PQL + Amplitude
高级
这是一个Lead Generation, AI Summarization领域的自动化工作流，包含 21 个节点。主要使用 Set, Code, Merge, Slack, Filter 等节点。 使用 Amplitude、Claude 和 PDL 评估产品合格潜在客户，用于销售路由
前置要求
- •Slack Bot Token 或 Webhook URL
- •HTTP Webhook 端点（n8n 会自动生成）
- •可能需要目标 API 的认证凭证
- •Anthropic API Key
使用的节点 (21)
工作流预览
可视化展示节点连接关系，支持缩放和平移
导出工作流
复制以下 JSON 配置到 n8n 导入，即可使用此工作流
{
"meta": {
"instanceId": "42b2652ebb0a87755df4710a5630695eec8e35cb0ce04a63b0e25751b1f044f1"
},
"name": "PQL + Amplitude",
"tags": [],
"nodes": [
{
"id": "66726c2e-0b01-4ea8-8024-a25221b0544d",
"name": "便签",
"type": "n8n-nodes-base.stickyNote",
"position": [
-864,
48
],
"parameters": {
"color": 4,
"width": 380,
"height": 340,
"content": "## 🎯 PQL 评分工作流"
},
"typeVersion": 1
},
{
"id": "665675ed-22b2-4bc6-b420-0ad5d7c26826",
"name": "Amplitude 群组 Webhook",
"type": "n8n-nodes-base.webhook",
"notes": "Fires instantly when user enters PQL cohort",
"position": [
-784,
400
],
"webhookId": "10ba6cb2-f402-43d4-a721-1d38f5073745",
"parameters": {
"path": "amplitude-pql-cohort",
"options": {},
"httpMethod": "POST"
},
"typeVersion": 1
},
{
"id": "99c46018-357d-488e-8a19-9621b79a0167",
"name": "便签1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-816,
560
],
"parameters": {
"color": 5,
"width": 320,
"height": 260,
"content": "## 📡 Amplitude 设置"
},
"typeVersion": 1
},
{
"id": "aa33ad91-737f-4aeb-af6e-ea803e43e8af",
"name": "解析 Webhook 数据",
"type": "n8n-nodes-base.code",
"notes": "Extracts user data + usage metrics from webhook",
"position": [
-576,
400
],
"parameters": {
"jsCode": "// Parse Amplitude cohort webhook payload\nconst payload = $json;\n\n// Extract first user from the batch (webhooks can send multiple)\nconst users = payload.users || [];\n\nif (users.length === 0) {\n throw new Error('No users in webhook payload');\n}\n\n// Process each user in the batch\nreturn users.map(user => {\n const email = user.user_id || user.user_properties?.email;\n \n if (!email) {\n throw new Error('No email found for user');\n }\n \n // Validate email\n const emailRegex = /^[^\\s@]+@[^\\s@]+\\.[^\\s@]+$/;\n if (!emailRegex.test(email)) {\n throw new Error(`Invalid email: ${email}`);\n }\n \n const domain = email.split('@')[1];\n const isFreeEmail = ['gmail.com', 'yahoo.com', 'hotmail.com', 'outlook.com'].includes(domain);\n \n return {\n json: {\n // User info\n email: email,\n name: user.user_properties?.name || user.user_properties?.full_name,\n userId: user.user_id,\n domain: domain,\n isFreeEmail: isFreeEmail,\n \n // Cohort context\n cohortName: payload.cohort_name,\n cohortId: payload.cohort_id,\n inCohort: payload.in_cohort,\n computedTime: payload.computed_time,\n \n // Usage data from Amplitude user properties\n usageData: {\n sessionCount: user.user_properties?.session_count || 0,\n lastSeen: user.user_properties?.last_seen,\n daysSinceSignup: user.user_properties?.days_since_signup,\n planType: user.user_properties?.plan_type || 'free',\n featuresUsed: user.user_properties?.features_used || [],\n teamSize: user.user_properties?.team_size || 1,\n apiCalls: user.user_properties?.api_calls_last_7d || 0,\n pricingPageViews: user.user_properties?.pricing_page_views || 0,\n teamInvitesSent: user.user_properties?.team_invites_sent || 0\n },\n \n timestamp: new Date().toISOString(),\n validationPassed: true\n }\n };\n});"
