing up as citations, and then have a strategy for each of those different groups of citations. The third would be landing make your own landing pages. So what are the kinds of landing pages that are appearing?

是列表文章？分类页面？工具介绍页？找出出现最频繁的页面类型，然后制作你自己的同类页面。如何让你的页面获得排名？

Is it a listicle? Is it a category page? Is it an article tool page? It's like figure out what page type is seem to be showing up the most, and then you make your own page for that. How do you have your page rank?

回答所有后续问题。找出用户可能提出的所有相关问题。你可以回溯搜索数据，寻找SEO主题中关键词的群组和主题，AEO主题也是如此。然后针对站外，为每组制定不同策略。

Answer all the follow-up questions. So what are all the follow-up questions that someone might ask? You could go back to your search data and look for groups and themes of your keywords that are in your SEO topic. Same thing for for AEO topic. Then on the off-site, so different strategies for each of those groups.

根据公司情况，付费让联盟会员提及你是很有效的方法——有预算的话这很简单。比如你想成为'最佳信用卡'，付费给福布斯，你就成了最佳信用卡。这是策略一：昂贵但简单可控。YouTube/Vimeo视频策略也很容易，因为不会有社区反对说'我不喜欢你的视频'。

And I would say that depending on the company, paying an affiliate to mention, know, that's pretty easy if you have the money. So if you wanna be the best credit card, you pay Forbes, and then you're the best credit card. So that's strategy one. Expensive, easy, controllable. The YouTube Vimeo strategy is also actually pretty easy because there's no community saying, I don't like your YouTube video.

你制作一个YouTube视频。你想做什么就做什么。可能有人观看，也可能没人看，但你可以制作YouTube视频或Vimeo视频。有趣的是，特别是对于B2B领域，YouTube、Vimeo和其他视频网站上，人们制作视频的内容大多是美食、旅行、娱乐、美妆。关于AI驱动的支付处理API的视频并不多，尽管这个话题本身很有趣。

You make a YouTube video. You do whatever you want. Maybe people view it, maybe they don't, but you can make a YouTube video or or a Vimeo video. And the interesting thing with this, especially for b to b, is that YouTube, Vimeo, other video sites, the kinds of things people make videos for are food, traveling, fun, beauty. There's not that many videos about AI powered payment processing APIs as interesting as that is.

但这确实是一个赚钱的好机会。所以如果你为这些非常具体、高终身价值（LTV）、可能不太光鲜的关键词、问题和话题制作视频，这实际上是一个巨大的机会。然后是Reddit。我之前提到我们在Webflow上的做法，就是创建一个Reddit账户，说明你是谁，你在哪里工作，并给出有用的回答。这个稍微棘手一些，因为社区可能会说，我不喜欢你的答案。

But it's a a great money churn. So if you make a video for these really specific high LTV, maybe non glamorous keywords, questions, topics, that's actually a big opportunity. Then Reddit. So I mentioned with Webflow what we did, which is just make a Reddit account, say who you are, say where you work, and give a useful answer. That one is a little bit trickier because the community might say, I don't like your answer.

所以你无法保证你的评论会保留在那里，但这很容易操作。所以我会尝试这个群体。哦，还有实验设计。实验设计和观察什么方法有效。SEO和AEO都很有趣，但大部分信息和最佳实践其实并不正确。

So you can't guarantee that your comment is there, but it is easy. So I would do that that group. Oh, and then experiment design. Experiment design and seeing what works. So SEO and AEO are both interesting and that the majority of the information and best practices are are not correct.

原因在于人们不做分析。有人会说某件事，然后它就会被重复传播。每个人都会跟着说，然后它就变成了最佳实践，但从来没有人做过分析。所以你做了我刚才提到的所有事情后，应该做一个实验看看是否有效。

And the reason why is because people don't do analysis. Somebody will say something and then it will get repeated. And everyone and then it becomes best practice, and no one ever did analysis. So you you did all the stuff that I just mentioned. Do an experiment and see if it worked.

可能我说的一半方法有效，一半无效。做你自己的实验。大多数最佳实践，大多数博客文章都是不正确的。那么如何设置一个实验呢？你先明确你的问题。

Maybe half the stuff I said works, maybe half it doesn't. Do your own experiment. Most best practices, most blog posts are not correct. So how do you set up an experiment? You get your questions.

开启跟踪功能。给它几周时间。进行你的改动。设置一个测试组。设置一个对照组。

You turn tracking on. Give it a couple weeks. Make your changes. Have a test group. Have a control group.

对测试组进行干预。实施你的改动。观察图表是否上升。观察对照组是否没有变化。这样你就知道你的特定策略是否有效了。

Intervene on the test group. Make your changes. See if the chart went up. See if the control group did not. And now you know your particular strategy worked.

所以我肯定会进行实验，并且不会假设你在网上读到的东西是正确的。然后你需要一个团队。那么你的团队是谁？可能是你的SEO团队、SEO机构或SEO顾问。希望他们能够处理这些事情。

So I would definitely do experiments, and I would not assume that stuff you read online is is correct. And then you need a team. So who's your team? Probably your team is your SEO team or your SEO agency or your SEO consultant. Probably, hopefully, they can do this stuff.

然而，我认为难以招聘的是站外优化方面的工作。大多数SEO人员并不擅长制作YouTube视频和制定Reddit策略，因此你可能需要另外的人来处理。那可能是一个社区通才营销人员。所以基本上就是你的SEO团队，请现在开始做答案引擎优化。

And then however, what I think is hard to hire for is the is the off-site stuff. So most SEO people are not gonna be amazing at creating YouTube videos and Reddit strategy, so you might need a different person for that. That might be a community generalist marketing person. So it basically be your SEO team. Please now do answer engine optimization.

然后营销社区团队，请帮助我在更多引用中出现。

And then marketing community team, please help me show up in in more citations.

哇。好的。这非常有价值。感谢你分享所有这些。我想其中一些建议就像是你在免费赠送很多精彩建议。

Wow. Okay. That is incredibly valuable. Thank you for sharing all that. I imagine some of this is like like you're just giving away a lot of amazing advice for free here.

谢谢。首先，我想这其中有一个层次。单打独斗只能走这么远，所以最终就像是，好吧，我们真的需要帮助。这就是像你们这样的团队发挥作用的地方。

Thank you. First of all, I imagine there's, like, a layer. There's only so far you can go on your own, and so eventually, it's like, okay. We really need help. That's where a team like yours comes in.

让我问几个后续问题。一个是这个追踪器的概念。那么这个追踪器是什么？它可以追踪，比如说，Letty的通讯在我目标问题答案中出现的频率。

Let me ask a few questions here to follow-up. One is this tracker concept. So what is this tracker? It can track, like, how often you show up, say, Letty's newsletter shows up in answers for the questions that I'm targeting.

是的。所以有答案追踪，这有点像关键词追踪。关键词追踪会是'最佳增长播客'，你把它放入关键词追踪工具中。这样的工具有上百个，它们都差不多，你可以看到你是否排名以及排名如何。

Yeah. So there's answer tracking, which is kind of like keyword tracking. So keyword tracking would be best growth podcast, and you put that in keyword tracking tool. There's a 100 of them. They're all the same, and you see whether or not what what you rank.

也许你希望排名第一，你确实排名第一。但在答案方面，情况就非常不同了，不过也是相关的。所以如果你问同一个问题，每次都会得到不同的答案。如果你提问一次，每次运行都会有不同的答案。ChatGPT基本上是在计算所有可能给出的答案的分布，根据你提问的时间，它基本上就像一个加权随机抽样。

Maybe you rank hopefully, you rank number one. Now in answers, it's very different, but it's related. So if you ask the same question, you will have different answers each time. If you ask a quest there's there's different answers per run. And so ChatGPT is basically calculating a distribution of all the, you know, potential answers that would give and depending on when you ask it, it's basically like a weighted random sample.

所以你会得到不同的答案。你还有问题变体。所以你可以问同一个问题的不同版本，可能在某个版本中出现，在另一个版本中可能不会出现。然后还有不同的平台。有Perplexity。

And so you're gonna get different answers. You you also have question variants. So you can ask different versions of the same question, and you might show up in one, you might not show up in another. Then there's different surfaces. There's Perplexity.

有Gemini。有ChatGPT。有MedAI。这些平台都有不同的答案。所以你基本上需要在这些不同的平台上创建一个声量份额，就像一个分布。

There's Gemini. There's ChatGPT. There's MedAI. And so these surfaces have different answers. And so you essentially need to create a share of voice for across all these different things and, you know, like a distribution.

那么我出现的频率是多少？我的平均排名是多少？这就是答案追踪。那么你在哪里进行答案追踪呢？答案追踪本质上是关键词追踪的一个演变。

So how often am I showing up? What's my average rank? And that's answer tracking. So then where do you get answer tracking? An answer tracking is essentially an an evolution of keyword tracking.

