How to Find Decision Makers in Clay When People Finder Falls Short
Clay's standard People Finder is powerful, but sometimes you need more control. Here's a workflow using AI Agents to find decision makers and two ways to format that data for your campaigns.
When Clay's AI Agent returns decision-makers as a list trapped in a single cell, use Clay's native 'Write each item to a new row in another table' action to explode the array. Map both the decision-maker fields and parent company columns to create individual rows per person while preserving company context, enabling direct campaign enrollment or CRM push.
Key takeaways
- Clay AI Agents can find niche decision-makers that standard People Finder databases miss, but often return results as arrays locked in single cells.
- Clay's native 'Write each item to a new row in another table' action splits list data into individual rows while preserving parent company information like website and phone number.
- Applying confidence score filters before splitting rows saves enrichment credits by removing low-quality matches early in the workflow.
- Exporting to CSV and using AI code editors like Cursor provides an alternative method for complex data cleaning before re-importing to Clay.
- Mapping parent table columns during the split operation ensures every new decision-maker row retains essential company context for outreach campaigns.
Reviewed and updated August 28, 2026
How to Find Decision Makers in Clay When People Finder Falls Short
If you've ever struggled to find specific decision-makers using Clay's standard "People Finder," you're not alone. Sometimes the built-in databases just don't cover your niche perfectly, or you need highly specific titles that require an AI agent's nuance.
Teams that still wonder whether this enrichment tool overlaps with their outreach platform will find a cross category platform comparison that clarifies how the two tools actually complement each other.
There's a powerful alternative method that works just as well, if not better, for these tricky cases.
The Challenge: Locked Data
Let's say you're targeting a specific niche (like schools, malls, or specialized firms) and need to find the "Head of School" or a specific Director. You import your list of companies into Clay and run a Clay AI Agent to find these people.
The agent does a great job. It returns a list of decision-makers for each company.
But here's the problem: That data is often returned as a list (array) inside a single cell. You have one row for the company, and a clump of people stuck in one column. You can't enroll them in a campaign like that.
You need to "explode" that list so each decision-maker gets their own row, while keeping the company's information (Website, Name, etc.) attached to them.
Here are two ways to solve this.
Method 1: The "Clay Native" Way (Recommended)
This is the fastest method and keeps everything inside Clay.
- Find Your List Column: Locate the column where the AI Agent output the list of decision-makers.
- Take Action: Click on the column header or use the "Actions" menu. Look for an option like "Write each item to a new row in another table".
- Map Your Data: Clay will ask you where to send this data. Create a new table (e.g., "Decision Makers").
- Select Columns:
- Map the decision-maker's name, title, and email from the list.
- Crucial Step: Make sure to also map the "Parent" columns from your original table, like the Company Name, Website, and Phone Number. This ensures every new row has the company context.
- Run It: Clay will process the list and create a new table.
Result: You now have a clean table where every row is a unique person, complete with their company data. You can now enrich them with emails or push them straight to your CRM.
Once those contacts land in your CRM, you may wonder whether that platform pairs well with Clay, a question explored in this comparison of Clay and Copper.
Method 2: The "AI Assistant" Way (For Complex Data)
If the data is messy or truncating, or if you want to do complex cleaning before creating new rows, you can use an AI code editor like Cursor.
- Export to CSV: Export your Clay table (the one with the list in a cell) as a CSV.
- Upload to AI: Drag that CSV into Cursor.
- The Prompt: Ask the AI:
"I have a column here called 'Decision Makers' which contains a list of objects. Please create a new CSV where each item in that list gets its own row. Keep the other columns (Company Name, Website) for each new row."
- Review & Re-Import: The AI will write a script to process the file and give you a clean CSV.
- Import to Clay: Upload this new CSV back into Clay.
Note: This method adds a few steps but is a lifesaver if you need to apply complex logic, like "Only keep decision makers if the confidence score is > 80%" or "Reformat the titles before splitting."
Pro Tip: Add Logic Before You Split
Whether you use Method 1 or 2, consider adding a filter before you create the new rows.
For example, if your AI Agent returns a "Confidence Score" for each person, you can tell Clay (or your AI script) to only keep people with a score of High or Medium. This saves you credits on enrichment later by filtering out low-quality matches early.
Summary
Don't let a "list in a cell" stop your workflow. Whether you use Clay's native "Write to new table" feature or wrangle the data with an external AI tool, unlocking this data gives you access to decision-makers that standard databases often miss.
Related Reading
- How to Extract Data from Any API in 2 Minutes Without Writing Code
- How to Scrape 2,000+ Apollo Leads in 5 Minutes for $0 (No Code Required)
- A Clay Lead Generation Workflow, End to End, With Real Costs
If you would rather have this run for you, RevenueFlow books qualified meetings on a pay-per-meeting basis and publishes client results.
Frequently asked questions.
Frequently asked questions- Why does Clay's AI Agent return decision-makers in a single cell instead of separate rows?
- Clay's AI Agent returns multiple decision-makers per company as a list or array within one cell because it's designed to keep all findings together in the original company row. This format prevents immediate campaign enrollment since each person needs their own row with complete contact and company data to be useful for outreach.
- How do I split a list of decision-makers into individual rows in Clay?
- Click the column header containing the list and select 'Write each item to a new row in another table' from the Actions menu. Map the decision-maker fields like name, title, and email, then crucially map parent columns such as Company Name and Website to ensure each new row retains company context. Clay will create a new table with one row per person.
- Should I filter decision-makers before or after splitting them into separate rows?
- Filter before splitting to save enrichment credits. If your AI Agent includes confidence scores, set a threshold to keep only High or Medium confidence matches before creating new rows. This prevents you from spending credits enriching low-quality matches that you'd discard later anyway.
- When should I use an AI code editor like Cursor instead of Clay's native split function?
- Use an AI code editor when your data is messy, truncating, or requires complex cleaning logic before splitting. Export your Clay table as CSV, upload to Cursor, and prompt it to split the list while applying custom rules like reformatting titles or filtering by multiple criteria. Then re-import the cleaned CSV back into Clay.
About the author.
Tim Carden is CMO / CTO at RevenueFlow, which builds and operates outbound revenue engines for B2B companies. Studied at McGill University.
Tim Carden · CMO / CTO
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