Neil Patel: AI营销的陷阱

The Trap of AI Marketing

AI 营销的陷阱

作者：Neil Patel 

There's a trap in AI marketing right now that's making brands invisible, and most marketers are walking straight into it.

目前的 AI 营销中存在一个让品牌变得不可见的陷阱，而大多数营销人员正径直走向它。

My team and I studied thousands of campaigns across the brands we work with and the ones we compete against.

我和我的团队研究了数以千计的营销活动，涵盖了与我们合作的品牌以及我们的竞争对手。

The ones using AI the most had the lowest brand recall.

那些最多使用 AI 的品牌，其品牌回想度反而最低。

The ones using it the least were falling behind on volume.

那些最少使用 AI 的品牌，在内容产出量上则处于落后状态。

But a small group figured out a third way, and they're outperforming everyone.

但有一小群人找到了第三种方法，他们的表现超越了所有人。

Here's exactly what they're doing differently.

以下正是他们与众不同的做法。

Chapter 1: AI Is Making Marketing Average

第一章：AI 正在让营销变得平庸

Most marketers think AI will make their creativity better.

大多数营销人员认为 AI 会提升他们的创造力。

And in many ways, it already has.

在许多方面，它确实已经做到了。

Today, one person can generate ad visuals, write scripts, produce voiceovers, and even create animations that rival Pixar's.

如今，一个人就能生成广告视觉效果、撰写脚本、制作配音，甚至创作出媲美皮克斯的动画。

These were once things that would require entire creative teams, and even millions and millions of dollars.

这些曾经都需要整个创意团队，甚至数以百万计的资金才能完成。

But there's a side effect no one talks about.

但这里有一个无人提及的副作用。

Instead of making brands more distinctive, AI is actually pushing everyone towards the same middle-of-the-road ideas.

AI 并没有让品牌变得更具特色，反而将所有人推向了同样中庸的想法。

And here's the thing nobody in marketing wants to say out loud: AI doesn't create originality.

这是营销界没人愿意大声说出的事实：AI 无法创造原创性。

It creates the statistical average of the internet.

它创造的是互联网上的统计平均值。

Ben Affleck explained this well in a recent conversation with Joe Rogan.

本·阿弗莱克在最近与乔·罗根的对话中很好地解释了这一点。

For example, if you try to get ChatGPT, Claude, or Gemini to write you something, it's really, by its nature, going to the mean, to the average.

“比如，如果你尝试让 ChatGPT、Claude 或 Gemini 给你写点东西，从本质上讲，它真的是在趋于平均水平，走向平庸。”

He said, "Generative AI tends to produce the average version of things because it's trained on massive data sets that predict the most likely next output."

他说：“生成式 AI 倾向于生成事物的平均版本，因为它是基于海量数据集进行训练的，其目的是预测最可能出现的下一个输出内容。”

That's exactly what we're seeing in marketing right now.

这正是我们目前在营销领域所看到的现象。

Don't believe me?

不相信我？

Let me show you.

让我展示给你看。

Open LinkedIn right now and scroll.

现在打开领英并向下滑动。

You'll see the same hooks, the same structures, the same 10-tips posts; different brands, but the content feels almost identical.

你会看到同样的吸睛话术、相同的文章结构、一样的“十个小技巧”帖子——虽然品牌不同，但内容感觉几乎一模一样。

And the data proves it.

数据也证明了这一点。

A study from Originality.ai found that over 54% of long-form LinkedIn posts are now AI-generated, a 189% increase since the ChatGPT launch.

Originality.ai 的一项研究发现，超过 54% 的领英长文现在是由 AI 生成的，自 ChatGPT 发布以来增长了 189%。

And here's the part that matters: those AI posts get 45% less engagement than original ones.

关键在于：这些 AI 帖子的互动率比原创帖子低了 45%。

Your audience can't always explain why something feels off, but they scroll past it anyways.

你的受众可能无法总是解释为什么感觉有些不对劲，但他们还是会直接滑过。

Right now, the default workflow for most marketers looks like this: Open ChatGPT, type "give me 10 ad headlines," maybe "write a blog post about this topic," and publish whatever comes out.

目前，大多数营销人员的默认工作流程是这样的：打开 ChatGPT，输入“给我写 10 个广告标题”，或者“写一篇关于这个主题的博客文章”，然后把生成的结果直接发布。

The problem is, thousands of other marketers are asking the same tools the same questions.

