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signal-detection-pipeline

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Signal Detection Pipeline

购买信号识别流程

Monitor multiple signal sources to find companies actively in-market for your client's solution. Combine signals for higher-confidence leads.
监控多类信号来源，寻找积极寻求客户解决方案的目标企业。结合多类信号以筛选出高可信度的潜在客户。

When to Use

适用场景

  • "Find companies that might need [our product]"
  • "Run signal detection for [problem area]"
  • "Find buying signals in [industry/topic]"
  • "寻找可能需要[我们产品]的企业"
  • "针对[问题领域]进行信号识别"
  • "在[行业/主题]中寻找购买信号"

Signal Sources

信号来源

Run the sources relevant to the client's ICP. Each is independent — run in parallel.
根据客户的ICP（理想客户画像）运行相关来源。各来源相互独立，可并行运行。

Job Posting Signals (Strongest)

招聘信息信号（优先级最高）

Skill: job-posting-intent
Companies hiring for roles in the problem area = budget allocated and pain acknowledged.
  • Input: Job keywords, ICP criteria
  • Output: Qualified companies with outreach angles
Skill: job-posting-intent
企业招聘相关问题领域的岗位 = 已分配预算且明确痛点。
  • 输入：招聘关键词、ICP筛选条件
  • 输出：带有触达切入点的合格企业列表

Funding Signals

融资信号

Skill: funding-signal-monitor
Recently funded companies = budget available, growth mandate.
  • Input: Industry, funding stage filter
  • Output: Funded companies with timing context
Skill: funding-signal-monitor
近期获得融资的企业 = 有可用预算、增长需求。
  • 输入：行业、融资阶段筛选条件
  • 输出：带有时间背景的融资企业列表

Conference Attendance Signals

会议参会信号

Skill: luma-event-attendees
People attending events in the problem space = actively engaged.
  • Input: Event URLs or topic search
  • Output: Person/company list
Skill: luma-event-attendees
参与相关问题领域活动的人群 = 高度关注该领域。
  • 输入：活动URL或主题搜索词
  • 输出：个人/企业列表

Reddit Pain Signals

Reddit痛点信号

Skill: reddit-post-finder
People complaining about or discussing the problem = experiencing the pain.
  • Input: Keywords, relevant subreddits
  • Output: Posts with authors, context
Skill: reddit-post-finder
用户抱怨或讨论相关问题 = 正面临该痛点。
  • 输入：关键词、相关子版块
  • 输出：包含作者及背景的帖子列表

LinkedIn Content Signals

LinkedIn内容信号

Skill: linkedin-post-research + linkedin-commenter-extractor
People posting about or engaging with the problem = thought leaders or practitioners.
  • Input: Keywords, time frame
  • Output: Posters and commenters with engagement data
Skill: linkedin-post-research + linkedin-commenter-extractor
发布或参与相关问题讨论的用户 = 意见领袖或从业者。
  • 输入：关键词、时间范围
  • 输出：带有互动数据的发帖者及评论者列表

Combining Signals

信号整合

After running relevant sources:
  1. Deduplicate companies appearing across multiple signals (multi-signal = strongest leads)
  2. Score each lead: assign signal strength based on source quality and recency
    • Job posting + funding = highest intent
    • LinkedIn post + Reddit complaint = validated pain
    • Single conference attendance = lowest (awareness only)
  3. Enrich top leads with web search for company details
  4. Consolidate into a single Google Sheet: Company, Signal Sources, Signal Strength, Context, Outreach Angle
  5. Prioritize companies with multiple signal types
运行相关来源后：
  1. 去重：合并在多类信号中出现的企业（多信号 = 高意向潜在客户）
  2. 评分：根据信号来源质量和时效性为每个潜在客户打分
    • 招聘信息 + 融资 = 最高意向
    • LinkedIn帖子 + Reddit抱怨 = 已验证痛点
    • 单一会议参会 = 最低（仅为认知阶段）
  3. 补充信息：通过网络搜索补充优质潜在客户的企业详情
  4. 整合汇总：将信息汇总至单个Google Sheet，包含：企业名称、信号来源、信号强度、背景信息、触达切入点
  5. 优先级排序：优先处理带有多类信号的企业

Human Checkpoints

人工审核节点

  • After combining signals: Review consolidated list before outreach
  • 信号整合后：在触达前审核汇总列表