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Sales & RevOps

Pre-Qualified Lead Discovery

Autonomous generation of high-integrity lead lists with provenance tracking and evidence-based qualification.

Configure Qualification Parameters

The Problem

  • •Utilization Leakage: SDRs and AEs allocate 30-40% of capacity to manual research and data validation rather than revenue-generating outreach.
  • •Database Decay: Third-party lead dumps suffer from high bounce rates and stale employment data, damaging domain reputation.
  • •The 'Black Box' Problem: Leadership lacks visibility into the qualification logic—leads appear in the CRM without an audit trail or contextual justification.

How It Works

The agent executes continuous, autonomous prospecting cycles. It ingests unstructured signals, validates employment status via workforce intelligence, and appends a 'Contextual Justification' field to every record before CRM insertion.

1

Parametric Calibration: Define strict inclusion/exclusion parameters based on ICP: seniority, functional role, geography, and technographic markers.

2

Signal Ingestion: Monitor disparate unstructured sources (association directories, conference attendee lists, niche job boards) to identify high-intent targets not yet saturated in commodity databases.

3

Enrichment & Verification: Cross-reference entities against Data Partners workforce metrics to verify current employment status, hiring velocity context, and head-count growth.

Data Sources

Unstructured Web Data (Conference sites, Public PDFs, Association Directories)Data Partners (Workforce dynamics, employment validation, growth metrics)CRM (Salesforce/HubSpot) for exclusion logic and ownership routing

Success Metrics

  • Increase in 'Golden Window' capture (speed-to-outbound).
  • Reduction in CAC via reallocation of SDR hours from research to execution.
  • Higher deliverability and meeting conversion rates due to verified employment status.

ROI Calculator

Your Inputs

  • 1
    Headcount (SDR/BDR)
  • 2
    Research Load (Hours/Week/Rep)
  • 3
    Fully Loaded Hourly Cost
  • 4
    Maai Automation Efficiency (0.7 - 0.9)

Formula

Operational Savings = (Headcount × Research_Hours × 52) × Automation_Efficiency

Example Output

For a 5-person SDR team averaging 10 hours of research/week: ~1,820 hours/year reallocated to active pipeline generation.

Implementation Timeline

1
Weeks 1-2

Calibration (Weeks 1-2): Define ICP parameters, map unstructured sources, and configure Data Partners API integration.

2
Weeks 3-4

Validation (Weeks 3-4): Execute initial discovery cycles; audit lead quality and 'Contextual Justification' accuracy with RevOps leadership.

3
Week 5+

Steady State (Week 5+): Enable autonomous CRM injection and continuous background replenishment.

Coming Soon

  • ◆Propensity Scoring: Weighting leads based on Data Partners 'Engineering Hiring' spikes.
  • ◆Dynamic Playbooks: Automating sequence assignment based on the specific data source (e.g., 'Conference Follow-up' vs. 'Hiring Surge' sequence).
  • ◆Territory Top-Ups: Trigger-based replenishment of lead pools when penetration falls below a set threshold.

Eliminate the trade-off between lead volume and lead quality. The Pre-Qualified Lead Discovery Agent delivers a continuous stream of validated, context-rich contacts, allowing your sales team to focus entirely on conversion mechanics.

Configure Qualification Parameters

Pre-Qualified Lead Discovery

AUTONOMOUS AGENT

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