问题在于，成千上万的其他营销人员也在向同样的工具询问同样的问题。

So, you end up with different companies publishing slightly different versions of the same content.

所以，最终的结果是不同的公司发布了同一内容的微调版本。

If your AI workflow starts with "generate content," you're already limiting your creativity.

如果你的 AI 工作流程以“生成内容”为起点，那么你已经在限制自己的创造力了。

But this isn't about your content sounding generic; there's a deeper problem, and it's costing brands something they can't easily get back.

但这不仅仅是内容听起来平庸的问题；这里还有一个更深层次的问题，它正在让品牌失去一些难以轻易找回的东西。

Chapter 2: Your Brand Is a Feeling, Not a Logo

第二章：品牌是一种感觉，而不仅仅是一个标志

One of the biggest mistakes marketers make is thinking a brand is just a visual identity: a logo, a color palette, maybe a tone-of-voice guide.

营销人员常犯的最大错误之一，就是认为品牌仅仅是一种视觉形象：一个标志、一组调色板，或者是一份品牌语调指南。

But that's not what a brand is.

但品牌并非如此。

A brand isn't what your marketing looks like; it's what people feel when they see it.

品牌不是你营销的表象，而是人们看到它时的感受。

I was talking about this recently with Matt, our Global SVP of Creative and Creative Technologies.

我最近和我们的创意与创意技术全球高级副总裁马特谈到了这个话题。

And he said something that stuck with me: "A brand doesn't live inside a design system or a brand book. It lives in the reaction people have when they encounter your company."

他说了一句让我记忆犹新的话：“品牌并不存在于设计系统或品牌手册中。它存在于人们接触你的公司时所产生的反应里。”

Think about Levi's.

想想李维斯（Levi's）。

When you see Levi's, there's a feeling: classic American, cool, durable, timeless.

当你看到李维斯时，会产生一种感觉：经典的美式风格、酷炫、耐穿、永恒。

Now, think about Dove.

现在，想想多芬（Dove）。

For years, they've reinforced one core idea: real beauty.

多年来，他们一直在强化一个核心理念：真正的美。

Those brands don't just produce content; they produce a recognizable emotional signal.

这些品牌不仅仅是在生产内容；它们在产生一种具有辨识度的情感信号。

And when companies rely too heavily on AI-generated marketing, that signal disappears.

而当公司过度依赖 AI 生成的营销时，这种信号就会消失。

Everything starts sounding polished, but strangely interchangeable.

一切听起来都很精致，但却出奇地千篇一律。

Want to see what that looks like in practice?

想看看在实践中这是什么样子的吗？

Look at Coca-Cola.

看看可口可乐。

They took one of the most beloved Christmas ads of all time and remade it with AI twice.

他们把有史以来最受人喜爱的圣诞广告之一，用 AI 翻拍了两次。

Both times, the internet called it soulless.

两次网友都评价其“没有灵魂”。

One analyst scored the AI version just 22 out of 100 compared to the YouTube ads.

一位分析师对 AI 版本的评分只有 22 分（满分 100 分），远低于以往的 YouTube 广告。

A marketing professor at the University of Wisconsin-Madison said the backlash hit so hard because Christmas represents a connection and community values that felt fundamentally at odds with AI-generated content.

威斯康星大学麦迪逊分校的一位营销学教授表示，之所以会引发如此强烈的反弹，是因为圣诞节代表着人际连结和社区价值观，这让人感觉与 AI 生成的内容在根本上是格格不入的。

The brand that reinvented emotional advertising couldn't replicate the feeling with AI.

这个重新定义了情感营销的品牌，也无法用 AI 复制出那种感觉。

That's not a technology problem; that's a taste problem.

这不是技术问题，而是品味问题。

Your customers may not consciously say, "This feels AI-generated."

你的客户可能不会下意识地说：“这感觉像是 AI 生成的。”

But they can feel when a brand has no real point of view.

但他们能感觉到一个品牌何时失去了自己真正的观点。

And when every brand starts sounding the same, the ones with a clear identity are the ones people remember.

当所有品牌听起来都如出一辙时，那些拥有鲜明特质的品牌才是人们真正能记住的。

So if AI is making content average and it's stripping the emotion out of brands, what are the companies that figured this out actually doing?

那么，如果 AI 正在让内容变得平庸，并且剥夺了品牌的情感，那些看透这一点的公司究竟在怎么做呢？

That's where this gets interesting.