所以我们有一个页面列出了60种不同的答案追踪工具。但最终就像关键词追踪一样。大致上都是相同的东西。所以从这60种中选择一个。我们有答案追踪功能。

So there's we have a page with 60 different answer tracking tools. But it's ultimately just like keyword tracking. It's all the same thing roughly. And so pick one of the 60. We have answer tracking.

我们正在开发答案追踪功能。还有59个其他选项。可能都相当不错。可能都很相似。但是选择一个吧。

We're building answer tracking. There's 59 other options. Probably all pretty good. Probably all pretty similar. But but pick one.

我的一般建议是选择最便宜且能满足你需求的工具。就像关键词追踪一样，你知道，关键词追踪没有高级版本。你要么排名第三，要么没有排名。所以选择最便宜的关键词追踪器，能满足你的需求就行，答案追踪也是如此。然后当我进行实验时，输入你的答案，追踪它们，查看随时间变化的图表，看看你的平均排名，你出现的频率，以及你的平均排名是多少。

My general suggestion is pick the one that pick the cheapest one that does what you need. Just like keyword tracking, you can only you know, there's not a premium version of keyword tracking. You rank number three or you don't. So pick the keyword tracker that is the cheapest that does what you want, same with answer tracking. And so then when I'm doing an experiment, put your answers in, track them, see a chart over time, see your average rank, how often you showing up, and what's your average rank.

然后你做出改变，希望之后能有所提升。

And then you make a change, and then hopefully you go up.

太棒了。我喜欢'声量份额'这个术语。我以前从没听过。很有道理。就像你在语言模型中出现的百分比时间。

Amazing. I love this term voice share. I never heard that before. Makes sense. The l like, percentage time you're showing up in LMs.

有没有大型语言模型？是像ChatGPT那样的吗？谷歌现在有相当于ChatGPT的产品吗？你会建议人们如何看待Gemini、Claude、Perplexity等其他模型？

Is there is there an LLM? Is it just like ChatGPP? Is, like, Google equivalent now to ChatGPP? How do you recommend people think about, say, Gemini or clutter or perplexity and others?

有趣的是，所有这些模型的基础算法都很相似。它们都在使用搜索功能，都在使用语言模型，基础算法其实都是一样的。但结果却相当不同。我们正在做一项研究。

So interestingly, there are similar foundational algorithms across all of these. Like, they're all using search. They're all using search, and they're all using LMs, which, you know, foundational algorithms are all the same. The results are actually pretty different. So we're we're doing a study.

我们发现谷歌和必应并不是那么相似的搜索引擎。我们发现ChatGPT的引用和谷歌搜索结果其实并不太相似。有趣的是，Perplexity与谷歌的相似度比与ChatGPT更高。我们研究了数千个问题，发现ChatGPT与谷歌搜索结果的引用重叠率约为35%，并不算高。而Perplexity达到了70%左右。

We're seeing that Google and Bing are not that similar search engines. We're seeing that ChatGPT citations and Google search results are actually not that similar. Perplexity is interestingly similar to more more similar to Google than than ChatGeeBT. We we did a study looking at thousands of questions and saw the citation overlap with Google search results was around 35% for ChatGeeBT and Google, so not that much. Perplexity was around 70%.

但本质上，它们都是相似的算法，只是引用和结果差异很大。所以要看哪些平台流量最大，然后跟踪这些。你可能不需要跟踪所有平台，但需要全面观察。你需要关注自己在所有这些平台上的声量份额，即你出现的频率百分比。你需要多次提问，还需要变换问题形式，才能真正了解自己出现的频率。

But, essentially, they're all similar algorithms, but with very different citations and and results. So then look at which surfaces have the most traffic and then track those. You probably don't need to track all of them, but look look across all those. But you but you you do need to look at your share of voice for the percent of time you show up across all these surfaces. You need to ask the question multiple times, and you need to ask the variance of the question to truly know how frequent you're showing up.

考虑到ChatGPT很快将达到每周10亿活跃用户，是否需要担心Claude、Gemini和Perplexity？这些平台的流量有意义吗？我知道用户很多，但专注于这些其他平台有多重要？

Considering that ChatGPT, they're gonna hit something like a billion weekly active users in the near future, like, do you need to worry about Claude and Gemini and Perplexity? Like, is the traffic there meaningful? I know it is, you know, a lot of people, but, like, how important is it to focus on those other elements?

嗯，我的回答是，我认为AOL早期是最大的搜索引擎之一，而谷歌当时还不是。所以我们可以问，在1999年或什么时候，我们是否应该只专注于AOL搜索和雅虎搜索？我们真的需要担心谷歌吗？答案是我们其实并不知道。那时还非常早期。

Well, the way that I would answer that is I believe AOL was the one of the largest search engines early on, and Google was not. And so we could ask in 1999 or whatever, should we just focus on AOL search and and Yahoo search? Do we really need to worry about Google? And the answer is we don't actually know. It's very early.

我们不知道谁会赢。我确实认为ChatGPT肯定会很大。Perplexity或Claude等其他产品会与它们竞争吗？很可能就像搜索引擎一样。我认为可能会有多个赢家，你可能需要为多个平台进行优化。

We don't know who's gonna win. I do think that ChatGPT for sure is going to be large. Will Perplexity or Claude or these others compete with them? Probably just like search. I think that there will probably be multiple winners, and probably you'll need to optimize for several.

我不认为你需要为10个平台优化，但可能大约会有三个左右的赢家，你会想要为这些平台进行优化。

I don't think that you'll need to optimize for 10, but they'll probably be around three or so that you'll wanna that that will win that you wanna optimize for.

好的。顺便说一下，我想澄清一下。我很喜欢Clot。我大致同等使用Clot和ChatGPT。我不想让人觉得ChatGPT是唯一使用的产品。

Okay. By the way, I wanna make it clear. I I love Clot. I use Clot and ChatGPT equally roughly. I didn't wanna make it sound like ChatGPT is the only product people use.

好的。这个策略如何根据你所在的公司类型而变化？比如说你是B2B SaaS公司还是消费产品公司。这七个步骤中有什么会显著改变吗？

Okay. How does this strategy change depending on the kind of company you are? Say you're a b to b SaaS company or consumer product. Does anything in these seven steps change significantly?

以B2B为例。首先，被提及的引用将会非常不同。所以引用优化会有很大差异。

Let's take b two b for example. First thing is that the citations that are being mentioned are gonna be quite different. So citation optimization will vary quite a bit.

只是想澄清你刚才说的，你说引用策略不同是什么意思？

Just to clarify what you just said, what do you mean when you say citation strategy is different?

意思是，B2B与市场平台出现的引文是不同类型的引文。嗯。所以对于B2B来说，可能是像Tech Radar这样的网站，当我提问时它出现得非常多。我从未读过Tech Radar，但不知为何它总是出现。我相信它很棒。

Meaning, the citations that show up for b to b versus marketplaces are are different kinds of citations. Mhmm. So for b to b, it might be, like, Tech Radar shows up a ton when I ask questions. I've never read Tech Radar, but for some reason, it shows up all the time. I'm I'm sure it's great.

但不管什么原因，Tech Radar在B2B领域出现得非常频繁。在电商领域就不会这样。会是《Glamour》和《Cosmopolitan》这类杂志。对于市场平台，则是Eater、Yelp、TripAdvisor这样的地方。所以出现的引文类型是不同的。

But Tech Radar is showing up a ton for for b to b for whatever reason. In commerce, it's not gonna be that. It's gonna be glamor and cosmopolitan. For marketplaces, it'll be Eater and, you know, Yelp, TripAdvisor, places like that. So so the kinds of citations that show up are different.

我谈论的大部分内容都是针对B2B特有的，与电商不同的东西。所以对于大多数B2B问题，答案是不可点击的。没有什么可以点击的。因此，如果你真想衡量影响，不能只看最后接触的推荐流量。你必须通过跟踪看是否出现在答案中，并且还需要在转化后询问用户是如何听说我们的，才能真正了解影响。

Most of the stuff that I've been talking about is specific to b two b, stuff that's different for commerce. So for most b to b questions, the answers are not clickable. There's nothing to click on. And so if you actually wanna measure the impact, you cannot just look at last touch referral traffic. You have to see whether or not you showed up in the answer with tracking, and then you also need to ask the user, how did you hear about us post conversion to actually know the impact.

B2B的跟踪更难。此外，对于B2B，你可能在50次接触点后才决定使用哪款薪酬管理软件。对于一个品牌来说，不会是你刚搜索某样东西就突然花10万美元购买薪酬管理软件。所以这就是B2B。电商则不同。

It's it's harder to track for for b two b. Also, for b two b, you're probably deciding which payroll management software to use after 50 touch points. With a brand, it's not gonna be you just search for something you suddenly spend a $100,000 on payroll management software. So that's b two b. Commerce is different.

