Home → Insights → AI Lead Gen

Lead Scoring Model Implementation

A production lead scoring model combines explicit (form) and implicit (page views, content downloads) signals with decay over time.

Direct answer: A production lead scoring model combines explicit (form) and implicit (page views, content downloads) signals with decay over time.

Model Components

Explicit: quiz answers, form fields. Implicit: pricing page visits, case study reads, return visits. Negative: competitor job title, student email domains.

Decay Function

Scores decay 10% per week without engagement. Re-engagement resets decay. Prevents stale 'hot' leads.

Thresholds

MQL: 70+. SQL: 85+. Adjust per sales capacity. Too low = SDR burnout. Too high = missed pipeline.

Tooling

HubSpot lead scoring, MadKudu, or custom in CRM. Sync with marketing automation for nurture triggers.

Key Insight: Build hub-and-spoke content around AI Lead Gen—single pages rarely win in AI synthesis or traditional SERPs.

Related Articles

Pillar Service

Next Step

Need AI Lead Gen for Your Brand?

DIG Marketing engineers AI-native marketing systems from Pune for India and global markets.