This Workato recipe takes a list of your accounts, from your CRM or a file, enriches them with Lusha, and finds similar lookalike companies. It exports the new list to your CRM, Google Sheets, or a review queue, ready for sales or marketing to act on.
Expand your pipeline with lookalikes
Why use lookalikes to expand your pipeline?
Your best accounts already show you who to target next. The hard part is turning that pattern into a list you can use.
This recipe does it for you. It learns from the accounts you already care about, finds companies that match them, and gives your team a clean list of new targets, instead of guesswork.
What this workflow does
- Starts from a CSV upload, a CRM list, or a predefined set of accounts
- Enriches each account with Lusha, adding industry, company size, location, and revenue range where available
- Finds lookalike companies with similar industries, sizes, and locations
- Lets you set how many lookalikes to find per account and keep them within your ICP
- Exports the results to your CRM, Google Sheets, or a review queue, tagged by source
How to set it up
01
Connect your apps in Workato
Ensure active connections for:
- Lusha: API access for enrichment and recommendations
- CRM or storage tool: destination for exported accounts
02
Define the source accounts
Choose how accounts enter the flow:
- Upload a CSV
- Pull accounts from your CRM
- Use a predefined account list
Best practice: Start with high-quality accounts (customers, high-value opportunities, or strategic targets).
03
Configure Lusha enrichment
Enrich each account with:
- Industry
- Company size
- Location
- Revenue range (if available)
This data powers accurate lookalike matching.
04
Generate lookalike companies
Lusha analyzes enriched account patterns to recommend:
- Similar industries
- Comparable company sizes
- Matching geographies
You can control:
- Number of lookalikes per account
- Filters to stay within your ICP
05
Export the results
Send the lookalike list to:
- Your CRM (as new accounts)
- Google Sheets or CSV
- A review queue for approval
Tag records clearly (e.g., Source = Lusha Lookalike Expansion).
06
Test end-to-end
Run the recipe and confirm:
- Accounts enrich correctly
- Lookalike companies are generated
- Exported data is complete and usable
What to do next
- Add contact discovery: Automatically find decision-makers at lookalike accounts.
- Score expansion targets: Rank companies by similarity or potential value.
- Route by segment: Send different lookalikes to different teams or territories.
- Trigger outbound workflows: Enroll lookalike accounts into ABM or outbound sequences.
- Measure expansion ROI: Track pipeline influenced by lookalike-generated accounts.
The goal: Expansion shouldn’t rely on intuition alone. This play turns your existing accounts into a systematic lookalike engine, helping you scale pipeline with companies that already look like a win.
FAQ
Use this Workato recipe. It enriches your existing accounts with Lusha and finds similar companies based on industry, size, and location.
Your strongest accounts, like customers, high-value opportunities, or strategic targets. Better input gives better lookalikes.
Yes. You set the number of lookalikes per account and add filters to stay within your ICP.
To your CRM as new accounts, to Google Sheets or a CSV, or to a review queue for approval.
Yes. You can add a step to find decision-makers at each new account.
Ready to run this?
One data connection. Works in Claude, ChatGPT, your CRM, or any agent you build.