所以电商现在实际上有更多可点击的卡片，就像你在Google中看到的那样。所以如果你问什么是最好的公寓电视，会有实际的可购物卡片。这些可购物卡片展示了多个卖家。这些卖家有丰富的摘要。Schema很重要。

So commerce actually now has more clickable cards like you would in a Google. So if you ask what's the best TV for for apartments, there are actual shoppable cards. Those shoppable cards are showing multiple sellers. Those sellers have rich snippets. Schema is important.

浏览量很重要，所以实际上相当不同。你可以查看最后接触的推荐流量来很好地了解电商获得的转化数量。餐厅、酒店和本地市场平台类似，情况也相似。然后我会说早期阶段也不同。所以我之前提到，早期阶段，我的建议是根本不要做SEO。

The number of views are important, so it's actually quite different. You can look at last touch referral traffic to get a good sense about the number of conversions that you're getting for commerce. Similar with with restaurants and hotels and local marketplaces, similar there. And then I would say early stage is also different. So I mentioned earlier, early stage, my recommendation is don't do SEO at all.

对于答案引擎优化，一定要做AEO，并且只做引文优化和长尾词。不要做任何中期的SEO工作。只需被引用并回答非常具体的问题。

For for answer answer engine optimization, definitely do AEO and only do citation optimization and long tail. Don't do any of the mid SEO stuff. Just get cited and answer really specific questions.

这太有趣了，这么多内容最终只是以那个小标签/药丸的形式呈现在答案中，因为现在想想确实很明显。这是用户通过LLM访问你网站的唯一方式，就像点击那个链接一样。好吧，让我去读这篇文章。

It's so interesting that so much of this is just, like, having showing up as that little tag slash pill in the answer because, like, it's obvious now that I think about it. That's the only way someone will get to your site from an LLM. It's just like clicking that. Okay. Let me go read this article.

是的。但他们会做的是：打开一个新标签页，输入品牌名称，然后去谷歌搜索，再点击你的域名。你会误以为这是品牌搜索带来的流量，其实不是。或者他们会打开新标签页，直接输入你的域名访问，而你会错误地认为这是直接流量。

Yes. But what they will do is they will open a new tab, and they will type in the brand name, and they will go to Google, and then they'll click on your domain, and you will think that it was branded Google search when it wasn't. Or they'll open up a new tab, and they will type in your domain, and they'll go directly to your domain. And you'll falsely think that it was direct traffic.

回到你一开始提出的问题。对我的新闻通讯来说，它们吸收了所有这些内容（我都不知道具体有多少），然后给我带来一定比例的流量。你有没有什么感觉——这样好吗？如果你在运营我的新闻通讯，你会鼓励所有这些LLM吸收我的内容然后说'哦，是的，如果你想了解更多，可以查看Morlady的新闻通讯'吗？

What is your coming back to a question you kind of raised at the beginning. So for my newsletter, the fact that they're sucking up all this content, like, don't even know how much, and sending me some percent of traffic. Do have any, I don't know, just sense of, like, is this good? Is this what I if you were running my newsletter, would you encourage all these LMPs to suck up my stuff and then be like, oh, yeah. You could check it out, Morlady's newsletter, if you want.

是的。我会给出和Brian Balfour在你上一期节目中相同的答案：你是否参与这个游戏不是你能选择的。无论你愿不愿意，你都已经在游戏中了，所以不如尽量让自己出现。如果你直接说不要查看我的任何数据，那么你就无法出现，而你的竞争对手会。现在你能做的是说：我不希望你用我的数据训练模型。

Yes. And I would get the same answer that Brian Balfour gave on your previous episode on this, which is that it's not your choice whether to play the game. You are playing the game whether you want to or not, so you might as well try to show up. If if you just say don't look at any of my data, then you cannot show up, and your competitors will. Now, what you can do is you can say, I don't want you to train on my data.

你可以索引我的网站，但请不要用我的数据训练。他们有不同的用户代理和不同的机器人来处理这个。你可以直接说——我们正在开发一个Webflow应用来阻止训练但不阻止索引。或者你可以在robots.txt中声明：训练机器人不允许，索引机器人允许。

So you can index my site, but please don't train on my data. And they have different user agents for that and different bots. So you can just say, and we're building a a Webflow app to block training, but not indexation. Or you can just put it in your robots.txt. This training bot not allowed index bot, you are allowed.

如果你担心这个问题，我建议这样做。我认为很多人都会这么做。但说完全不能索引我的网站，这在我看来没有意义。

If you're concerned about that, I I I would suggest that. And I think probably a lot of people will do that. But saying you can't index my set at all, that doesn't make sense to me.

说得太好了。因为我不知道在这个具体领域是否有竞争对手，但基本上，他们会代替我出现，然后我就失去了所有这些流量。是的，说得太好了。好的。

Such a good point. Because my I don't I don't know if I have competitors in this exact space, but basically, they would show up instead, and then I lose all that traffic. Yes. Such a good point. Okay.

让我回到你刚才分享的步骤，看看是否有值得进一步深入探讨的地方。这基本上是如何在LM响应中更成功地出现。第一步是确定你想要排名的问题，你可以通过查看竞争对手的广告、付费广告等内容来实现。就像查看ChatGPT或Claude中经常被询问的术语，将这些转化为人们会用来查找这些术语的问题，然后设置一个追踪器来了解你目前的表现，比如你出现的频率如何。追踪器有很多种。

Let me come back to the steps you shared just to see if there's something here that's worth diving into a little further. So this is essentially how to be more successful showing up in LM responses. One is figure out what questions you want to rank for, and you could do this by looking at what your competitors are, advertising and their paid ads and things like that. Just like look at the terms asked almost ChatGPT or Claude, turn these into questions people would ask to find these terms, then set up a tracker to see just how you re doing today, like how often are you showing up. There s a million trackers.

我们有一个链接可以查看这些内容。然后你查看今天谁在出现，他们今天被引导到哪里，利用这些信息来创建登陆页面，更好地回答那些问题。并且你明确指出，不仅要回答主要问题，还要回答后续问题，这一点非常重要。然后是站外内容。所以要进入像Emdash、YouTube、Reddit、Quora这样的联盟，听起来是核心，然后运行一个实验。

You have a link we link to to check these out. Then you look at who is showing up today, where are they being taken today, use that to inform landing pages that you create to answer those questions better. And it's an you you make it very clear that it's very important not to just answer that main question, but also follow-up questions. Then there's off-site stuff. So get into affiliates like Emdash, YouTube, Reddit, Quora, sounds like, or the core, and then run an experiment.

所以你查看这个追踪器，然后你如何...让我实际问一下。下一步是组建一个团队，但回到这一步，你如何设置一个不仅仅是前后对比的实验？你如何做一个对照组的情况？

So you look at this tracker, and then you how let me actually ask this. And the next step is just set up a team, but just to come back to this step, how do you set up an experiment that isn't just like a before after? How do you do a control group situation?

是的。我会做的是，我会选取100个不同的问题。其中一半，我会进行干预。另一半，我不会。或者我们说是200个问题吧。

Yeah. So what I would do is I would take a 100 different questions. Half of them, I will intervene. Half of them, I won't. Or let's say let's take 200 questions.

所以100个问题，我什么都不会做。那就是我的对照组。我们看到即使什么都不做，答案也有相当多的变化。所以你肯定需要一个对照组。而且，我们也看到人们越来越多地使用LMs，LM流量正在上升。

So a 100 of the questions, I'm not gonna do anything. So that's my control group. And we are seeing a fair amount of variance in answers just without doing anything at all. So you definitely want a control group. And, also, we're seeing people, you know, people are using LMs more, and LM traffic is going up.

所以你肯定需要控制，尤其是在即时优化中。对照组就是完全不动它。保持原样。那就是对照组。测试组会是，我现在要在Reddit帖子上评论。

So you definitely need to control, especially in instant optimization. So control group is don't touch it at all. Leave it leave it as it is. That's a control group. Test group would be, I'm going to now comment on Reddit threads.

所以让我们测试那个。或者我现在要制作一个YouTube/Vimeo视频，或者我现在要付费给福布斯顾问说我是最好的信用卡。也许将这些分成几个不同的组。追踪它们。有几周的前期，几周的后期，与对照组比较，然后那些在对照组没有上升时上升的内容起作用了，而那些没有上升的则没有。

So let's test that. Or I'm now going to make a a YouTube Vimeo video, or I'm now going to pay Forbes advisor to say that I'm the best credit card. Maybe break those up into a few different buckets. Track them. Have a couple weeks before, couple weeks after, compare against control group, and then and then the stuff that went up when the control group did not worked, and the stuff that didn't did not.

然后进行复现。所以可复现性非常重要。我的背景是学术研究，经常会出现无法复现的研究。因此，要让学术界真正接受某项研究，它必须是可复现的。这意味着有多人进行了这项研究，并且能够反复复现该结果。

And then reproduce it. So reproducibility is very important. And my background's in academic research, and it's common to do a study that cannot be reproduced. And so for something to truly be accepted with a with an academia, needs to be reproducible. Meaning multiple people have done this study and reproduce that thing over and over again.

