Funding Signal Outreach

Funding Signal Outreach

Monitors and acts on funding announcements from companies matching ICP. For each funded company, researches what they will likely need post-funding, matches needs to agency services, scores timing urgency, and drafts personalized outreach referencing their round. Outputs qualified leads with funding context and ready-to-send messages.

Prerequisites

• agency.config.json in the project root
• WebSearch tool for finding funding announcements
• Optional: company-researcher for deep company analysis
• Optional: cold-email-drafter for polished email generation
• Optional: person-researcher for finding the right contact

Capabilities Used

1. company-researcher -- for deep-dive on funded companies
2. person-researcher -- for identifying decision-makers at funded companies
3. cold-email-drafter -- for generating polished outreach emails
4. lead-scorer -- for scoring the funded company against ICP
5. crm-writer -- for logging qualified leads to CRM

Phase 0: Read Config

1. Read agency.config.json from the project root.
2. Extract ICP definition:
   • icp.segments[] -- target segments with industry, size, geography
   • icp.geography -- target geographies
   • icp.company_size -- revenue or employee range
3. Extract services[] -- services to match against post-funding needs.
4. Extract outreach.tone and outreach.banned_phrases for email drafting.
5. Extract case_studies[] for proof points relevant to funded companies.
6. Check tools.research for data source preferences.

Phase 1: Search for Funding Announcements

Search for recent funding events matching ICP:

Search queries (via WebSearch):

- "[industry] funding announcement [current_month] [current_year]"
- "[industry] Series A OR Series B OR seed round [geography]"
- "D2C brand funding [geography] [current_year]"
- "e-commerce startup funding round [current_month]"
- site:techcrunch.com "[industry] funding [current_year]"
- site:crunchbase.com "[industry] funding rounds"
- "[geography] startup funding news this week"

Additional sources to check:

• Crunchbase recent rounds (via WebSearch: site:crunchbase.com/funding_round)
• TechCrunch funding coverage
• Inc42 (for India), TechInAsia (for Asia)
• Press releases on PR Newswire / BusinessWire
• LinkedIn funding announcements

For each result, extract:

Company: [name]
Round: [Seed / Series A / Series B / etc.]
Amount: $[X]M
Date: [announcement date]
Investors: [lead investor(s)]
Industry: [sector]
Geography: [HQ location]
Website: [URL]
Source: [where we found this]

Phase 2: Filter and Match to ICP

Score each funded company against ICP:

ICP MATCH SCORING
===
Company          | Industry Match | Geo Match | Size Match | ICP Score | Status
-----------------|---------------|-----------|------------|-----------|--------
FreshD2C         | D2C (exact)   | India     | Series A   | 95/100    | STRONG
GlowSkin         | Skincare D2C  | US        | Seed       | 80/100    | GOOD
TechWidget       | SaaS (miss)   | India     | Series B   | 30/100    | SKIP
SportyBrand      | Sports D2C    | UK        | Series A   | 85/100    | GOOD

Discard companies with ICP score below 50. Proceed with matches.

Phase 3: Post-Funding Needs Analysis

For each qualified company, predict what they need post-funding:

Post-funding need patterns by round:

Research each company (via WebSearch and company-researcher):

POST-FUNDING NEEDS ASSESSMENT: [Company Name]
===
Round: Series A ($5M)
Current website: [URL] -- quality assessment
Current Shopify store: [yes/no, theme quality]
Current team size: [N] (check LinkedIn)
Open positions: [roles being hired -- indicates gaps]
Recent press: [what they say they'll use funds for]

Predicted needs:
1. [Need 1 -- e.g., "Store revamp -- current site is basic Shopify theme"]
2. [Need 2 -- e.g., "CRO -- scaling traffic without optimized conversion"]
3. [Need 3 -- e.g., "Catalog management -- expanding from 50 to 200 SKUs"]

