SALES OPERATIONS // FREE LIVE DEMO
Outbound Prospect Scorer
A scraped list of 500 cold prospects gets worked in the order it was exported, not the order that would actually convert — reps burn hours on low-fit accounts before reaching the good ones.
Need inbound sales-readiness scoring instead? Lead Scoring Agent →
WHAT IS OUTBOUND PROSPECT SCORER?
An AI outbound prospect scorer takes a raw, cold list of prospects and a target ICP, scores each purely on firmographic fit, and returns a ranked sequencing order so reps work the highest-fit accounts first instead of working the list in export order. It scores cold potential, not warm readiness — there's no engagement signal to read yet.
HOW IT WORKS
Cold outbound sequencing is a resourcing problem before it's a messaging problem: a rep who works 500 prospects in random order burns the same hours on a 20-fit account as an 85-fit one. This agent scores strictly on firmographic signal — industry match, size band, and inferred absence of the capability being sold — because that's the only signal available before any contact has been made. It deliberately avoids scoring on engagement or readiness, since a cold prospect by definition hasn't engaged; conflating firmographic fit with buying readiness is exactly the mistake that makes cold-list scoring unreliable.
The output is a sequencing table, not just a score list, because the point isn't the number — it's the work order it produces. Low-fit accounts get flagged for deprioritisation with a reason, so a rep (or an SDR manager reviewing the list) can see why an account was pushed down rather than trusting a black-box score.
You are a firmographic scoring analyst for a B2B outbound sales operation. Given a raw list of cold prospects and a target ICP, score each prospect 0-100 on firmographic fit only (industry match, size band, likely absence of the capability being sold) — never on engagement, since these are cold and have shown none. Return a ranked sequencing table so outbound reps work best-fit accounts first, plus a short note on which to deprioritise and why. Output ONLY a JSON array of typed blocks matching the OutputBlock union — no prose outside the JSON.USE CASES
Fresh scraped-list triage
A Google Maps or LinkedIn scrape returns 300 raw leads — score and sequence them before the first outbound touch goes out.
SDR territory planning
An SDR inherits a territory list at quarter start — the agent produces a working order so week one targets the accounts most likely to convert.
Multi-vertical outbound campaigns
A campaign targets three different verticals at once — score each against its own ICP variant so sequencing stays apples-to-apples within each segment.
Re-scoring a stale list
A list that's sat untouched for a quarter gets re-scored against an updated ICP before reps pick it back up.
RESULTS & BENCHMARKS
List triage time per 100 prospects
projected (modeled)
Weekly optimisation time (production)
real, anonymized
LIVE DEMO
Try it right now
FAQ
Common questions
What does this agent score, exactly?
Firmographic fit only — industry match, size band, and likely need — since cold prospects haven't engaged yet and there's no readiness signal to score.
How is this different from a sales-readiness or lead score?
A readiness score (like agent #37, Lead Scoring) measures how close an already-engaged lead is to buying. This agent works upstream of that — it decides which cold, unengaged prospects are worth contacting first.
Can it handle a large list?
The live demo scores a handful of sample prospects to show the mechanism; the same scoring logic scales to list-sized batches in a production integration.
RELATED AGENTS
Lead Research Agent
Cold-outbound lists take hours of manual research per prospect before the first message can even be written.
Signal Opener Writer
Trigger events — a funding round, a new hire, an office expansion — get spotted and then wasted on a generic "congrats on the news!" opener that reads like every other message referencing the same event.
A/B Messaging Optimizer
Reps write one version of an outreach message, send it to everyone, and never learn which angle actually works — there's no variant to compare against.
Built by Hammad Yousuf — AI Marketing Automation Engineer, 540K+ YouTube subscribers.
See the production missions these agent patterns run in, or hire the whole system.