特别是在SEO领域，经常会出现某些变化，你以为是由某个因素引起的，但实际上并不是。而你却一直认为那个方法有效。所以可复现性非常重要。要尝试多次进行该研究。尝试获取其他人的研究结果。

And especially in SEO, it's common for something to change, and you think that it was this thing that caused it, and it's actually not. And you just assume forever that that works. So reproducibility is very important. Try to do that study multiple times. Try to get studies from other people.

如果，你知道，如果这个方法有效10次，那么它很可能确实有效。这就回到了浪费的问题。在SEO中大部分工作都是浪费的。在AEO中大部分工作也是浪费的。那么你怎么知道哪些不是浪费的呢？

And if, you know, if it works 10 times, then it probably works. And the stuff that and this comes back to the waste problem. Most work is wasted in SEO. Most work is wasted in AEO. So how do you know what's not wasted?

你要做实验。不要假设你在网上读到的东西都是真的。你要自己做实验，然后多次复现，持续做有效的事情，不做无效的事情。

You do an experiment. You don't assume that what you read online is true. You do your own experiment, and then you reproduce it multiple times and keep doing the stuff that works and don't do the stuff that doesn't.

在AEO中获胜感觉是如此重要。回到这个想法，人们来到ChatGPT、Collad Gemini寻找答案。如果你就是那个答案，我觉得这可能直接决定你公司的成败。感觉这比SEO更重要，就是要做好这件事。

It feels like such a big deal to win at a AEO. Just coming back to this idea that, like, people are coming to ChatGPT, Collad Gemini, looking for an answer. If you're that answer, I feel like that could just make or break your company. It feels like even more important than SEO, just getting this right.

我想说的是，我想要获得尽可能多的转化，这个渠道有多大？这个渠道没有搜索那么大。搜索肯定更大，但它现在确实是一个相当大的渠道。Webflow公司有8%的注册来自语言模型。它现在已经成为你的顶级渠道之一。

I would say that where I wanna get the most conversions possible, how big is the channel? The channel is not as big as search. The search is definitely larger, but it's it's it is a substantial channel now. And Webflow, they get 8% of their sign ups from from LMs. You it's now your one of your top channels.

所以这个渠道很大。虽然不是最大的渠道，也不是第一渠道。付费广告可能是第一渠道，但它绝对是一个相当大的渠道，值得进行优化。

So it's large. It's not the largest channel. It's not the number one channel. Paid is probably the number one channel, but it's definitely a substantially large channel and one worth optimizing for.

正如你所说，可能会随着时间的推移而增长。是的。好的。让我稍微放大视野，问你这个问题。你认为在AI、SEO和AEO方面，有哪些最令人惊讶或未被充分讨论的话题是我们还没有谈到的？

And as you said, probably growing over time. Yes. Okay. Let me zoom out a little bit, and let me just ask you this. What do you think are maybe the most surprising or under discussed topics when it comes to AI and SEO and AEO that we haven't already talked about?

首先是关于AI和AEO存在大量错误信息，而且相当极端。错误信息与正确信息的比例异常地高，相当显著。举个例子，每两年就会有新闻报道说谷歌搜索即将消亡或正在消亡，因为有新事物出现。现在这种情况正在发生，与AI概览和AEO有关。谷歌要垮了，但这并不真实。

The first thing is that there's significant misinformation on on AI and on AEO, and and it's pretty extreme. It's unusually the percent of misinformation to correct information is is pretty substantial. So one example is every two years, there's news articles about how Google searches is going to die or it is dying because there's a new thing. So that's happening right now with with AI overviews and with AEO. Google's going down, which is not true.

在此之前是TikTok搜索。所以现在每个人都在用TikTok。Z世代在用TikTok。他们再也不会用SEO了。SEO要完蛋了。

Before that, it was TikTok search. So everyone is using TikTok now. Gen z is using TikTok. They're never gonna use SEO. SEO is gonna be dead.

所以你确实需要关注TikTok搜索，这并非错误。但它并不是不真实，只是它并没有从谷歌那里夺走份额。它只是一个新的平台。再之前是Instagram，再之前是Facebook，还有YouTube。

And so you really need to focus on TikTok search, which is not false. But it's it's it's not untrue. It's but it's not taking share away from Google. It's just a new surface. And then before that, it was Instagram, and then before that, it was Facebook, and it was YouTube.

人们确实会在Instagram、TikTok、YouTube上进行搜索和发现。但这并不会减少谷歌搜索的份额。它是在谷歌搜索之上增加的。这些都是新渠道。所以谷歌的份额保持不变。

And people do search and discover on Instagram, TikTok, YouTube. But it doesn't take away from Google search. It adds on top of it. These are all new channels. So Google's slice of the pie stays the same.

整个市场变大了。所以关于谷歌衰退的错误信息。谷歌并没有衰退。谷歌最近发布了一些东西。他们的搜索副总裁明确表示，我查看了我们发送给发布商的流量，并没有下降。

The pie gets bigger. And so misinformation about Google going down. Google is not going down. Google published something recently. Their VP of search explicitly said, I looked at our the traffic that we're sending to publishers, and it is not down.

甚至还略有上升。所以谷歌搜索正在衰退的说法是不真实的，而大部分相关新闻信息都在说它正在衰退。这是第一个令人惊讶的事情。第二个令人惊讶的事情是工具。我从未见过一个渠道里有这些极其昂贵的工具，却基本上只做普通任务。

It's up slightly. So it is not true that Google Search is going down, and most of the news information about that is saying that it's going down. So that's the first surprising thing. The second surprising thing is tooling. And I've never seen a channel where these extremely expensive tools that essentially do commodity tasks.

想象一下，如果我说要收你5万美元做关键词追踪。你肯定会说，这太荒谬了。就是关键词追踪嘛，我一天就能写出来。没人会这么做的。

So imagine if I said, I'm going to charge you $50,000 for keyword tracking. You would say, well, of course, that's absurd. It's keyword tracking. I could write this in a day. No one would do that.

但对于答案引擎来说，它很神秘，人们不太清楚它是如何运作的。而且增长曲线的斜率如此显著，我看到人们在本质上就是关键词追踪或商品化的东西上投入巨资。这是第二点。第三点是渠道的增长曲线。我们一年前做过一个Reforge AEO网络研讨会。

But for answer engines, it's mysterious, and people don't really know how it's working. And also the slope of the growth curve is so significant that I'm seeing people spend huge amounts of money on what are essentially, you know, keyword tracking or commodities. That's the second thing. The third thing is the the growth curve of the channel. And we did a a Reforge AEO webinar a year ago.

当时很兴奋，但随后就消退了，人们对它的兴趣非常小。这是在六月份。然后人们就不太在意了。他们在理智上被吸引，但并不关心，因为他们没有看到实际影响。所以从七月到一月基本上没什么兴趣。

And it there was excitement and then it died, and there was very little excitement about it. This was in June. And then people didn't really care. They were intrigued intellectually by it, but they didn't care because they didn't see the impact from that. So there's essentially very little interest between July and January.

然后突然在一月份，它就飙升了。你知道，如果是Chattypitty发布，人们会很感兴趣，但对增长人员来说就没那么有趣了。然后在六月份有个小高峰，接着就像这样，这通常不是新渠道的典型表现。所以曲线的斜率异常陡峭，曲线的形状也非常不寻常。最后一点是很多人确实认为SEO和AEO是不同的，但实际上它们并没有区别。

And then suddenly in January, it's just skyrocketing. So, you know, if it's it's Chattypitty launches, people are very interested, and then it's not not that interesting for growth people. And then there's this little spike in June, and then it's like this, which is usually not what you see with a with a new channel. So the slope of the curve is is unusually steep, and the shape of the curve is is is also very unusual. The the last is that a lot of people do think that SEO and AEO are different, and and they're not different.

我认为部分原因可能是因为说'这是一个全新渠道'听起来很棒。它完全不同，我是专家，我有工具卖给你。你知道，它完全独特，所有其他工具都不相关。实际上，它们之间有很多重叠之处。区别在于引文优化。

I think probably part of that is because it sounds great to say that there's this new channel. It's completely different, and I'm an expert, and I have a tool to sell you. And, you know, it's totally unique, and, you know, all these other tools are not not not relevant. In reality, it's actually there's there's quite a bit of overlap. There is the difference of the citation optimization.

头部不同，尾部也不同，但核心技术是相当相似的。这些可能是最令人惊讶的事情。

The head is different, and the tail is different, but the core the core technology is is pretty similar. So those are probably the most most surprising things.

关于一月份成为转折点这部分，你提到是因为参考文献开始更 prominently 显示。这是那个重大变化吗？

This piece about January being the inflection point, you mentioned that it was because references started showing up more prominently. Is that the big change?

