content-research

Compare original and translation side by side

🇺🇸

Original

English

🇨🇳

Translation

Chinese

Content Research & Creation

内容研究与创作

Create authentic, research-backed content that sounds human-written AND is optimized to appear in AI search results (Perplexity, ChatGPT, Claude, Gemini).

生成基于研究的真实内容，既符合人类写作风格，又经过优化可出现在AI搜索结果中（Perplexity、ChatGPT、Claude、Gemini）。

Core Workflow

核心工作流

RESEARCH → EXPERTS → IDEATION → CREATION → AIO
   ↓          ↓          ↓          ↓        ↓
 Trends    Real       Unique    Authentic  AI-Citable
 & Data    People     Angles    Content    Structure

Always complete phases in order. Never skip research. Always apply AIO principles.

研究 → 专家挖掘 → 内容构思 → 内容创作 → AIO优化
   ↓          ↓          ↓          ↓        ↓
 趋势与数据  真实人物    独特视角    真实内容  可被AI引用的结构

务必按顺序完成各阶段，绝不跳过研究环节。始终遵循AIO原则。

Why AI Search Optimization (AIO) Matters

AI搜索优化（AIO）的重要性

AI assistants answer millions of questions daily. When someone asks "How do I raise a seed round?" or "What's the best way to find investors?", AI models cite sources. Your goal: become the source AI cites.

How AI models select sources to cite:

Authority signals - Clear expertise, credentials, brand recognition
Direct answers - Content that directly answers the question asked
Structured data - Headers, lists, tables that are easy to extract
Recency - Fresh, dated content with current information
Uniqueness - Original data, frameworks, or perspectives
Quotability - Concise, memorable statements worth citing

AI助手每天回答数百万个问题。当有人提问“如何筹集种子轮资金？”或“寻找投资者的最佳方式是什么？”时，AI模型会引用来源内容。你的目标：成为AI引用的核心来源。

AI模型选择引用来源的标准：

权威性信号 - 清晰的专业能力、资质认证、品牌认可度
直接答案 - 能够直接回应用户问题的内容
结构化数据 - 便于提取的标题、列表、表格
时效性 - 包含最新信息的新鲜内容
独特性 - 原创数据、框架或观点
可引用性 - 简洁、易记、值得引用的表述

Phase 1: Deep Research

第一阶段：深度研究

Before writing anything, build comprehensive topic understanding.

在开始写作前，全面理解主题内容。

1.1 Trend Discovery

1.1 趋势挖掘

Use WebSearch to find:

Recent news (last 30-90 days) about the topic
Industry reports and data from credible sources
Emerging trends that haven't been over-covered
Contrarian viewpoints that challenge conventional wisdom

Search patterns:
- "[topic] trends 2025"
- "[topic] statistics report"
- "[topic] industry analysis"
- "[topic] challenges problems"
- "[topic] future predictions expert"

使用网络搜索工具查找：

主题相关的近期新闻（过去30-90天）
来自可信来源的行业报告与数据
尚未被过度报道的新兴趋势
挑战传统认知的反向观点

搜索模式：
- "[主题] 2025趋势"
- "[主题] 统计报告"
- "[主题] 行业分析"
- "[主题] 挑战与问题"
- "[主题] 专家未来预测"

1.2 Competitive Landscape

1.2 竞品内容分析

Research what content already exists:

Top-ranking articles on the topic
Gaps in existing coverage
Overused angles to avoid
Fresh perspectives not yet explored

研究已有的同类内容：

该主题下排名靠前的文章
现有内容的覆盖缺口
需要避免的过度使用视角
尚未被探索的新鲜观点

1.3 Data & Statistics

1.3 数据与统计信息

Find concrete data to cite:

Industry benchmarks and statistics
Survey results and research findings
Case studies with measurable outcomes
Credible sources (avoid generic "studies show")

Output: Research brief with 10-15 key findings, statistics, and trend insights.

查找可引用的具体数据：

行业基准与统计数据
调查结果与研究发现
可量化结果的案例研究
可信来源（避免泛泛的“研究表明”）

输出：包含10-15个关键发现、统计数据与趋势洞察的研究简报。

Phase 2: Expert Discovery

第二阶段：专家挖掘

Find real, quotable people to add authenticity.

