Lead scoring
AI lead scoring is the practice of ranking leads by how likely they are to buy, using a model that weighs behavioral and intent signals — email opens, page visits, replies, fit — instead of a fixed manual point system. It tells sales which leads to work first, so effort lands on the buyers most ready to move. In dolv, lead scoring runs as intent-signal scoring on the built-in CRM, read against one unified funnel scored on a rolling 30-day baseline.
What AI lead scoring actually is
Not every lead is worth the same effort. One downloaded a checklist and went quiet; another booked a demo, visited pricing twice, and replied to your last email. Lead scoring is how you tell them apart — assigning each lead a number that ranks how likely they are to buy, so sales spends its hours on the buyers most ready to move. Done well, it turns a flat list of names into a prioritized queue and answers one question every rep is already asking: who should I call first?
The difference with AI lead scoring is where the weights come from. Traditional scoring is a hand-built point system — plus ten for a demo request, plus five for an industry — and those rules drift out of date the moment buying behavior shifts. AI lead scoring instead learns which signals actually precede a closed deal and weights them automatically, so the score reflects real intent rather than a guess someone made once. We walk through how to build one in the guide to AI lead scoring.
Why lead scoring matters
Without scoring, sales works leads in the order they arrive, which means high-intent buyers wait behind tire-kickers and the best opportunities go cold. Scoring fixes the order: it surfaces the leads worth a same-day call, flags the ones to nurture, and keeps reps from burning a morning on names that were never going to convert. For revenue teams, that's the difference between a pipeline that's busy and one that's productive — the kind of prioritization that turns marketing effort into booked meetings. It's also a core building block of any modern AI sales motion.
How dolv does lead scoring
In dolv, lead scoring isn't a static field on a record — it lives inside a grounded command center. Live signal flows from 30 read-and-write integrations: Gmail, Calendar, GA4, Search Console, LinkedIn, and the Google, Meta, and LinkedIn ad platforms, all landing on the built-in CRM. dolv runs intent-signal lead scoring on that connected data, then reads every score against one unified TOFU/MOFU/BOFU funnel scored on a rolling 30-day baseline (weighted composite health: TOFU 0.25 / MOFU 0.40 / BOFU 0.35), so a hot lead is hot relative to real, current momentum — not an arbitrary threshold.
A cross-metric correlation engine then links scoring signals to downstream conversion, keeping the model weighted toward what actually predicts a closed deal. And because every action is human-in-the-loop, scoring drives real work: when a lead crosses threshold, an agent prepares the outreach and you approve it — prepare → approve → executing → done — before a single email sends. That's the point of a command center — the score doesn't just sit there, it triggers the next move.
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Intent-signal scoring
dolv scores leads on real intent signals — opens, clicks, page paths, replies — so the score reflects buying behavior, not just a job title.
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Read against one funnel
Scores live inside one unified TOFU/MOFU/BOFU funnel on a rolling 30-day baseline, so a hot lead is hot relative to real, current momentum.
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Cross-metric correlation
A correlation engine links scoring signals to downstream conversion, so the score keeps weighting what actually predicts a closed deal.
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30 read + write integrations
Signal flows in from Gmail, Calendar, GA4, Search Console, LinkedIn, and the ad platforms — one connected source of truth, not stale exports.
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Built on the full CRM
Scoring runs on the built-in CRM, so every contact carries a live score next to its record — no separate tool to reconcile.
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Human-in-the-loop action
When a lead crosses threshold, an agent prepares the outreach and you approve it — prepare → approve → executing → done — before anything sends.
Surfacing the lead that's ready to buy
A contact you'd half-forgotten opens three emails in a day, revisits the pricing page, and clicks a case study. In dolv, intent-signal scoring lifts them to the top of the queue, and the correlation engine confirms that pattern reliably precedes a closed deal against the 30-day baseline. An agent drafts a tailored follow-up grounded in their activity, you read it, and you approve it in one click — prepare → approve → executing → done. The hottest lead gets worked first, while it's still hot. dolv it.
AI lead scoring questions
Quick answers to what people ask about lead scoring.
What is AI lead scoring?
AI lead scoring is the practice of ranking leads by how likely they are to buy, using a model that weighs behavioral and intent signals — email opens, page visits, replies, fit — instead of a fixed manual point system. In dolv it runs as intent-signal lead scoring on the built-in CRM, read against one unified TOFU/MOFU/BOFU funnel scored on a rolling 30-day baseline, so a hot score reflects real, current buying behavior.
How is AI lead scoring different from traditional lead scoring?
Traditional lead scoring assigns fixed points by hand — plus ten for a demo request, plus five for an industry — and those rules go stale fast. AI lead scoring learns which signals actually precede a closed deal and weights them automatically. dolv pairs intent-signal scoring with a cross-metric correlation engine, so the model keeps reweighting toward the signals that genuinely predict conversion rather than the ones someone guessed at once.
How does dolv do AI lead scoring?
dolv pulls live signal from 30 read-and-write integrations — Gmail, Calendar, GA4, Search Console, LinkedIn, and the ad platforms — onto the built-in CRM, then scores each lead on intent signals read against one unified funnel on a rolling 30-day baseline. When a lead crosses threshold, an agent prepares the outreach and you approve it — prepare → approve → executing → done — so scoring drives real action, not just a number on a dashboard.
See scoring that ranks leads by real intent
Intent-signal scoring, a correlation engine, and one unified funnel — running in a single grounded command center, with every move approved before it sends. dolv it.