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Analytics 7 minJuly 10, 2024

AI Intent Scoring vs. Classic Lead Scoring: What Actually Works

Compare traditional point-based scoring with AI-derived intent models built from PerksMate engagement data.

intent lead scoring analytics ai

Classic lead scoring assigns arbitrary points. AI intent scoring uses behavioral data from every agent touch.

Classic Model

  • +10 for webinar
  • +5 for email open
  • -5 for no reply in 14 days

AI Model

Feed engagement events (opens, clicks, replies, call outcomes) into a lightweight model hosted in Supabase Functions. It returns a 0-100 intent score.

Comparison Table

MetricClassicAI Intent
Setup timeHoursMinutes (auto)
Signal freshnessManual updatesReal-time
PersonalisationLowHigh (per ICP)

Action Triggers

When intent ≥ 80, start phone + LinkedIn agents. When intent drops below 40, move lead to nurture and send a value-add resource.

Implementation Tip

Use agent events as the single source of truth so marketing and sales read the same score.

Frequently Asked Questions

Do we need a data scientist?+

No. Start with a regression or even weighted average. Upgrade to ML once you collect a few thousand labeled events.

How often should intent scores refresh?+

Every time a tracked event occurs. Use Supabase's realtime channel to push updates into the dashboard instantly.

PM

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