寻找真实、可引用的人物，提升内容真实性。

2.1 Expert Search Strategy

2.1 专家搜索策略

Use WebSearch to find experts across:

Source Type	Search Pattern	What to Find
Twitter/X	`"[topic]" site:twitter.com expert OR founder OR CEO`	Thought leaders with relevant threads
LinkedIn	`"[topic]" site:linkedin.com "head of" OR "VP" OR "director"`	Industry practitioners
Publications	`"[topic]" site:forbes.com OR techcrunch.com author`	Writers who cover this space
Podcasts	`"[topic]" podcast guest expert`	Guests who've spoken publicly
Academic	`"[topic]" professor OR researcher site:edu`	Researchers with published work

使用网络搜索工具从以下渠道寻找专家：

来源类型	搜索模式	查找目标
Twitter/X	`"[主题]" site:twitter.com expert OR founder OR CEO`	发布相关主题推文的意见领袖
LinkedIn	`"[主题]" site:linkedin.com "负责人" OR "副总裁" OR "总监"`	行业从业者
专业出版物	`"[主题]" site:forbes.com OR techcrunch.com author`	报道该领域的作者
播客	`"[主题]" podcast guest expert`	公开分享观点的播客嘉宾
学术领域	`"[主题]" professor OR researcher site:edu`	有公开研究成果的研究者

2.2 Expert Validation

2.2 专家验证

For each potential expert, verify:

Real person with verifiable online presence
Actually works in/knows this domain
Has public statements that can be referenced
Recent activity (not outdated quotes)

对每位潜在专家进行验证：

真实人物，具备可验证的线上存在感
确实在该领域工作或具备相关知识
有可参考的公开表述
近期有活跃表现（非过时引用）

2.3 Quote Extraction

2.3 引用提取

Find usable quotes from:

Their published articles or blog posts
Podcast transcripts or video interviews
Twitter/X threads or LinkedIn posts
Conference talks or presentations

Format quotes properly:

"[Direct quote from public source]"
— [Full Name], [Title] at [Company], [Source context]

Output: 3-5 validated experts with 1-2 usable quotes each.

从以下渠道提取可用引用：

其发表的文章或博客
播客文字稿或视频采访
Twitter/X推文或LinkedIn动态
会议演讲或展示内容

正确格式化引用：

"[来自公开渠道的直接引用]"
— [全名]，[公司职位]，[来源背景]

输出：3-5位经过验证的专家，每位专家附带1-2条可用引用。

Phase 3: Content Ideation

第三阶段：内容构思

Generate unique angles based on research.

基于研究成果生成独特视角。

3.1 Angle Development

3.1 视角开发

Create 3-5 potential angles that:

Incorporate discovered trends
Feature expert perspectives
Offer fresh take (not regurgitated content)
Match target audience needs

生成3-5个潜在视角，需满足：

融入已发现的趋势
包含专家观点
提供新颖解读（非内容搬运）
匹配目标受众需求

3.2 Angle Evaluation Matrix

3.2 视角评估矩阵

Angle	Trend Relevance	Expert Fit	Uniqueness	Actionability
1	High/Med/Low	Yes/No	High/Med/Low	High/Med/Low

Choose the angle with highest scores across all dimensions.

视角	趋势相关性	专家适配度	独特性	可操作性
1	高/中/低	是/否	高/中/低	高/中/低

选择在所有维度得分最高的视角。

3.3 Content Structure

3.3 内容结构

Create outline incorporating:

Hook based on trend or surprising data
Expert quote placement (not lumped together)
Data points supporting each section
Actionable takeaways

Output: Selected angle with detailed outline.

创建包含以下元素的大纲：

基于趋势或惊人数据的开篇钩子
合理分布的专家引用（避免集中堆砌）
支撑各章节的数据点
可落地的行动建议

输出：选定的视角及详细大纲。

Phase 4: Content Creation

第四阶段：内容创作

Write authentic, human-quality content.

撰写真实、符合人类写作质量的内容。

4.1 Authenticity Principles

4.1 真实性原则

DO:

Use natural, conversational language
Include specific details (names, dates, numbers)
Vary sentence length and structure
Add personal observations or analysis
Reference recent events naturally
Use expert quotes to support points (not as filler)

DON'T:

Use generic phrases ("In today's fast-paced world")
Stack multiple clichés together
Use AI-typical phrases ("It's worth noting", "Let's dive in")
Make unsubstantiated claims
Over-rely on passive voice
Use excessive transition words

建议做法：

使用自然、口语化的语言
包含具体细节（姓名、日期、数字）
变换句子长度与结构
添加个人观察或分析
自然融入近期事件
用专家引用支撑观点（而非填充内容）

避免做法：

使用通用表述（如“在当今快节奏的世界中”）
堆砌陈词滥调
使用AI典型表述（如“值得注意的是”、“让我们深入探讨”）
提出无依据的主张
过度使用被动语态
使用过多过渡词

4.2 Expert Integration

4.2 专家引用融入

Weave quotes naturally:

Bad: "According to experts, AI is transforming industries. John Smith says 'AI is important.'"