},
"typeVersion": 2
},
{
"id": "41bd0754-df78-4b46-b5fd-c70a08c21ab7",
"name": "过滤：仅限进入群组",
"type": "n8n-nodes-base.filter",
"notes": "Only process users ENTERING cohort, not exiting",
"position": [
-384,
400
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 1,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "191ec8a1-8105-4e08-9b75-a03c6a514c80",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{ $json.inCohort }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2
},
{
"id": "7a7929ef-e675-4840-977e-f2d5a859e8d0",
"name": "便签2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-400,
96
],
"parameters": {
"color": 6,
"width": 300,
"height": 280,
"content": "## 🔍 PDL 数据丰富"
},
"typeVersion": 1
},
{
"id": "64c56856-0127-492d-b455-c109c145b072",
"name": "PDL 数据丰富",
"type": "n8n-nodes-base.httpRequest",
"notes": "Enriches with company/person data",
"position": [
-192,
400
],
"parameters": {
"url": "https://api.peopledatalabs.com/v5/person/enrich",
"options": {},
"sendQuery": true,
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"queryParameters": {
"parameters": [
{
"name": "email",
"value": "={{ $json.email }}"
},
{
"name": "pretty",
"value": "true"
}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "JAhnxxCoDQgWyILm",
"name": "Serp AI API"
}
},
"typeVersion": 4.2,
"continueOnFail": true
},
{
"id": "e87ac8db-48d1-4f05-b0b4-dcca9f848329",
"name": "便签3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-48,
-48
],
"parameters": {
"color": 2,
"width": 280,
"height": 304,
"content": "## 🔎 公司调研"
},
"typeVersion": 1
},
{
"id": "c775f858-6e66-4716-9d86-6b3d6bea7823",
"name": "公司研究",
"type": "n8n-nodes-base.perplexity",
"position": [
48,
272
],
"parameters": {
"options": {},
"messages": {
"message": [
{
"content": "=Research {{ $json.data.job_company_name }} for product-led growth context.\n\nFocus on:\n1. Company growth stage and funding\n2. Tech stack and product complexity\n3. Team size and structure\n4. Expansion signals (hiring, new offices)\n5. Budget indicators\n\nProvide under 150 words.\n\nFormat:\n**COMPANY STAGE:** [Growth stage, funding, maturity]\n**TECH SOPHISTICATION:** [Tech stack, product complexity]\n**EXPANSION SIGNALS:** [Hiring, growth indicators]\n**BUDGET INDICATORS:** [High/Medium/Low likelihood to pay]"
}
]
},
"requestOptions": {}
},
"credentials": {
"perplexityApi": {
"id": "zcUXOu9Mm9oaXJep",
"name": "Perplexity account"
}
},
"typeVersion": 1,
"continueOnFail": true
},
{
"id": "0fca7a25-1940-4643-a699-33482bebd526",
"name": "合并所有来源",
"type": "n8n-nodes-base.merge",
"position": [
288,
384
],
"parameters": {},
"typeVersion": 3.2
},
{
"id": "dec4ca1e-0f6a-4382-8d3a-85565dc94ce7",
"name": "合并 PQL 数据",
"type": "n8n-nodes-base.code",
"position": [
448,
384
],
"parameters": {
"jsCode": "// MERGE USAGE + ENRICHMENT DATA\nconst inputs = $input.all();\n\nconst enrichedPQL = {\n user: {\n email: null,\n name: null,\n userId: null\n },\n usage: {},\n enrichment: {\n pdl: {},\n company: {}\n },\n cohort: {\n name: null,\n id: null\n },\n metadata: {\n enrichmentTimestamp: new Date().toISOString(),\n sourcesSuccessful: [],\n sourcesFailed: []\n }\n};\n\ninputs.forEach((input, index) => {\n const data = input.json;\n \n // Input 0: Company research\n if (index === 0 && data.choices?.