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[case_004] · § Marketing · Advanced

AI Lead Scoring Engine — 3× qualified lead increase.

ML model that scores and ranks inbound leads in real time, integrating with your CRM to surface the highest-value prospects instantly.

PythonScikit-learnCRM APIFastAPIPostgresAWS

client · B2B SaaS · NDA

  • [1] · qualified leads
    3×
  • [2] · model turnaround
    72h
  • [3] · roc-auc holdout
    0.89
  • [4] · prod timeline
    11w
AI Lead Scoring Engine — fig. 01 illustration

fig. 01 · ai lead scoring engine accent = 3× qualified lead increase

[01]
§ Challenge

Challenge

400+ inbound leads per week across paid, organic, and partner channels. Sales triaging manually with a legacy lead-grade system everyone admitted was stale. High-intent prospects sitting in queue for days.

[02]
§ Approach

Approach

Gradient-boosted classifier trained on 18 months of historical opportunities. Firmographic features (company size, industry, region) paired with behavioral signals (pages viewed, time-to-convert, content depth). Retrains weekly against closed-won/closed-lost outcomes.

[03]
§ Outcome

Outcome

Sales working a ranked queue instead of a chronological one. Response time on top-tier leads from 12h to under 3h. Close rate on A-grade leads lifted 38% QoQ.

"They didn't pitch us an AI project. They pitched us three more closed-won deals per week — and delivered it."

— VP Revenue Operations · B2B SaaS (NDA)

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