这正是事情变得有趣的地方。

Chapter 3: Use AI to Expand Ideas, Not Replace Them

第三章：用 AI 拓展创意，而非替代创意

The real power of AI isn't generating finished output.

AI 真正的力量不在于生成最终作品。

It's expanding the number of ideas you can explore.

而在于增加你可以探索的创意的数量。

Most marketers are using AI like a shortcut to the final answer.

大多数营销人员把 AI 当作通往最终答案的捷径。

But the smartest teams, they're using it earlier in the process, when ideas are still in the brainstorming phases.

但最聪明的团队是在流程的更早期使用它，即当创意仍处于头脑风暴阶段时。

In traditional advertising agencies, creative teams didn't jump straight into writing the ad.

在传统的广告公司中，创意团队不会直接跳进去写广告。

They started by tossing around ideas, half-formed concepts, odd connections, and cultural references.

他们首先会抛出各种想法、半成型的概念、奇特的关联以及文化参考。

Sometimes someone from another team would walk past a brainstorm and suggest something unexpected, a small observation that completely shifted the direction of the campaign.

有时，其他团队的人路过头脑风暴会议时，会提出一些意想不到的建议——一个微小的观察就彻底改变了整个营销活动的方向。

Those moments weren't planned.

这些时刻并非事先计划好的。

They were often where the strongest ideas came from.

但它们往往是诞生最强大创意的地方。

Today, AI can play that role in the early stages.

如今，AI 可以在早期阶段扮演这个角色。

Instead of asking AI to write the final ad, use it to explore different angles, new concepts, cultural references, and different ways to frame the idea that creates creative divergence instead of convergence.

不要让 AI 直接写出最终的广告，而是利用它来探索不同的角度、新的概念、文化背景以及不同的框架方式，从而创造出创意的发散而非收敛。

Matt described how he does this with our clients at NP Digital.

马特描述了他在 NP Digital 与客户合作时是如何做到这一点的。

Instead of asking AI to write headlines, he starts with the loose territory around the brand: themes like journeys, experiences, and the emotional state the brand wants customers to feel.

他没有让 AI 写标题，而是从品牌周围宽松的领域入手：比如旅程、体验等主题，以及品牌希望客户感受到的情感状态。

From there, he pushes the conversation wider, asking for related concepts, metaphors, and adjacent ideas.

从那里开始，他将对话推向更广的范围，要求提供相关的概念、隐喻和相近的想法。

During one of those explorations, the word "flow" surfaced.

在其中一次探索中，“心流（flow）”这个词浮现了出来。

That single word ended up becoming the seed for the entire direction of the campaign.

这一个词最终成为了整个营销活动方向的种子。

That's the difference between using AI for answers and using AI for exploration.

这就是把 AI 用于寻找答案和把 AI 用于探索的区别。

The best marketers don't treat AI as a writer.

顶尖的营销人员不会把 AI 当作作家。

They use it as an idea accelerator, the tool that helps them see more possibilities before choosing the strongest one.

他们将它视为一个创意的加速器，一个在选择最强创意之前帮助他们看到更多可能性的工具。

But companies that are really pulling ahead, they're not just changing how they brainstorm.

但那些真正遥遥领先的公司，他们不仅仅是在改变头脑风暴的方式。

They're building something bigger.

他们正在构建更宏大的体系。

Chapter 4: Build a Creative System, Not a Prompt

第四章：建立创意系统，而非仅仅编写提示词

The biggest misconception about AI in marketing is that it's just a tool.

在营销中，关于 AI 最大的误解就是认为它仅仅是一个工具。

You open ChatGPT, generate content, and move on.

你打开 ChatGPT，生成内容，然后继续做别的事。

But the companies getting the most value aren't treating it like a single tool.

但获得最大价值的公司并没有把它当作一个单一的工具来对待。

They're building systems around it.

他们正在围绕它建立系统。

Think of it as a brand AI stack.

可以把它看作是一个品牌 AI 技术栈。

Instead of relying on one generic model, these companies build multiple AI tools trained for specific roles inside the brand.

这些公司不再依赖于单一的通用模型，而是构建了多个针对品牌内部特定角色进行训练的 AI 工具。

One system analyzes contextual trends and surfaces ideas the brand could react to.

一个系统负责分析环境趋势，并呈现品牌可以做出反应的创意。

Another evaluates whether a campaign idea actually fits the brand's voice.

另一个系统评估活动理念是否真正符合品牌的声音。

Another explores creative directions before the team commits to one.