[0]?.message?.content) {\n const content = data.choices[0].message.content;\n enrichedPQL.enrichment.company = {\n rawResearch: content,\n companyStage: extractSection(content, 'COMPANY STAGE'),\n techSophistication: extractSection(content, 'TECH SOPHISTICATION'),\n expansionSignals: extractSection(content, 'EXPANSION SIGNALS'),\n budgetIndicators: extractSection(content, 'BUDGET INDICATORS')\n };\n enrichedPQL.metadata.sourcesSuccessful.push('Company Research');\n }\n \n // Input 1: PDL data\n else if (index === 1 && data && !data.error) {\n const pdl = data.data || data;\n enrichedPQL.enrichment.pdl = {\n fullName: pdl.full_name,\n jobTitle: pdl.job_title,\n companyName: pdl.job_company_name,\n companySize: pdl.job_company_size,\n industry: pdl.job_company_industry,\n seniorityLevel: pdl.job_title_levels,\n linkedinUrl: pdl.linkedin_url,\n location: pdl.location_name\n };\n enrichedPQL.user.name = pdl.full_name;\n enrichedPQL.metadata.sourcesSuccessful.push('PDL');\n }\n \n // Input 2: Amplitude webhook data\n else if (index === 2 && data.validationPassed) {\n enrichedPQL.user.email = data.email;\n enrichedPQL.user.userId = data.userId;\n enrichedPQL.user.name = enrichedPQL.user.name || data.name;\n enrichedPQL.usage = data.usageData;\n enrichedPQL.cohort = {\n name: data.cohortName,\n id: data.cohortId\n };\n enrichedPQL.metadata.sourcesSuccessful.push('Amplitude');\n }\n});\n\nconst qualityScore = calculateQuality(enrichedPQL);\nenrichedPQL.metadata.dataQualityScore = qualityScore;\n\nfunction extractSection(text, header) {\n const regex = new RegExp(`\\\\*\\\\*${header}:\\\\*\\\\*\\\\s*([^\\\\n*]+)`, 'i');\n const match = text.match(regex);\n return match ? match[1].trim() : 'N/A';\n}\n\nfunction calculateQuality(data) {\n let score = 0;\n if (data.enrichment.pdl.fullName) score += 25;\n if (data.usage.sessionCount > 0) score += 25;\n if (data.enrichment.company.companyStage !== 'N/A') score += 25;\n if (data.enrichment.pdl.companySize) score += 25;\n return score;\n}\n\nreturn [{ json: enrichedPQL }];"
},
"typeVersion": 2
},
{
"id": "1ac94f52-f1db-4cd3-b015-d6170dd10cdb",
"name": "便签4",
"type": "n8n-nodes-base.stickyNote",
"position": [
528,
0
],
"parameters": {
"color": 3,
"width": 340,
"height": 364,
"content": "## 🤖 AI 评分代理"
},
"typeVersion": 1
},
{
"id": "07721f11-f4ae-49cb-905c-aa8a876a2d78",
"name": "PQL 评分代理",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
592,
384
],
"parameters": {
"text": "=You are a PQL (Product-Qualified Lead) scoring AI with access to usage data and ICP rules.\n\nCRITICAL: Use the Google Docs tool to fetch the PQL criteria document before scoring.\n\nPQL Data:\n{{ JSON.stringify($json, null, 2) }}\n\nSCORING PROCESS:\n1. Fetch PQL criteria from the doc\n2. Score each component:\n - Usage Intensity (0-3): Based on session count, feature adoption, engagement\n - ICP Fit (0-3): Company size, industry, seniority match\n - Intent Signals (0-2): Pricing page views, team invites, integration usage\n - Timing (0-2): Recent activity spikes, expansion signals\n3. Calculate pqlScore = usageIntensity + icpFit + intentSignals + timing\n4. Determine routing:\n - 8-10 = \"hot\" (immediate sales handoff)\n - 5-7 = \"warm\" (SDR nurture sequence)\n - 0-4 = \"cold\" (automated education drip)\n\nReturn ONLY valid JSON (no markdown):\n{\n \"email\": \"extract from