我认为是人们对语言模型的采用率提高了，所以实际上它只是在增长更多。然后是点击率，我看到你现在看到了实际点击量的大幅增加。可能以前即使你展示了一个答案，也得不到任何点击。所以答案的点击率提高了，特别是对于商业、本地和酒店这类内容，因为它们有这些丰富的模块，你可以点击东西并跳转到某个地方，这在以前是不存在的。这一点，再加上我认为人们只是更多地使用语言模型了。

I think it's increase of adoption of LMs by people, so it's just actually growing more. And then the clickability, and I am seeing you are seeing now this large increase of actual clicks. Probably before you got no clicks, even if you showed up an answer. So the clickability of the answer has increased, especially for things like commerce and local and hotels because they have these rich modules where you can click on stuff and go somewhere, which was not true before. That, and I think people are just using LMs more.

Ethan，让我说，我从这次对话中学到了很多。多么有趣的事情。我能清楚地看出你有多热爱这些东西，你钻研得多么深入和极客，和如此深入且对这些事情如此了解的人交谈真是有趣。所以谢谢你与我们分享这一切。我想稍微换个方向。

Ethan, let me just say, I'm learning so much from this conversation. What a fun thing. I could see it's just, like, clear how much you love this stuff, and it's just how nerdy and deep you get into it, and it's just fun to talk to someone that's so deep and knowledgeable about all these things. So thank you for sharing all this with us. I wanna go in a slightly different direction.

有一个完整的AI内容世界，人们用AI生成内容，生成落地页，就像，哦天哪，SEO永远不会，就像，只是生成所有这些东西，AI会让所有这些东西变得更容易。你们做了一个很大的研究，关于它是如何工作的，用AI生成内容是否是个好主意。你能谈谈你从中学到了什么，以及人们应该如何思考在生成内容时使用AI吗？

There's this whole world of AI content, people generating content with AI, generating landing pages, just like, oh my god, SEO is never going to, just like, just generate all this stuff, AI is going to make all this stuff easier. You guys did a really big study on how that works, whether it's a good idea to generate content with AI. Can you just talk about what you learned from that and how people should think about AI in generating content?

是的。我记得当ChatGPT推出时，Brian Balfour在LinkedIn上发帖，你们认为ChatGPT和AI会发生什么？我立即的反应是垃圾邮件。所以就是大量的垃圾邮件，特别是SEO垃圾邮件。然后围绕AI生成内容出现了一个完整的行业，我立即知道它不会奏效。

Yes. So I remember when ChatGPT launched and Brian Balfour posted on LinkedIn, what do you people think that is gonna happen from ChatGPT and AI? And my my immediate response is spam. So just lots and lots of spam, especially SEO spam. And then there was a whole industry around AI generated content, and and I knew immediately that it wouldn't work.

我为什么知道它不会奏效？当我说AI生成内容时，我指的是没有人类参与的自动化内容。所以我认为内容的未来显然是AI辅助的。就像，显然，你和我将使用AI来帮助我们写作。所以不是完全没有AI，但也不是100%由AI生成。我立即知道它不会奏效。

And the reason why I knew it wouldn't work and when I say AI generated content, I mean, automated content with no human in the loop. So I think that the future of content is clearly AI assisted. Like, clearly, you and I will be using AI to help us write. So it's not no AI at all, but it's not 100% generated with AI. I immediately knew that it wouldn't work.

我为什么知道？我知道是因为我在2007年2月创建过垃圾内容，我知道谷歌对此做了什么以及如何做的，我知道同样的事情将会发生。所以我在2007年做的是，我和所有其他购物比较网站的人互相抓取彼此的内容、评论，切碎内容，抓取了1亿个搜索页面、片段，而且效果非常好。然后它停止工作了，然后所有这些公司都消失了。我认为这正是AI生成内容将会发生的情况。

Why did I know that? I knew that because I created spam in 02/2007, and I knew what that what Google did about it and how, and I knew the exact same thing was gonna happen. So what I did in 2007 is I and all the other shopping comparison people comparison people scraped all each other's content, reviews, chopped it up, scraped content, 100,000,000 search pages, snippets, and and it worked really well. And then it stopped working, and then all those companies disappeared. And I think that that was exactly what's gonna happen with AI generated content.

所以从一开始，我就没有专注于AI生成内容。很多人有。但我不知道。所以也许它确实有效。有很多关于它有效的案例研究。

And so from the beginning, I've I've not focused on AI generated content. Many people have. And we but I don't know. So maybe it does work. There's lots of case studies about it working.

那么我们就来做这项研究。我们进行了一项分析。我们收集了数千次搜索和数千个问题，分别来自Google和ChatGPT，然后将这些搜索输入Google搜索，将这些问题输入ChatGPT。接着我们查看了引用来源和Google搜索结果，然后使用了AI检测器进行分析。

So let's do the study. Let's do an analysis. So we took we looked at both Google and at ChatGPT where we took thousands of searches and thousands of questions, and we put those searches into Google Search. We put those questions into chat and the ChatGPT, and then we looked at the citations or the Google search results. Then we looked at an AI detector.

我们使用了Surfer SEO的AI检测器。当我告诉别人这个时，他们会说AI是无法检测的。于是我们评估了这个AI检测器的有效性和准确性。我们通过生成数千篇AI生成的文章来测试，结果非常有预测性。然后我们又查看了真实文章。

So we used surfer surfer SEO's AI detector. Now when I tell people this, they say, well, you can't detect AI. So then we evaluated the the efficacy and the accuracy of the AI detector. So we did that by generating thousands of AI generated articles, and it was very predictive. And then we looked at real articles.

我们通过两种不同方式进行了测试。一种是我们撰写真实文章，另一种是我们从过去五年的Common Crawl中随机抽取了10万个URL样本。然后我们查看了ChatGPT发布前的AI检测结果，这些内容必然不是人类创作的，误报率大约在8%左右。所以基本上，这个AI检测器非常准确。

We did that two different ways. One way is we write real articles, and the other is we took a random sample of a 100,000 URLs from Common Crawl over the last five years. And then we looked at the AI detector before ChatGPT was launched. So it necessarily was content not created by a human, and then the false positive rate was around 8%. So basically, the AI detector is very accurate.

我们基于这个结果对内容进行了分析。我们发现Google搜索和ChatGPT中大约10%到12%的内容是AI生成的，90%不是。我们还进行了相关性分析，显示了完全相同的结果。所以我们基本上做了一个非常严谨的研究，表明AI生成的内容行不通。

So we took that. Then we ran on the content. So then what we saw was was around 10 to 12% of content in Google search and in ChatGPT are AI generated, 90% or not. And we ran a correlation analysis showing the exact same thing. So we essentially did a very rigorous study showing that AI content doesn't does not work.

经过人工编辑的AI辅助内容很棒。我们有时会这样做，其他人也会这样做。这显然是内容的未来。这种方式确实有效而且应该有效，这是很好的。

AI assisted content edited is great. We we we do that sometimes. Other people do that. That is clearly the future of content. So that that does work and should work, and that's good.

但纯粹100%由AI生成的内容行不通。然后我们做的第二件事是发现了一个意外结果：互联网上AI生成的内容比人类生成的内容更多。回到Common Crawl的研究，我们查看了过去五年中10万个不同的URL，可以看到这条曲线显示AI生成的内容现在超过了人类创作。所以互联网上AI生成的内容比人类生成的更多，这有点令人不安。假设AI生成的内容确实有效的话。

But purely 100% AI generated does not work. So then the second thing that we did was we found that this was unexpected, but we found that there's more AI generated content on the Internet than human generated content. So back to the common crawl study, we we looked at a 100,000 different URLs over the past five years, and then you can see this curve where AI generated is now higher than human created. So there's more AI generated content on the Internet than human generated content, which is kind of disturbing. So then let's say that AI generated content did work.

如果AI生成的内容有效，那么每个人都会这么做。就像2007年的购物比价网站一样，如果我可以抓取内容，为什么还要付钱请人写？我直接从你那里抓取内容然后重新组合。那么每个人都会这样做，然后从大多数内容是AI生成的变成几乎所有内容都是AI生成的。

If AI generated content worked, then everyone would do it. Just like in 2,007 shopping comparison sites, if I can scrape my content, why would I pay anyone to write it? I'll just scrape it from you, and I'll chop it up. So then everyone will do that. And then it will go from most content is AI generated to almost all of the content is AI generated.

那么接下来会发生的是，如果这个方案有效，谷歌就变成了ChatGPT回答的搜索引擎。如果谷歌只是ChatGPT回答的搜索引擎，那它就没有存在的必要了。直接去ChatGPT就行了，这完全就是2007年2月发生的情况重演。谷歌当时说，我看到所有这些购物比价搜索引擎出现在我的搜索结果中。所以我本质上成了搜索引擎的搜索引擎。

Then what will happen, if that works, is that Google now becomes a search engine for ChatGPT responses. So if Google is a search engine for ChatGPT responses, there's no reason for Google to exist. Just go to ChatGPT, which is the exact same thing that happened in 02/2007. Google said, I see all these shopping comparison search engines showing up in my search results. So I am essentially a search engine for search engines.

