Find similar contacts from Lusha-enriched records
Scale your ICP by building an automated lookalike prospecting workflow. This play uses your best enriched contacts (champions and power users) as a seed to generate high-fit contact recommendations directly in your CRM via Make.com.
Why this works
Most teams already know who converts well: the VP of Sales at a 200-person SaaS company, the Director of RevOps at a Series B fintech, the Head of Marketing at a growing tech startup. The problem is finding more people who look exactly like that.
Manual lookalike prospecting means guessing at filters, building searches from scratch, and hoping you’ve captured the pattern correctly.
This play removes the guesswork: Lusha’s AI analyzes your best contacts and finds similar people automatically, based on role, seniority, company type, industry, and more.
What you get
- AI-powered lookalike prospecting that finds contacts similar to your best customers, champions, or closed-won buyers
- Automatic CRM population with recommended contacts created as new leads or added to expansion lists
- Repeatable expansion plays where you can run the same workflow on different segments (land & expand, ABM target lists, win-based prospecting)
- Structured recommendations with full contact enrichment (email, phone, title, company data) included
How to set it up
Use the Make template
Start from the “Get contact recommendations from Lusha enriched records” template. It connects the full flow: enriched contacts → Recommendations API → CRM sync.
Connect your data source
Pull enriched contacts from your CRM (HubSpot/Salesforce) based on your criteria:
- Closed-won opportunities (primary buyer/decision-maker)
- Champion contacts from your best accounts
- Power users or high-engagement contacts
- ICP-fit contacts who converted
Tip: The source contacts must already be enriched with Lusha (they need personId and companyId fields).
Send to Lusha Contact Recommendations API
The Make scenario calls:
POST https://api.lusha.com/api/recommendations/contacts
Include the Lusha IDs from your enriched contacts:
json{
“contacts”: [
{ “personId”: “123456”, “companyId”: “789” },
{ “personId”: “234567”, “companyId”: “890” }
]
}
Receive similar contact recommendations
Lusha returns contacts that match the profile of your input set: similar roles, seniority levels, company types, industries, and firmographics.
Map recommendations to your CRM
For each recommended contact, create:
- A new Lead/Contact record in Salesforce or HubSpot
- Pre-filled fields: name, title, email, phone, company data
- Source tag: “Lookalike – Contact Recommendations”
Add to the right workflow
Route recommended contacts based on use case:
- Land & expand: Route to account owner for existing customers
- Win-based prospecting: Add to outbound sequences
- ABM expansion: Add to target account lists
Test with a small batch
Start with 5-10 of your best contacts. Confirm:
- Recommendations return similar profiles
- CRM records are created correctly
- Routing logic works as expected
What to do next
- Segment by use case: Run separate recommendation flows for expansion (existing customers) vs. new logo acquisition (closed-won lookalikes)
- Add quality filters: Only sync recommendations that meet minimum fit criteria (company size, industry, location)
- Track performance: Measure conversion rates from recommended contacts vs. manually sourced prospects
- Iterate on input set: Refine which contacts you use as the “seed” — test different champion types, deal sizes, or segments to see which produces the best lookalikes
- Combine with signals: Layer in buying signals (funding, hiring, job changes) on top of recommended contacts to prioritize who to reach out to first
The goal: Stop guessing who to prospect. Let your best contacts show you exactly who to target next—at scale, automatically, and with verified data ready to work.
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