user.email\",\n \"name\": \"extract from enrichment.pdl.fullName\",\n \"title\": \"extract from enrichment.pdl.jobTitle\",\n \"companyName\": \"extract from enrichment.pdl.companyName\",\n \"companySize\": \"extract from enrichment.pdl.companySize\",\n \"industry\": \"extract from enrichment.pdl.industry\",\n \"usageIntensity\": \"high|medium|low\",\n \"usageSummary\": \"Brief summary of product usage\",\n \"pqlScore\": sum of breakdown scores,\n \"scoreBreakdown\": {\"usageIntensity\": 0-3, \"icpFit\": 0-3, \"intentSignals\": 0-2, \"timing\": 0-2},\n \"icpMatch\": {\"companySizeMatch\": true/false, \"industryMatch\": true/false},\n \"keyInsights\": [\"insight1\", \"insight2\"],\n \"handoffRecommendation\": \"specific sales advice\",\n \"conversationStarters\": [\"starter1\", \"starter2\"],\n \"redFlags\": [\"flag1\"] or [],\n \"nextAction\": \"immediate_sales_call|sdr_nurture|education_drip\",\n \"confidenceLevel\": \"high|medium|low\",\n \"routingCategory\": \"hot\" if 8-10, \"warm\" if 5-7, \"cold\" if 0-4\n}",
"options": {},
"promptType": "define"
},
"typeVersion": 2.2
},
{
"id": "7213fb59-b881-45a8-81ac-d8a230e39487",
"name": "思考",
"type": "@n8n/n8n-nodes-langchain.toolThink",
"position": [
704,
608
],
"parameters": {},
"typeVersion": 1.1
},
{
"id": "49a71d70-2f0f-4253-832d-1f57e06e0012",
"name": "Anthropic 聊天模型",
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"position": [
592,
592
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "claude-sonnet-4-20250514",
"cachedResultName": "Claude 4 Sonnet"
},
"options": {}
},
"typeVersion": 1.3
},
{
"id": "072fa1a8-88fd-4e71-957b-85ee27ac5fdf",
"name": "解析和结构化 PQL",
"type": "n8n-nodes-base.set",
"position": [
880,
384
],
"parameters": {
"mode": "raw",
"options": {},
"jsonOutput": "={{ $json.output }}"
},
"typeVersion": 3.4
},
{
"id": "ab8e61f7-75ad-4c3f-afef-ea6d015bb897",
"name": "便签5",
"type": "n8n-nodes-base.stickyNote",
"position": [
608,
768
],
"parameters": {
"width": 496,
"height": 388,
"content": "## 📋 ICP 标准文档"
},
"typeVersion": 1
},
{
"id": "27896435-f5a1-4495-959e-1928f0584fc2",
"name": "格式化热门 PQL Slack",
"type": "n8n-nodes-base.set",
"position": [
1072,
384
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "c1d2e3f4",
"name": "prompt",
"type": "string",
"value": "=Format this PQL alert for Slack:\n\n{{ JSON.stringify($json, null, 2) }}\n\nCreate an engaging alert with:\n- 🔥 emoji for hot leads (score 8-10)\n- ⚡ emoji for warm leads (score 5-7)\n- Lead name, company, title\n- PQL score and key insights\n- Conversation starters for sales\n- Next action recommendation\n\nUse Slack markdown (bold with *text*, bullets with •)"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "8bc7b1ef-3ef2-4bf2-9c67-661a8a56bdda",
"name": "便签6",
"type": "n8n-nodes-base.stickyNote",
"position": [
1120,
16
],
"parameters": {
"color": 7,
"width": 340,
"height": 348,
"content": "## 💬 Slack 提醒"
},
"typeVersion": 1
},
{
"id": "98c21e06-e44d-4298-add2-f8f78892fcc7",
"name": "发送热门 PQL 提醒",
"type": "n8n-nodes-base.slack",
"notes": "⚠️ UPDATE CHANNEL ID: Replace YOUR_SLACK_CHANNEL with your actual Slack channel ID",
"position": [
1248,
384
],
"webhookId": "a9aab25e-dacf-4875-8047-c332367c3684",
"parameters": {
"text": "={{ $json.content.parts[0].text }}",
"select": "channel",
"channelId": {
"__rl": true,