还有一个系统在团队做出最终决定之前，探索各种创意方向。

In that setup, AI isn't replacing the creative team.

在这种架构下，AI 并不是在取代创意团队。

It's acting like an ecosystem of assistants, helping the team think faster.

它是作为一个助手生态系统发挥作用，帮助团队思考得更快。

Instead of generating one idea and hoping it works, teams can explore dozens of directions, test them quickly, and refine the strongest ones.

团队不再是只生成一个创意并祈祷它能奏效，而是可以探索几十个方向，快速进行测试，并不断打磨出最强的方案。

The marketers who win with AI won't be the ones writing the best prompts.

在 AI 时代胜出的营销人员，不会是那些写出最佳提示词的人。

They'll be the ones who design systems that help their teams discover better ideas faster.

而将是那些设计出能够帮助团队更快发现更好创意的系统的人。

But even the best systems need one thing AI still can't do.

但即便是最好的系统，也需要具备一个 AI 至今仍无法做到的东西。

And this is where the real competitive advantage lives.

而这正是真正竞争优势的所在。

Chapter 5: The Real Competitive Advantage Is Human Taste

第五章：真正的竞争优势是人类的品味

As AI keeps improving, the one thing in marketing that's becoming cheaper every year is execution.

随着 AI 的不断进步，营销中一项每年都在变得越发廉价的东西就是执行力。

AI can write copy, generate visuals, and produce ad variations faster than most teams, which means the competitive advantage is shifting somewhere else.

AI 撰写文案、生成视觉效果和制作广告变体的速度超过了大多数团队，这意味着竞争优势正在向其他地方转移。

And the data tells us exactly where.

数据准确地告诉了我们这个优势在哪里。

Research shows that human-generated content receives over five times more traffic than AI-generated content, with steady growth, while AI content traffic fluctuates.

研究表明，人类生成的内容获得的流量是 AI 生成内容的五倍以上，而且呈现稳步增长，而 AI 内容的流量则波动不定。

But here's the part most people miss: The highest performing companies aren't avoiding AI.

但这里有一个大多数人忽略的细节：表现最好的公司并没有回避 AI。

They're the ones who have figured out where AI should help and where humans should lead.

他们是那些弄清楚了哪里该由 AI 辅助，哪里该由人类主导的公司。

That's the third way.

这就是前面提到的第三种方法。

AI can surface thousands of possible ideas, but someone still has to recognize the one that's worth building an entire campaign around.

AI 可以呈现成千上万个可能的主意，但仍需要有人来识别出那个值得为其打造整个营销活动的金点子。

In the AI era, the skill that matters the most isn't prompting; it's taste.

在 AI 时代，最重要的技能不是写提示词，而是品味。

And if you need help with taste, check out my ad agency, NP Digital, where we were just named Performance Marketing Agency of the Year by Ad Age.

如果你在品味方面需要帮助，不妨去了解一下我的广告公司 NP Digital，我们刚被《广告时代》(Ad Age) 评为年度效果营销机构。

The ability to look at a wall of AI-generated options and say, "That one, that's the one"—that's what can't be automated.

面对满墙的 AI 生成选项，能够指出“就是那个，就是它了”的能力——这是无法被自动化的。

The future of marketing won't be AI versus humans.

营销的未来不会是 AI 对抗人类。

It'll be creative teams using AI to explore more ideas, test more directions, and move faster.

而是创意团队利用 AI 来探索更多想法、测试更多方向并快速推进。

While the final decisions will still come from people who understand culture, customers, and the brand they're building.

同时，最终的决定仍然由那些理解文化、客户以及他们正在塑造的品牌的人来做出。

Brands that combine both will move faster than everyone else without becoming average.

将两者结合的品牌将比所有人都跑得更快，且不会沦为平庸。

So, here's what I want you to do.

所以，这就是我希望你做的。

Take your last 10 pieces of content, strip the brand name off, show them to someone on your team, and ask, "Can you tell this is us?"

拿出你最近创作的 10 篇内容，隐去品牌名称，拿给你的团队成员看，然后问他们：“你能看出来这是我们的内容吗？”

If they can't, you're already in the trap.

如果他们看不出来，那么你已经掉进陷阱里了。

Drop a comment and tell me what you found.

留下评论，告诉我你的发现。

And if you want to go deeper on which AI tools actually work for marketing and how to build this into your workflow, watch this next video.

如果你想深入了解哪些 AI 工具在营销中切实有效，以及如何将此融入你的工作流程，请观看下一个视频。

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