Best for
- B2B teams with enough closed-won data to identify repeatable buying patterns
- Sales teams that want warmer outbound based on actual customer wins
- RevOps teams trying to turn CRM history into repeatable prospecting plays
Mine recent closed-won CRM notes, call transcripts, objections, and proof points, then find similar accounts and draft human-reviewed outbound sequences.
Create a weekly lookalike outbound queue built from real closed-won patterns, not generic ICP guesses.
Quick view
Check the audience, core tools, and access before you start the detailed steps.
Best for
Core tools
7 tools used across the workflow.
Access
Preview the open steps, then unlock the remaining implementation details and prompts.
Why this works
Most outbound starts from static ICP attributes: industry, size, title, and geography. Closed-won deals contain richer signals: the pain that triggered the project, the objections that almost killed it, the proof that closed it, and the stakeholders who mattered. This workflow turns those patterns into lookalike prospecting while keeping final outreach human-reviewed.
Expected results
Lookalike accounts sourced
25-75 accounts per run
A focused closed-won pattern usually supports a tight account set without creating an unreviewable outbound dump.
Contacts prepared
75-250 prospects
Finding 3-5 people per account creates enough multi-threading coverage while staying practical for human review.
Review-ready drafts
4 role-based touches
The output is a draft sequence for each buying-committee role, not an automatically sent campaign.
Strategic value
Closed-won-backed targeting
The prospecting logic is derived from actual customers and calls instead of static persona assumptions.
Step-by-step workflow
The first 2 steps are open. Pro unlocks the remaining steps, copy-paste prompts, pro tips, tool-by-tool setup guidance, and implementation details.
45 min
45 min
Start in HubSpot and export recent closed-won deals from the last 30-90 days. Include company name, industry, employee count, deal size, source, close date, sales notes, owner, primary persona, and any structured fields for pain, use case, or competitor. Do not include every deal if the motion is too broad. Pick a coherent segment so the lookalike logic has a real pattern to learn from.
A focused closed-won deal set with the fields needed for pattern analysis.
Segment before you analyze. A $20K SMB self-serve win and a $500K enterprise win may both be closed-won, but they probably should not create the same outbound play.
1-2 hours
1-2 hours
For each selected deal, pull relevant Gong call snippets, discovery notes, and late-stage objection moments. Capture the trigger, stated pain, current workaround, competitor mention, buying committee, proof point that landed, and final reason they bought. Store these notes next to the deal record in Airtable so the analysis does not rely on CRM fields alone.
Deal evidence table with real pain language, objections, buying triggers, and proof points.
The most useful transcript moments are not the polished testimonials. They are the messy lines where the buyer explains why the old way is painful.
Pro workflow preview
Previewing 2 of 8 steps
Get the remaining 6 steps, copy-paste prompts, pro tips, tool-by-tool setup guidance, and ongoing workflow and prompt releases.
$9/month
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