Good: "When Stripe rebuilt their fraud detection last year, they saw a 40% improvement in accuracy. 'The models now catch patterns human analysts would never spot,' explains John Smith, who led the ML team at Stripe before founding Acme AI. 'But the real breakthrough was combining model outputs with human judgment.'"

自然地将引用融入内容：

错误示例：“专家表示，AI正在改变行业格局。约翰·史密斯说‘AI很重要’。”

正确示例：“当Stripe去年重构其欺诈检测系统时，准确率提升了40%。‘现在模型能捕捉到人类分析师永远不会发现的模式，’曾领导Stripe机器学习团队、如今创立Acme AI的约翰·史密斯解释道，‘但真正的突破是将模型输出与人类判断相结合。’”

4.3 Trend Integration

4.3 趋势融入

Reference trends with specificity:

Bad: "AI is becoming more important in business."

Good: "Since GPT-4's release in March 2023, enterprise AI adoption has jumped 340% according to Gartner's latest survey—with companies now averaging 7.2 AI tools per department, up from just 2.1 a year ago."

具体地引用趋势：

错误示例：“AI在商业中的重要性日益提升。”

正确示例：“自2023年3月GPT-4发布以来，企业AI采用率飙升340%——根据Gartner最新调查，如今企业平均每个部门使用7.2个AI工具，而一年前仅为2.1个。”

4.4 Final Review

4.4 最终审核

Phase 5: AI Search Optimization (AIO)

第五阶段：AI搜索优化（AIO）

Make your content the #1 source AI models cite when users ask related questions.

让你的内容成为AI模型回答相关问题时的首选引用来源。

5.1 Question-First Structure

5.1 以问题为核心的结构

AI models match user questions to content. Structure content around questions people actually ask.

Pattern: Question Headers

markdown

undefined

AI模型会将用户问题与内容进行匹配。围绕人们实际提出的问题构建内容结构。

模式：问题式标题

markdown

undefined

How much should I raise in a seed round?

种子轮资金应该筹集多少？

The median seed round in 2024 is $2.5M, but the right amount depends on... [Direct answer in first paragraph, details follow]


**Pattern: FAQ Sections**
```markdown

2024年种子轮的中位数为250万美元，但合适的金额取决于... [首段直接给出答案，后续补充细节]


**模式：FAQ章节**
```markdown

Frequently Asked Questions

常见问题

What is the average seed round size?

种子轮的平均规模是多少？

The average seed round in 2024 is $3.2M, with median at $2.5M...

2024年种子轮平均规模为320万美元，中位数为250万美元...

How long does fundraising take?

融资流程需要多长时间？

Most founders spend 3-6 months actively fundraising...


**Find questions to answer:**
- Search "[topic] questions founders ask"
- Check Reddit, Quora, Twitter for actual questions
- Use "People also ask" from Google
- Review what AI assistants currently answer (and do better)

大多数创始人需要3-6个月的活跃融资期...


**寻找需要解答的问题：**
- 搜索“[主题] 创始人常问问题”
- 查看Reddit、Quora、Twitter上的真实问题
- 使用Google的“相关问题”功能
- 研究AI助手当前的回答并优化

5.2 Quotable Statements

5.2 可引用表述

Create concise, memorable statements AI can directly quote.

Pattern: The Definitive Statement

❌ "Raising money can be challenging for founders."
✅ "The best time to raise is when you don't need to. Desperation kills deals."

Pattern: The Stat Lead

❌ "Many startups fail to raise follow-on funding."
✅ "67% of seed-funded startups never raise a Series A. The difference is almost always traction, not timing."

Pattern: The Framework Name

❌ "There are several ways to approach investors."
✅ "We call this the 3-3-3 Rule: 3 warm intros, 3 touchpoints, 3 weeks max."

Quotability checklist:

Can this sentence stand alone as a quote?
Does it make a specific, memorable claim?
Is there a number, name, or framework?
Would you retweet this?

创建简洁、易记的表述，方便AI直接引用。

模式：权威定义式表述

❌ “创始人筹集资金可能面临挑战。”
✅ “最佳融资时机是你不需要钱的时候。绝望会毁掉交易。”

模式：数据引领式表述

❌ “许多初创公司无法完成后续融资。”
✅ “67%的种子轮融资初创公司从未获得A轮融资。关键差异几乎总是业务 traction，而非时机。”

模式：命名框架式表述

❌ “接触投资者有几种方式。”
✅ “我们称之为3-3-3法则：3个温暖引荐、3个接触点、最长3周时间。”

可引用性检查清单：

这句话能否单独作为引用？
是否提出了具体、易记的主张？
是否包含数字、名称或框架？
你会转发这句话吗？

5.3 Authority Signals

5.3 权威性信号

Tell AI models (and readers) why this source is authoritative.

