Closed-Won Lookalike Workflow

Outbound

Automation

Prospecting

Data

The companies you already closed are the most accurate target list you own. This workflow reads them, then goes and finds more like them.

What is a closed-won lookalike workflow and how we set it up?

Your best customers are the proof of what a good customer looks like. This workflow finds more companies like them.

Most target lists are built on opinion. Somebody picks an industry, a company size and a few job titles, and thousands of companies come back that match the filter and nothing else. Meanwhile the best description of a good customer already sits in your CRM: the deals you won.

This workflow starts there. You choose which wins you want more of, because the accounts that pay most, close fastest and stay longest are rarely the same companies. Then it turns those wins into a profile, searches for companies that match, removes everyone you should not contact, and ranks the rest.

Your outbound gets a list where every company comes with a reason: which customer it looks like, and why. That reason is what makes the first message land.

Step 1: We choose which customers to clone

Your closed deals are the best proof of what a good customer looks like. But your won deals are not one group. The biggest contracts, the fastest deals and the customers who stayed longest are usually different companies. Mixing them gives you a profile that fits nobody. So the first step is a decision, made together. • The highest paying: pick these if you want bigger contracts, and accept longer deals • The fastest to close: pick these if you need speed this quarter • The best retained: pick these if you want customers who stay. Most teams should, and few do The whole workflow is only as good as this choice. That is why people make it, out loud, and not a tool.

Step 2: Your wins become a profile

Then the workflow takes the customers you chose apart. What size are they. What tools do they run. How do they sell. Who sat at the table when they signed. • The traits that keep coming back become the profile, including the ones nobody expected • The result is precise enough for a machine to score companies against • That is a very different thing from the one-line customer description most teams keep in a slide

Step 3: Three searches look for matches

With the profile ready, the workflow searches for companies that match. Not one search: three, each from a different angle, because every search source has blind spots. • Companies built the same way: size, market, structure • Companies using the same tools your customers use • Companies in the same market: the competitors, partners and neighbours of your current customers Everything lands in one list. A company found by two searches is a stronger match than a company found by one.

Step 4: The list gets cleaned and ranked

Before any money is spent, everyone you should not contact comes off the list: current customers, open deals, accounts a colleague owns, and anyone who asked not to hear from you. Then every company that is left gets a score against your profile. • The check runs against your CRM, so the list matches what your team sees • The list arrives sorted: the companies most like your best customers sit at the top Your team just works down from the top.

Step 5: We find the buyers

A company on a list is not someone you can write to. So for the companies at the top, the workflow finds the people. • The roles that sat at the table when your winning deals closed • Found live, so the job titles are current • With verified email addresses

Step 6: Outreach starts with a reason

The finished list lands in your sending tools, and every company carries its reason: which of your customers it looks like, and why. That reason is what makes the first message land. • Each account is reached on the channel its market answers: email, LinkedIn, or both • Nothing goes out without a person able to see it first • Replies, meetings and deals get read back against the profile, so the next round starts smarter Run every quarter, this becomes the most dependable list source you have. It learns from the only evidence that never lies: the customers who already said yes.

Step 1: We choose which customers to clone

Your closed deals are the best proof of what a good customer looks like. But your won deals are not one group. The biggest contracts, the fastest deals and the customers who stayed longest are usually different companies. Mixing them gives you a profile that fits nobody. So the first step is a decision, made together. • The highest paying: pick these if you want bigger contracts, and accept longer deals • The fastest to close: pick these if you need speed this quarter • The best retained: pick these if you want customers who stay. Most teams should, and few do The whole workflow is only as good as this choice. That is why people make it, out loud, and not a tool.

Step 2: Your wins become a profile

Then the workflow takes the customers you chose apart. What size are they. What tools do they run. How do they sell. Who sat at the table when they signed. • The traits that keep coming back become the profile, including the ones nobody expected • The result is precise enough for a machine to score companies against • That is a very different thing from the one-line customer description most teams keep in a slide

Step 3: Three searches look for matches

With the profile ready, the workflow searches for companies that match. Not one search: three, each from a different angle, because every search source has blind spots. • Companies built the same way: size, market, structure • Companies using the same tools your customers use • Companies in the same market: the competitors, partners and neighbours of your current customers Everything lands in one list. A company found by two searches is a stronger match than a company found by one.

Step 4: The list gets cleaned and ranked

Before any money is spent, everyone you should not contact comes off the list: current customers, open deals, accounts a colleague owns, and anyone who asked not to hear from you. Then every company that is left gets a score against your profile. • The check runs against your CRM, so the list matches what your team sees • The list arrives sorted: the companies most like your best customers sit at the top Your team just works down from the top.

Step 5: We find the buyers

A company on a list is not someone you can write to. So for the companies at the top, the workflow finds the people. • The roles that sat at the table when your winning deals closed • Found live, so the job titles are current • With verified email addresses

Step 6: Outreach starts with a reason

The finished list lands in your sending tools, and every company carries its reason: which of your customers it looks like, and why. That reason is what makes the first message land. • Each account is reached on the channel its market answers: email, LinkedIn, or both • Nothing goes out without a person able to see it first • Replies, meetings and deals get read back against the profile, so the next round starts smarter Run every quarter, this becomes the most dependable list source you have. It learns from the only evidence that never lies: the customers who already said yes.

Closed-won lookalike workflow tools

Your won deals in, a ranked target list out.

Your won deals in, a ranked target list out.

Three lookalike engines search in three different ways, which is exactly why all three run. Clay collects what they find, removes the duplicates, and scores every company against the customers you chose. Your CRM supplies the exclusions, LeadsFactory finds the buyers, and your sending tools start the outreach.

HubSpot logo, a connected CRM platform unifying sales, marketing, and service on one customer record

HubSpot

CRM

Salesforce logo, the enterprise CRM standard, deeply configurable and built to scale

Salesforce

CRM

Clay logo, a go-to-market data platform that enriches and researches leads in a spreadsheet workflow

Clay

Enrichment

Claude logo, Anthropic's LLM family used across GTM for research, classification, and drafting

Claude

AI

Ocean.io logo, a B2B account-discovery platform built around lookalike search on your best customers

Ocean.io

Data

Discolike logo, a B2B account-discovery tool that finds lookalike companies from across the open web

Discolike

Data

AI Ark logo, an AI-powered B2B data platform with lookalike and semantic search that builds ICP-matched prospect lists

AI Ark

Data

LeadsFactory logo, a contact discovery tool that scrapes LinkedIn Sales Navigator in real time

LeadsFactory

Scraping

Instantly logo, a cold email sending platform with inbox rotation, warmup, and a built-in lead database

Instantly

Sending

Lemlist logo, a multichannel sales engagement tool that combines email, LinkedIn, and calling sequences

Lemlist

Sending

HeyReach logo, a LinkedIn outreach platform that runs automated sequences across many sender accounts

HeyReach

LinkedIn

Ready to implement this workflow?

Ready to implement this workflow?

Ready to implement this workflow?

Book a workflow consultation and see how automation transforms your GTM engine.

Book a call with our team to discuss how this workflow fits your sales process and timeline.

Book a workflow consultation and see how automation transforms your GTM engine.

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© 2026 Nebor. All rights reserved.

© 2026 Nebor. All rights reserved.

© 2026 Nebor. All rights reserved.

© 2026 Nebor. All rights reserved.