Blueprint 2 · Lead → Cash

AI-Driven Prospecting

Turn dark-funnel intent into booked meetings with autonomous, multi-channel outbound loops — so SDR capacity goes to conversations, not list-building. Built on Common Room, LinkedIn Sales Nav, GhostGTM, and Outreach.

What SDR leaders get: more booked, qualified meetings per rep — without burning domain reputation.

01 · Signal

Dark-funnel intent

Community signups, GitHub stars, job changes detected.

Common Room · LinkedIn
02 · Reasoning

Prioritize & draft

GhostGTM ranks accounts by ICP fit × intent and drafts hooks.

GhostGTM
03 · Action

Outreach sequence

Multi-channel sequence (email, LinkedIn) auto-launched.

Outreach · Slack
04 · Record

Booked meeting

Reply detected → meeting booked → Opp created in SFDC.

Salesforce

How to build it

1
Consolidate dark-funnel intent
Connect Common Room to Slack/community, GitHub, and the website to capture signals.
2
Score fit × intent × whitespace
Document the weighting GhostGTM uses to prioritize — it's the agent's brain.
3
Lay the deliverability foundation
Authenticated domains (SPF/DKIM/DMARC), dedicated sending domains/inbox rotation, per-mailbox send caps, and bounce (<3%) / spam (<0.1%) kill-thresholds that auto-pause a sequence.
4
Gate draft vs. send
Default to draft → human-approve for the first touch; auto-send only proven templated steps. Honor a global suppression list (CAN-SPAM/GDPR/CASL).
5
Auto-enroll in Outreach
Integrate the Outreach API to launch multi-channel sequences; add LinkedIn Sales Nav steps.
6
Book, qualify, then create the opp
On a positive reply, book the meeting and create a pending SAL; the Opp is created only after AE acceptance against agreed SQL criteria. Rejected meetings recycle with a reason code.

What this looks like in Slack

G
GhostGTM
App · Slack
👻 New prospect: techflow.io
Hiring RevOps + visited Integrations page 3× this week + starred the GitHub repo. I drafted a 3-step Outreach sequence referencing their hiring post.
Review Sequence
Edit Draft

Beyond outbound

A demand engine, not an SDR cost center

The goal isn't meetings booked — it's marketing-sourced pipeline (in dollars and as a share of total), cost-per-opportunity by signal source, and the blended CAC of the signals you act on. Meetings are a leading indicator; sourced pipeline at an efficient cost is the number that gets funded.

Inbound, ABM & paid — the same loop, not just outbound

The loop is signal-agnostic: a form fill, a Fin chat, a doc page revisited three times, a paid-search click, a content download, or a job change is all just Signal. What changes is the threshold — when an account crosses a fit × intent line, the loop fires a coordinated play: a campaign audience add, an SDR task, and an AE heads-up land together, not a lone cold email. Paid, SEO, website, and content feed the same signal store the outbound agent reads. One account, one orchestrated motion, wherever the signal came from.

Edits become coaching

Every edit a rep makes to an AI-drafted opener is a data point. Consistently rewrite the value prop or soften the ask, and that's a messaging gap the loop captures instead of discarding. Diffs roll into a per-rep coaching scorecard and a messaging certification — a rep passes (approval rate and edit-depth below threshold) before auto-send unlocks for low-risk steps. The bar is a meeting-quality competency: reps are measured on qualified meetings that survive AE acceptance, not dials.

What to measure

Marketing-sourced pipeline ($ and %) vs target — reported separately so it's never double-counted against AE/SDR-sourced. Cost-per-meeting and cost-per-opp by signal source — retire sources running above blended CAC. Speed-to-lead under 5 minutes on hot inbound. SAL rate above 70%, with reason codes on every rejection routed back to retune scoring and spend. MQL→SQL 13% median / 31% top-decile. And the share of pipeline sourced by the autonomous loop vs manual — climbing at flat-or-lower cost-per-opp is the proof the engine works.