我应该在我的搜索结果中直接显示电视产品。我不应该显示其他垂直搜索引擎。所以我要把它们清除掉，直接展示产品本身。ChatGPT的情况也会完全一样。对于ChatGPT来说，假设它在引用中对自己的衍生内容进行排名。

I should be showing the TV in my results. I shouldn't be showing others vertical search engines. So I'm gonna get rid of them, and I'm just gonna go straight to the product. Same thing will be we true for ChatGPT. Now for ChatGPT, what let's say that ChatGPT ranks its own derivatives in its citations.

这样你就会陷入衍生内容的无限循环。我去ChatGPT，让它生成10篇文章。我把这些文章放入引用中，然后让它总结这些衍生出来的引用。接着我不断对衍生内容进行再衍生，你就陷入了衍生内容的无限循环。

So then you have this infinite loop of derivatives. So I go to chat GBT. I say generate 10 articles. I put those articles into the citations, and then I say summarize these citations that were derivative. And then I keep on doing derivatives of derivatives, and you have an infinite loop of derivatives.

现在AI正在自我总结。有一篇关于这个问题的论文叫做模型崩溃。所以，再次强调，有核心算法，还有RAG部分。关于核心算法，一个研究小组做了项研究展示了模型崩溃，即如果你将AI衍生内容输入模型，并用你自己的衍生内容进行训练，训练核心模型的衍生内容。结果出现了一系列问题：幻觉现象、系统很快崩溃。

And now AI is summarizing itself. We've there's a paper about this called model collapse. So, again, there's the core algorithm, and then there's the rag piece. So the core algorithm, a group did a study showing model collapse, which was what if you feed in AI derivatives into the model and train on your own derivatives, train the core model derivatives. And then what happened was you had all these problems, hallucinations, things break very quickly.

好的。于是我们做了一个研究，探讨如果将衍生内容输入到RAG组件中会发生什么。先生成10个衍生内容，放入排名中，进行总结，然后再生成10个，接着总结我的总结，形成一个衍生内容的无限循环。结果如何呢？结果就是出现了群体智慧。

Okay. So then we did a study on what if you feed derivatives into the rag piece. So generate 10 derivatives, put that in rank, summarize that, and then generate 10 more, and then summarize my summarizations, infinite loop of derivatives. What happens? And so what happens is there's a there's a wisdom of the crowd.

这是在总结许多人的观点。所以如果你问一个问题，比如什么口味的冰淇淋最好？并没有一个标准答案。而是有成千上万种观点。我在总结这许许多多的观点，这就是群体智慧。

The is summarizing the opinion of many people. So if you ask a question like, what's the best flavor of ice cream? There's not one answer. There's thousands of opinions. So they all I'm summarizing these many, many opinions, and there's wisdom of the crowd.

群体智慧基本上是说，如果你取一大群人的平均值，他们的平均回答会比群体中最好的单个个体更优。因此拥有更多样化的观点会更好，这就是群体智慧。那么对于无限循环的衍生内容会发生什么呢？你基本上会收敛到一个观点上。所以如果你问，什么口味的冰淇淋最好？

The wisdom of the crowd basically says, if you take the average of a large group of people, their average response will be better than the best single individual in the group. And so it's better to have more diversity of opinions, wisdom of the crowd. So what happens to the to the infinite loop of derivatives? You essentially converge on one opinion. So if you ask, what's the best flavor of ice cream?

它最终会说这是香草味的，只有香草味。没有其他口味的冰淇淋。这是一个简单的例子。但如果你将导数的导数输入模型，你基本上会采纳群体的智慧，而这种智慧会缩小，最终对所有事情都只有一个观点，这真的很糟糕。所以这就是如果AI内容100%由无辅助AI生成会发生的情况。

It will eventually say it's vanilla, it's only vanilla. And there's no other flavor of ice cream. And so that's a simple example. But if you feed in derivatives of derivatives into the model, you will basically take the wisdom of the crowd, and that will shrink, and you'll have a single opinion on everything, which is really bad. So that's what happens if AI content 100% unassisted AI content works.

我担心如果存在一个所有东西都在AI上训练的世界，AI又在AI上训练并生成AI，就像没有任何东西是可信的。我觉得有趣的是这些激励机制在多大程度上推动了这一切。比如，如果ChatGPT发现这很有价值，这就是人们会做的事情，然后就有点失控了。所以只是有一些团队在阻止这种情况发生。你认为这会如何演变？

I'm afraid if there's a world where everything is trained on AI, and AI is trained on AI and generating AI, and just like nothing is trusted. And I love how it's interesting just how much of these incentives are driving this. Like, if ChatGPT was finding this valuable, this is what people do and then just kinda goes off the rails. So there's just, like, some team there that is keeping this from happening. How do you think this evolves?

比如，如果你是他们，未来几年你会怎么做来保持高质量，而不是驱动这些不良激励机制？

Like, if you were them, what would you do over the next few years to keep things high quality and not drive these perverse incentives?

所以我会识别可能的不良激励机制，广告生成内容就是其中之一。第二件事是我认为语言模型和搜索将会融合。你在Google搜索中看到这一点，他们有了LM AI概览功能。你在语言模型中看到这一点，他们整合了地图和购物轮播，正在向搜索融合。所以我认为会融合成一个单一的体验。

So I would identify what the perverse incentives might be, and ad generated content is one of them. The second thing is I think that LMs and search are gonna converge. And so you're seeing that with Google Search where they're having LM AI overview. You're seeing that with LMs where they're incorporating maps and shopping carousels, and it's converging on search. So think it'll converge on a single experience.

这是第一件事。弄清楚2007年的Ethan会怎么做来制造垃圾内容，并确保他不会那样做。比如AI生成内容或抓取内容。这将是第二件事。第三件事是语言模型还有许多其他有趣的功能和用例可以做得很好。

So that's the first thing. Figure out what 2,007 Ethan would do to to create spam and and make sure that he doesn't do that. Like, AI generated content or or scrape content. That'll be the second thing. And the third thing is there's all these other interesting features that use cases that LMs can be great for.

所以语言模型可以很好地记住你曾经问过的所有事情。它可以专门为Lenny个性化定制内容。我认为最终会出现的一个有趣用例是，我说'计划一次去旧金山的旅行'，然后无需任何干预就为你做出决定。我有一个很棒的助理叫Jen。我说，Jen，我要去迈阿密。

So LMs could be great for remembering everything that you've ever asked. It could be good for personalizing stuff specifically to Lenny. One interesting use case that I think will eventually come would be, I say, plan a trip to San Francisco, and decisions are made for you without any intervention. I have this wonderful EA named Jen. And I say, Jen, I'm going to Miami.

请为我安排好一切。然后她为我安排好一切。她了解我。她知道我的偏好。她知道我想要海景房，还想要有音乐的餐厅。

Please just do everything for me. And she does everything for me. She she knows me. She knows my preferences. She knows that I want a ocean view, and I want a restaurant with music.

她完成所有这一切，而我无需干预。AI最终基本上能做到这一点。它之所以能做到，是因为它会深度理解你。它会记住关于你的一切。它会拥有上下文。

She does all that, and I don't have to intervene. AI can essentially do that eventually. And that would do that because it would deeply understand you. It would remember everything about you. It would have context.

它会具备推理能力，然后就能在没有你干预的情况下做出所有这些决策，这就是自主代理。所以这也是像我这样的人非常感兴趣的另一个优化方向。

It would have a reasoning, and then it would be able to do make all these decisions without your without your intervention, which would be autonomous agents. So that that that's also another very interesting place for someone like me to to to optimize for as well.

我正想说，想象一下甚至不需要被告知这就是你的选择。比如，'哦，去查看并订阅最棒的新闻通讯'。如果你在上面，好事就会发生。哇，多么疯狂的世界。

I was just gonna say, just imagine not even being told this is what you're choosing. Like, oh, and go check out subscribe to the best newsletter out there. And, you know, if you're up there, if the good things will happen. Wow. What a wild world.

我们还有什么没涉及的内容吗？你觉得对于那些想要在这方面做得更好、尝试迈出AEO第一步的人们会有帮助的？

Is there anything else that we haven't covered that you think would be helpful to folks that are trying to get better at this stuff, try to take the first steps down this road of AEO?

是的。我最兴奋的话题是帮助中心优化和支持。太好了。我之前提到人们在聊天中会提出后续问题。他们在寻找工具。

Yes. My the most exciting topic, which is help center optimization and support. Sweet. So I mentioned that people in chat are asking follow-up questions. They're looking for tools.

'你们有这个功能、这个用例、这个集成吗？'这些问题通常可以在帮助中心找到答案。通常，你不会对SEO团队说'我们真的希望你们专注于帮助中心'。但在聊天中，由于存在所有这些关于'你能做这个吗？能满足我的用例吗？'的问题

Do you have this feature, this use case, this integration? And that frequently can be answered in help centers. And usually, you would not have an SEO team and say, we really want you guys to focus on the help center. But in chat, since you're there's all these questions about, can you do this thing? Can you fulfill my use case?