"mode": "id",
"value": "YOUR_SLACK_CHANNEL"
},
"otherOptions": {},
"authentication": "oAuth2"
},
"typeVersion": 2.3
},
{
"id": "1f833363-5bea-4023-a403-f09f07c77374",
"name": "ICP 指南",
"type": "n8n-nodes-base.googleDocsTool",
"position": [
816,
608
],
"parameters": {
"operation": "get"
},
"credentials": {
"googleDocsOAuth2Api": {
"id": "UxwVvTjaY2WY3bMb",
"name": "Google Docs account"
}
},
"typeVersion": 2
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "",
"connections": {
"Think": {
"ai_tool": [
[
{
"node": "PQL Scoring Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"PDL Enrich": {
"main": [
[
{
"node": "Company Research",
"type": "main",
"index": 0
},
{
"node": "Merge All Sources",
"type": "main",
"index": 1
}
]
]
},
"ICP Guidelines": {
"ai_tool": [
[
{
"node": "PQL Scoring Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Merge PQL Data": {
"main": [
[
{
"node": "PQL Scoring Agent",
"type": "main",
"index": 0
}
]
]
},
"Company Research": {
"main": [
[
{
"node": "Merge All Sources",
"type": "main",
"index": 0
}
]
]
},
"Merge All Sources": {
"main": [
[
{
"node": "Merge PQL Data",
"type": "main",
"index": 0
}
]
]
},
"PQL Scoring Agent": {
"main": [
[
{
"node": "Parse & Structure PQL",
"type": "main",
"index": 0
}
]
]
},
"Parse Webhook Data": {
"main": [
[
{
"node": "Filter: Entering Cohort Only",
"type": "main",
"index": 0
}
]
]
},
"Anthropic Chat Model": {
"ai_languageModel": [
[
{
"node": "PQL Scoring Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Format Hot PQL Slack": {
"main": [
[
{
"node": "Send Hot PQL Alert",
"type": "main",
"index": 0
}
]
]
},
"Parse & Structure PQL": {
"main": [
[
{
"node": "Format Hot PQL Slack",
"type": "main",
"index": 0
}
]
]
},
"Amplitude Cohort Webhook": {
"main": [
[
{
"node": "Parse Webhook Data",
"type": "main",
"index": 0
}
]
]
},
"Filter: Entering Cohort Only": {
"main": [
[
{
"node": "PDL Enrich",
"type": "main",
"index": 0
}
]
]
}
}
}常见问题
如何使用这个工作流？
复制上方的 JSON 配置代码，在您的 n8n 实例中创建新工作流并选择「从 JSON 导入」，粘贴配置后根据需要修改凭证设置即可。
这个工作流适合什么场景？
高级 - 潜在客户开发, AI 摘要总结
需要付费吗？
本工作流完全免费，您可以直接导入使用。但请注意，工作流中使用的第三方服务（如 OpenAI API）可能需要您自行付费。
相关工作流推荐
使用AI丰富线索并评分
使用Claude AI、PDL和Perplexity自动丰富和评分线索
Code
Gmail
Merge
+13
28 节点Connor Provines
自动化竞争对比卡生成与实时销售情报
使用AI、Slack和Notion自动生成竞争对比卡（Klue替代方案）
Code
Merge
Slack
+15
58 节点Connor Provines
市场调研
潜在客户开发与邮件工作流
使用Google Maps、SendGrid和AI自动化B2B潜在客户开发与邮件营销
If
Set
Code
+21
141 节点Ezema Kingsley Chibuzo
潜在客户开发
在可视化参考库中探索n8n节点
在可视化参考库中探索n8n节点
If
Ftp
Set
+93
113 节点I versus AI
其他
基于AI的会议研究与每日议程（Google日历、Attio CRM和Slack）
基于AI的会议研究与每日议程：使用Google日历、Attio CRM和Slack
If
Set
Code
+15
30 节点Harry Siggins
AI 摘要总结
自动化会议准备
使用 GPT-5 和 Gemini 研究从日历到 Slack 通过 Attio CRM 自动准备会议
If
Set
Code
+16
39 节点Harry Siggins
AI 摘要总结
工作流信息
难度等级
高级
节点数量21
分类2
节点类型13
作者
Connor Provines
@connorprovinesOver the past 10+ years, I've led marketing initiatives for B2B SaaS companies at every stage, from initial market entry (0→1) through scaled growth (1→10). My approach is grounded in a simple principle: strategic thinking paired with hands-on execution. I focus on building sustainable growth engines, not just campaigns. Whether it's positioning a new product, optimizing conversion funnels, or scaling demand generation, I bring both the framework and the tactical expertise to move fast and win.
外部链接
在 n8n.io 查看 →
分享此工作流