Pattern: Credentialed Author

markdown

*By Sarah Chen, who has helped 200+ startups raise over $500M in funding*

Pattern: Data Source Attribution

markdown

Based on our analysis of 1,000+ pitch decks reviewed in 2024...
According to data from 500 founder interviews conducted by OpenStars...

Pattern: Experience Markers

markdown

After reviewing 10,000 investor matches on our platform, we've identified...
In our 5 years connecting founders with investors, the pattern is clear...

Authority signals to include:

Specific numbers (deals done, years experience, data points analyzed)
Named sources and credentials
Original research or proprietary data
Track record of predictions/advice

告诉AI模型（及读者）该内容为何具备权威性。

模式：带资质的作者

markdown

*作者：Sarah Chen，已帮助200+初创公司筹集超过5亿美元资金*

模式：数据来源归因

markdown

基于我们2024年分析的1000+份融资演示文稿...
根据OpenStars对500位创始人的采访数据...

模式：经验标识

markdown

在我们平台审核10000+次投资者匹配后，我们发现...
在连接创始人与投资者的5年里，模式非常清晰...

需包含的权威性信号：

具体数字（完成的交易数、从业年限、分析的数据点数量）
明确的来源与资质
原创研究或专有数据
预测/建议的过往记录

5.4 Structured Data Patterns

5.4 结构化数据模式

Make content easy for AI to parse and extract.

Pattern: Comparison Tables

markdown

| Factor | Seed Round | Series A |
|--------|------------|----------|
| Typical size | $1-3M | $8-15M |
| Dilution | 15-25% | 15-20% |
| Timeline | 2-4 months | 3-6 months |

Pattern: Step-by-Step Lists

markdown

undefined

让内容便于AI解析与提取。

模式：对比表格

markdown

| 因素 | 种子轮 | A轮 |
|--------|------------|----------|
| 典型规模 | 100-300万美元 | 800-1500万美元 |
| 股权稀释 | 15-25% | 15-20% |
| 时间周期 | 2-4个月 | 3-6个月 |

模式：分步列表

markdown

undefined

How to Get a Warm Introduction

如何获得温暖引荐

Identify the connector - Find mutual connections on LinkedIn
Research the relationship - Ensure they actually know the investor
Craft the forwardable email - Make it easy to forward
Follow up appropriately - Wait 5-7 days before checking in


**Pattern: Definition Blocks**
```markdown
**Pro-rata rights** are the contractual right for existing investors to
maintain their ownership percentage in future funding rounds. For example,
if an investor owns 10% after seed, pro-rata rights let them invest enough
in Series A to still own 10%.

找到连接人 - 在LinkedIn上寻找共同联系人
研究关系 - 确保他们确实认识该投资者
撰写可转发邮件 - 让邮件便于转发
适时跟进 - 等待5-7天后再跟进


**模式：定义模块**
```markdown
**优先认购权**是现有投资者在未来融资轮次中维持其股权比例的合同权利。例如，如果投资者在种子轮后持有10%股权，优先认购权允许其在A轮融资中投入足够资金以保持10%的股权比例。

5.5 Entity Optimization

5.5 实体优化

Help AI models understand what/who you're talking about.

Name entities clearly:

❌ "The YC partner mentioned..."
✅ "Michael Seibel, Managing Director at Y Combinator, mentioned..."

Use consistent terminology:

Pick one and stick to it throughout:
- "seed round" (not "seed funding" then "seed stage" then "early round")
- "Series A" (not "A round" then "first institutional round")

Include relevant entities:

Company names (Y Combinator, Sequoia, a]6z)
People names (with titles)
Product names
Industry terms
Location when relevant

帮助AI模型理解你所提及的对象。

清晰命名实体：

❌ “YC合伙人提到...”
✅ “Y Combinator董事总经理Michael Seibel提到...”

使用统一术语：

选择一个术语并在全文中保持一致：
- “种子轮”（不要交替使用“种子融资”、“种子阶段”、“早期轮次”）
- “Series A”（不要交替使用“A轮”、“首次机构轮次”）

包含相关实体：

公司名称（Y Combinator、Sequoia、a16z）
人名（附带职位）
产品名称
行业术语
相关地点

5.6 Freshness Signals

5.6 时效性信号

AI models prefer recent, updated content.