帮助中心实际上是个很好的地方来处理这些。所以我认为如何优化帮助中心？第一点是它经常位于子域名上。不管什么原因，子域名不如子目录效果好。把它移到子目录下。

Help center act is actually a great place to do that. And so I think how how can you optimize the help center? So number one is it's frequently on a subdomain. For whatever reason, subdomains don't work well as subdirectories. Move it to a subdirectory.

第一点。第二点是确保你们有良好的交叉链接。通常，你们没有优化的内部链接。所以要从帮助中心页面链接到帮助中心页面。确保减少交叉链接。

Number one. Number two is make sure that you're cross linking well. So usually, you do not have optimized internal links. So link from help center page to help center page. Make sure there's less cross linking.

第三点是你们可能有关于头部的帮助中心内容，但对于长尾部分，你们可能没有任何帮助中心内容。举个例子，我当时想追踪我们的销售电话，查看谁参加了会议以及情绪如何。我想把这些数据导入Looker。于是我问，哪些会议转录工具能与Looker集成？答案是都没有。

The third is you probably have help center content about the head, but the tail, you probably don't have any help center content for. So an example of this is I was looking for I wanted to track our sales calls and look to see who is in the meeting and what the sentiment was. And I wanted to put that into Looker. So I said, which meeting transcription tool integrates with Looker? And the answer is none of them.

但你可以使用Otter，因为Otter有Zapier集成。你可以通过zap发送会议记录，存入BigQuery，然后在上面使用Looker。但没有关于这个的帮助中心文章，因为这是一个非常小众的使用场景，但并非零需求场景。所以在长尾部分，会有很多问题你们可能没有相应的帮助中心文章。所以，再次强调，销售电话中会出现哪些问题？

But you could use Otter because Otter has a Zapier integration. You could send a zap of the meeting, put it into BigQuery, and then do Looker on top of that. But there wasn't a help center article about that because it's a very obscure use case, but it's not a zero use case. And so the tail, there's gonna be a bunch of questions in the tail that you may not have help center articles for. So, again, what are the questions in sales calls?

你们在客户支持中看到哪些问题？为这些问题创建页面。我甚至可能会向社区开放，任何人都可以提问，因为社区会填补长尾部分并回答这些问题。而且，在很多情况下，可能根本没有人讨论这个话题。

What are the questions that you're seeing customer support? Having pages for that. I might even open up to the community. Anyone can ask anything because the community will then fill on the tail and then answer those. And, again, in many cases, there might be nobody talking about this at all.

所以你可以成为这个话题的唯一引用来源，然后赢得这些长尾问题的流量。

So you could be the only citation for this and then win that tail of questions.

目前有没有什么帮助台系统软件能让这件事变得更容易？或者你觉得这是Zendesk或Intercom之类的机会？

Are there any help desk, I don't know, system software that are just making this easier yet, or you think that's an opportunity for, say, Zendesk or Intercom?

我认为可能所有的软件都应该能完美运作。唯一需要做的就是交叉链接和使用子目录而不是子域名，这大多数软件应该都支持。所以我认为它们都应该能免费实现这个功能。主要需要做的是向社区开放，确保填补长尾内容，但这些工具应该都适合这个用途。

I think probably all of them should work perfectly well. I think that the only thing you need to do is cross linking and subdirectory rather than subdomain, which probably most of them do. So I think that they should all work for free. That the main thing you would wanna do would be, again, open it up to the community, make sure that you fill in the tail, but probably all those tools should be good for this.

好了，说到这里，我们已经进入了非常激动人心的快速问答环节。我有五个问题要问你，Ethan。你准备好了吗？

Well, with that, we've reached our very exciting lightning round. Got five questions for you, Ethan. Are you ready?

我准备好了。

I'm ready.

你发现自己最常向别人推荐的两三本书是什么？

What are two or three books that you find yourself recommending most to other people?

第一本是《情商》。人们经常谈论情商这个概念，但心理学领域确实有相关研究。我记得这本书应该是八十年代出版的，但有一本很好的书总结了关于情商的基础研究。在建立人际关系和与人沟通时，理解他们的情绪非常有用。所以这是第一本。

Number one is emotional intelligence. And people talk about the concept of emotional intelligence, but there's actual research in psychology around that. I believe it was published in the eighties, but there's a really good book that summarizes the foundational research around emotional intelligence. And it's very useful when when building relationships and communicating with people to understand their emotions. So that's the first one.

还有关于增长的书，因为增长就是让用户使用你的产品。所以如果你有框架来指导人们如何使用你的产品，你就能成为一个更有效的增长人员，这就引出了我推荐的第二本书——西奥迪尼的说服力书籍。罗伯特·西奥迪尼写了一系列关于说服力的书。同样，他提供了通过某些方式说服用户注册的框架，并详细分解了这个框架。

And doing growth because growth is, you know, getting people to use your stuff. And so if you have frameworks to inform how people are will use your things, then you can be a more effective growth person, which brings me to my second book, which is Cialdini's persuasion book. Robert Cialdini does a bunch of books around persuasion. But, again, there's frameworks for how to persuade somebody to sign up by something. And so he breaks down his framework for that.

同样，这也是基于心理学的。我认为特别是在增长领域，有各种心理学研究和行为经济学研究来指导测试。如果你读了《思考，快与慢》、说服力相关书籍和情商书籍，你基本上可以运用这些框架，以各种不同方式应用到增长中。最后一本是《如何测量一切》。这本书讲的是如何测量那些不容易直接测量的东西。

And, again, it's based on psychology. And I think, especially in growth, there's all kinds of psychology research and behavioral economics research to inform tests. And if you just read thinking fast and slow persuasion, emotional intelligence, you can basically take those frameworks and apply it to growth in all kinds of different ways. And then the last is how to measure anything. So how to measure anything is about measuring things that are not immediately obvious to to measure.

书中举了个例子：他们想测量一个乐团指挥的水平，可以通过调查或查看每位指挥获得起立鼓掌的次数来判断。起立鼓掌次数越多，可能意味着指挥水平越高，这样就不需要去调查人们了。但增长和商业中的许多事情都不是那么容易直接测量的，然而任何事情都是可以测量的。所以这是我的第三个推荐。

They give this example of they wanted to measure how good an orchestra conductor was, and they could survey or they could see the number of standing ovations for each orchestra conductor. And the more standing ovations probably means it's this this better one, and that you don't need to survey people. But much of growth and and business is things that are not immediately obvious for how to measure, but anything could be measured. And so that's my third recommendation.

你最近有没有特别喜欢的一部电影或电视剧？

Is there a favorite recent movie or TV show you've really enjoyed?

我不怎么看电视，但我看两类不同的东西。我喜欢看非常激烈的体育赛事。所以我特别喜欢迈克尔·乔丹的纪录片《最后一舞》。我喜欢兰斯·阿姆斯特朗那些展现他攻击性和对抗性的纪录片，还爱看UFC。我喜欢极致的攻击性和强度。

I don't really watch TV, but I watch two different groups of things. I watch really aggressive sports. So I really like Michael Jordan documentary, Last Dance. I like Lance Armstrong documentaries about how aggressive and confrontational he is, and I love watching UFC. I like extreme aggression and and intensity.

另一类我喜欢看的是攀岩纪录片。只要是亚历克斯·霍诺德、金国洋做的，我都会看，这完全与激烈运动相反。这是禅意、保持专注、缓慢而稳健的技艺，但这某种程度上也是我工作的方式——极致的强度和攻击性，再加上禅意般的专注技艺。

The other group of stuff that I like to watch are climbing documentaries. So anything that Alex Honnold, Jimmy Chan do, I watch all that, which is the exact opposite of aggressive sports. So it's zen, being present, slow and steady craftsmanship, but this is sort of how I approach my work, which is extreme intensity and aggressiveness, and then the zen craftsmanship being present.

我很喜欢这个解释，它说明了为什么人们喜欢与你合作，以及你为什么擅长这个——既有这种竞争性，又有那种超级书呆子般深入研究事物运作原理的热情。我之前没想过其中的禅意元素，就是在整个过程中保持冷静。

I love how this explains why people love working with you and why you're good at this is, like, this competitiveness and also just, like, the super nerdiness to get really knowledgeable about how this stuff works. And then I didn't think about the zen element of it just, like, staying calm throughout it all.

心流。心流状态。

Flow. Flow state.

哇。这真是解释你为什么如此擅长这个的有趣缩影。谢谢。好的，我继续问。

Woah. What a funny microcosm of of why you're so good at this. Thank you. Okay. I'm gonna keep going.

你最近有没有发现特别喜爱的产品？

Do you have a favorite product you recently discovered that you really love?