Service match:
- [Your service 1] matches need [1] -- relevance: HIGH
- [Your service 2] matches need [2] -- relevance: HIGH

Timing urgency: HIGH (Series A companies typically spend on growth within 3 months of closing)

Phase 4: Score and Rank Leads

Score each lead on:

LEAD SCORING
===
Company     | ICP Fit | Funding Recency | Need Match | Timing | Total Score
------------|---------|-----------------|------------|--------|------------
FreshD2C    | 95      | 5 days ago      | 3 services | HIGH   | 92/100
SportyBrand | 85      | 12 days ago     | 2 services | HIGH   | 85/100
GlowSkin    | 80      | 30 days ago     | 2 services | MEDIUM | 72/100

Scoring weights:

• ICP fit: 30%
• Funding recency (prefer last 30 days): 25%
• Service need match: 25%
• Timing urgency: 20%

Phase 5: Draft Personalized Outreach

For each qualified lead, draft outreach using the Signal-Proof-Ask framework:

Email structure:

Subject: Congrats on the [round] -- [specific observation]

[Reference the funding]: "Saw [Company] just closed [round] -- congrats.
[Most companies at this stage face X]."

[Match to their need]: "With [amount raised], you're likely [scaling/revamping/expanding].
We've helped [similar company] do exactly that."

[Proof point]: "[Case study result -- specific metric]."

[Soft CTA]: "Worth a quick look at how this could work for [Company]?"

Generate for each lead:

1. Email draft (using cold-email-drafter if available)
2. LinkedIn connection note (under 300 chars)
3. LinkedIn message (if already connected)

Personalization must include:

• The specific round and amount
• A specific observation about their current website/store
• A relevant case study matching their industry
• A specific service recommendation based on their needs

Phase 6: Output

Return structured JSON:

{
  "funding_signal_outreach": {
    "search_date": "2024-03-15",
    "search_criteria": {
      "industries": ["D2C", "e-commerce"],
      "geographies": ["India", "US", "UK"],
      "round_types": ["Seed", "Series A", "Series B"],
      "recency": "last 30 days"
    },
    "funding_events_found": 15,
    "icp_matches": 8,
    "qualified_leads": [
      {
        "company": "FreshD2C",
        "website": "https://freshd2c.com",
        "round": "Series A",
        "amount": "$5M",
        "date": "2024-03-10",
        "investors": ["Sequoia India"],
        "icp_score": 92,
        "predicted_needs": ["store revamp", "CRO", "catalog management"],
        "service_matches": ["Shopify development", "CRO optimization"],
        "timing_urgency": "high",
        "contacts": [
          {
            "name": "Founder Name",
            "title": "CEO",
            "linkedin": "URL",
            "email": "email@freshd2c.com"
          }
        ],
        "outreach": {
          "email_subject": "",
          "email_body": "",
          "linkedin_note": "",
          "linkedin_message": ""
        }
      }
    ],
    "summary": {
      "total_qualified": 5,
      "total_outreach_drafted": 5,
      "top_opportunity": "FreshD2C -- Series A, strong ICP match, 3 service needs"
    }
  }
}

Log qualified leads to CRM via crm-writer (Researched Leads tab) with source tagged as "funding_signal."

Example Usage

Trigger phrases:

• "Find companies that just raised funding in our ICP"
• "Search for D2C funding announcements this month"
• "Funding signal outreach for this week"
• "Which startups just got funded that we should reach out to?"
• "Find recently funded e-commerce companies in India"

User: Find recently funded D2C companies we should reach out to
Assistant: [searches for D2C funding in last 30 days, finds 15 events, filters to 5 ICP matches, researches each company's website and needs, drafts personalized outreach referencing their specific round and current store gaps, logs to CRM]

User: Any new funding rounds in Indian e-commerce this week?
Assistant: [searches India-focused funding news, finds 3 new rounds, scores against ICP, identifies 2 strong matches, drafts outreach for each with relevant case studies]