How Raregap finds non-obvious B2B buyers

# How Raregap finds non-obvious B2B buyers

Most prospecting tools scrape LinkedIn and filter by job title. Raregap looks deeper.

## The insight

The best buyers aren't always the obvious ones. Example:

**Bad targeting**: "VP of Sales at 50-500 employee SaaS companies"

**Good targeting**: "Companies that just raised Series A, hired their first sales engineer, and posted about 'scaling outbound'"

Raregap finds the second group.

## How it works

### 1. Multi-signal ingestion

We pull:
- Hiring patterns (roles, seniority, timing)
- Tech stack changes (via job postings, case studies)
- Content signals (blog posts, podcasts, webinars)
- Funding events (even small seed extensions)

### 2. LLM-powered classification

Given your ICP description ("Companies struggling with sales productivity"), we:
- Generate search queries for each signal type
- Classify results as "strong fit" / "weak fit" / "not relevant"
- Cross-reference signals (hiring + funding + content = hotter lead)

### 3. Enrichment + export

For qualified leads, we:
- Enrich with email, LinkedIn, company size
- Export to CSV or push directly to CRM
- Provide "why this lead" context for SDRs

## Results

Pilot customers (3 GTM tools):
- 320+ qualified leads per week (vs 80-100 with manual research)
- 22% reply rate (vs 8% industry average)
- 40% reduction in SDR research time

## Key learning

The best leads aren't hiding. They're just not searched for correctly. LLMs make intent discovery programmable.

## Status

Raregap is open to acquisition or partnerships with sales tools. Integration plan ready.