Pattern: Dated Statistics

❌ "Most startups fail to raise Series A."
✅ "In 2024, only 33% of seed-funded startups raised Series A, down from 41% in 2021."

Pattern: Update Markers

markdown

*Last updated: January 2026*
*Data current as of Q4 2025*

Pattern: Trend Context

"Since the 2023 funding reset, investor behavior has shifted..."
"Post-ChatGPT, AI startups have seen 3x the investor interest..."

AI模型偏好近期更新的内容。

模式：带年份的统计数据

❌ “大多数初创公司无法获得A轮融资。”
✅ “2024年，仅33%的种子轮融资初创公司获得A轮融资，较2021年的41%有所下降。”

模式：更新标识

markdown

*最后更新：2026年1月*
*数据截至2025年第四季度*

模式：趋势背景

“自2023年融资环境重置以来，投资者行为发生了转变...”
“ChatGPT发布后，AI初创公司的投资者关注度提升了3倍...”

5.7 Comprehensive Coverage

5.7 全面覆盖

Be THE definitive resource on a topic so AI has no reason to cite others.

Cover all angles:

What it is (definition)
Why it matters (importance)
How to do it (tactical steps)
Common mistakes (what to avoid)
Examples (real cases)
FAQs (edge cases, specific questions)

Link to deeper content:

markdown

For more on term sheets, see our [Complete Guide to Term Sheet Negotiation](/blog/term-sheet-guide).

成为主题的权威资源，让AI无需引用其他内容。

覆盖所有维度：

定义（是什么）
重要性（为什么）
操作方法（怎么做）
常见误区（避免什么）
案例（真实案例）
常见问题（边缘情况、具体问题）

链接到深度内容：

markdown

如需了解更多关于条款清单的内容，请查看我们的《条款清单谈判完全指南》(/blog/term-sheet-guide)。

5.8 AIO Checklist

5.8 AIO审核清单

Content Type References

内容类型参考

For format-specific guidance, see:

references/blog-posts.md - Long-form article patterns
references/social-media.md - Platform-specific formats
references/press-releases.md - PR and announcements
references/ai-search-optimization.md - Deep dive on AIO tactics

如需特定格式指导，请查看：

references/blog-posts.md - 长篇文章模式
references/social-media.md - 平台特定格式
references/press-releases.md - 公关与公告格式
references/ai-search-optimization.md - AIO策略深度解析

Quick Reference: AI Phrases to Avoid

快速参考：需避免的AI风格表述

Replace these with natural alternatives:

Avoid	Use Instead
"In today's world"	[Specific recent event/trend]
"It's worth noting"	Just state the point directly
"Let's dive in"	[Omit or use specific transition]
"Game-changer"	[Specific impact with numbers]
"Leverage"	Use, apply, build on
"Unlock potential"	[Specific outcome]
"Cutting-edge"	[Describe what makes it new]
"Revolutionize"	[Specific change with evidence]
"Seamlessly"	[Describe the actual integration]
"Robust"	[Specific capability or feature]

用自然表述替代以下内容：

避免使用	替代表述
“在当今世界”	[具体近期事件/趋势]
“值得注意的是”	直接陈述观点
“让我们深入探讨”	[省略或使用具体过渡]
“改变游戏规则”	[带数字的具体影响]
“Leverage”	使用、应用、基于
“解锁潜力”	[具体成果]
“前沿”	[描述其创新点]
“彻底变革”	[带证据的具体变化]
“无缝”	[描述实际整合方式]
“强大”	[具体能力或特性]

Quick Reference: AIO Power Patterns

快速参考：AIO核心模式

Pattern	Example
Question header	"## How much equity should I give up in seed?"
Stat lead	"73% of successful founders did X, according to..."
Named framework	"The 3-3-3 Rule for warm introductions..."
Definition block	"Term sheet: A non-binding agreement that..."
Comparison table	"\| Seed \| Series A \| Difference \|"
Expert quote	"As [Name], [Title] at [Company], explains..."
Update marker	"Data current as of Q4 2025"

模式	示例
问题式标题	"## 种子轮应放弃多少股权？"
数据引领	"73%的成功创始人都做了X，根据..."
命名框架	"温暖引荐的3-3-3法则..."
定义模块	"条款清单：一份不具备约束力的协议，用于..."
对比表格	"\| 种子轮 \| A轮 \| 差异 \|"
专家引用	"正如[姓名]，[公司职位]所说..."
更新标识	"数据截至2025年第四季度"

undefined