这个相机和这个麦克风。我买了一台索尼的无反单反相机，具体型号我忘了。但是拥有一台带广角镜头的无反单反相机真的能彻底改变你的视频通话体验。

This camera and this microphone. So I I got a Sony mirrorless SLR. I forget which one. But getting a Sony or sorry. Getting a mirrorless SLR with a wide angle lens really transforms your video calls.

然后我还有这个舒尔麦克风，我觉得大概是180型号。这极大地提升了我的视频通话质量。我喜欢设计东西，你也可以设计你的视频通话，让它们变得惊艳。你可以在背景这里放些花，比如向日葵。

And then I have this I have this Shure microphone, and I think it's like one eighty. So this dramatically improves the quality of my video call. And I like to design things, and you can design your video calls, and you can make them amazing. You can have, you know, you can have flowers in the background over here, some sunflowers.

真漂亮。

So Beautiful.

我最喜欢的产品是我的相机，就是我用在视频通话上的单反相机，还有我的麦克风。

My my favorite products are my my camera, my SLR camera that I use for video calls, and my microphone.

你的背景非常精致，我之前没提，但看起来很美。好的，还有两个问题。你有没有觉得在工作或生活中特别有用的人生格言？

Your background is quite exquisite, and I didn't mention that, but it looks beautiful. Okay. Two more questions. Do you have a life motto that you find really useful in work or in life?

《异类》这本书提到了一万小时定律，其中的核心观点是：你不必是最聪明的，但第一要足够聪明；第二是专注练习。所以不仅仅是努力，而是要有意识、专注地去做。

I there's a there's the Outliers book about ten thousand hours, And the themes there are, you don't have to be the smartest. You have to be sufficiently smart, number one. Number two is focused practice. So it's not just trying hard. It's doing it in a in intentional focused way.

第三点是大量练习。没有人能因为是天才能掌握任何技能，他们掌握是因为投入了大量时间练习，并且是以有意识的方式练习。所以我的格言基本上是这些要素的结合：我不一定能赢是因为我的大脑最大或我最努力，而是因为我会以最有意识的态度去练习，并尽可能全力以赴。

And the third thing is lots of practice. So you're not going to master any no one can master anything because they're a genius. They master it because they spend a significant amount of time practicing, and they practice in a in an intentional way. And so my motto is essentially a combination of those things, which is that I'm not going to necessarily win because my brain is the largest brain or that I tried the hardest. It's because I'm going to be the most intentional about my practice, and I'm gonna be as intense as I possibly can be about that practice.

好的。最后一个问题。我很好奇，有没有一个SEO甚至是AEO的成功案例让你最引以为傲，总是让你想起，哇，我简直不敢相信我做到了。我简直不敢相信我们当时产生的影响。

Okay. Final question. I'm curious if there's just, like, an SEO or even AEO win you're just most proud of that you always think about, wow. I can't believe I pulled that off. I can't believe the impact we had there.

我我我一直很喜欢黄油生菜与MasterClass的例子，因为MasterClass，在我刚开始与他们合作时，他们的权威性远不及All Recipes和Martha Stewart。我实际上当时不确定是否应该接这个项目，因为我觉得可能太难了。但我还是接了，确实很难。但我们最终排名非常有竞争力，比我预期的好得多，我认为这很可能是因为所有这些具体的执行细节。但黄油生菜是我最喜欢的案例，虽然我其实不喜欢吃黄油生菜。

I I I always like the example of butter lettuce with MasterClass because MasterClass, when when I was first working with them, they did not have nearly as much authority as all recipes and Martha Stewart. And we'd I actually didn't know I actually didn't know if I should take the project because I thought it might be too hard. But I did the project, it and it was hard. But we were able to rank really competitively and way better than I expected, and I think it's probably because of all these, you know, specific little execution details. But butter lettuce was was my favorite one, and I I don't like butter lettuce.

所以我现在可以搜索黄油生菜，就能在Masterclass上找到食谱。

So I can search for butter lettuce, I can get a recipe on Masterclass.

太棒了。我不知道这个播客之前是否提到过黄油生菜。Ethan，这真是太精彩了。这正是我所期待的一切。我感觉我们刚刚提升了每个人对SEO和AEO到底是怎么回事的认知水平。

That's amazing. I don't know if butter lettuce has been mentioned on this podcast before. Ethan, this was incredible. This was everything I was hoping it'd be. I feel like we've just leveled up everyone's knowledge on what the hell is happening with SEO and AEO.

先别管地理定位了。有两个后续问题。如果大家想和你们合作，可以在哪里找到你们？以及听众如何能对你们有所帮助？

Forget about geo. Two follow-up questions. Where can folks find you if they wanna potentially work with you guys? And how can listeners be useful to you?

所以首先，你可以在LinkedIn上找到我。我花很多时间在LinkedIn上，并且我们发布原创研究。我们有一个完整的研究团队进行假设和验证。所以我提到的所有研究我们都会发布在我们的网站上，我也会在LinkedIn上发布。所以在LinkedIn上关注我吧。

So where you can find me, number one, is on LinkedIn. I spend lots of time on LinkedIn, and I publish original so we do original research. We have a real whole whole research team hypothesizing and evaluating those hypotheses. So we publish all all the studies that I mentioned we publish on our site, and I publish them on LinkedIn. So follow me on LinkedIn.

在LinkedIn上加我好友。给我发消息。LinkedIn是第一选择。其次是我们有一个博客，我们称之为5%。也就是/5%，代表着5%的工作，5%的着陆页驱动了几乎所有的效果。

Add me on LinkedIn. Send me a message. LinkedIn number one. And then number two is we have a a blog, which which we call the 5%. So slash 5%, which stands for 5% of work, 5% of landing pages drive almost all the impact.

这就是我们的主题。只分享有用的内容。您可以在我们的5%博客订阅我们的邮件和研究报告。那么人们如何能对我有所帮助呢？我花时间思考过这个问题，主要有两种方式。

So that's sort of the theme. This is only useful stuff. So our our blog at 5%, you could subscribe to our to our email and to our studies. And then how can people be useful to me? So I spent time thinking about this, and there's two ways people can help me.

第一种方式是：目前关于AEO有效方法的研究并不多，我非常想知道大家在测试什么、结果如何以及哪些方法有效。所以如果有人能进行研究并发布或发送给我，我会非常欢迎，希望获得尽可能多的分析和研究，这是第一点。第二点是在LinkedIn上通过评论我的帖子和留言来帮助我。比如您最近发布的Brian Balfour那期节目，我写了一条长篇深度评论，获得了约25个赞，还收到了回复。我一直在评论他人的LinkedIn帖子，并且自己也撰写这些长篇LinkedIn内容。

The first way is that there's not that much research around what works in AEO, and I would love to know what people are testing and what the results are and what works. So people doing studies and publishing that or sending it to me, I would love, you know, as much analysis and research as possible, number one. Then the second one is to help me on LinkedIn by commenting on my posts and on my comments. So you posted most recently the Brian Balfour episode for which I wrote a long thoughtful comment, and then I got about 25 likes, and then I got responses to that. And so I've been commenting on other people's LinkedIn posts, and I've been writing these long LinkedIn posts.

当人们评论时，会提升LinkedIn内的互动度，从而让我获得大量曝光。所以越多的人发表深度评论越好——不是简单说'很棒'，而是能引发对话的长篇 thoughtful 评论。如果有人评论我的帖子，我在LinkedIn上就会爆红，说不定哪天也能像您一样成功。

And when people comment, it boosts engagement within LinkedIn, and then I get mass distribution. So the more people and thoughtful comments. So not this is great, but, you know, a long thoughtful comment that stimulates conversation. So if people comment on my post, then I'm just gonna blow up in LinkedIn, and I might be as big as you someday.

我很欣赏这个请求如此具体务实。Brian Johnson——那个研究长寿的家伙——在Twitter上就很擅长这个。他总是用特别有趣的方式回复推文，感觉这成了他重要的增长渠道。很高兴您和Brian Johnson有这个共同点。

I love how tactical this ask is. It's something Brian Johnson, noticed, is really good at on Twitter, the longevity guy. He just replies to tweets in a really funny way and feels like that's a big growth channel for him. So I love that that you have this in common with Brian Johnson.

是的。

Yes.

另外，指引大家访问您的域名graphite.io。是这个域名对吗？

Also, to point people to your domain, graphite.io. Is that the right domain?

对的。

Yep.

太棒了。伊桑，非常感谢你与我们分享这么多，也感谢你的到来。

Amazing. Ethan, thank you so much for sharing so much with us and for being here.

当然。很高兴能来到这里。

Absolutely. It's good to be here.

再见，各位。非常感谢大家的收听。如果你觉得本期内容有价值，可以在苹果播客、Spotify或你喜欢的播客应用上订阅我们的节目。同时，请考虑给我们评分或留下评论，因为这真的能帮助其他听众发现这个播客。你可以在lennyspodcast.com上找到所有往期节目或了解更多关于节目的信息。

Bye, everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennyspodcast.com.

下期节目再见。

See you in the next episode.