How to Connect People Data Labs to Google Sheets (4 Methods Compared)

The Problem With Getting Sheet Data In and Out of People Data Labs

You have a Google Sheet full of data — names and emails from a webinar, company names from a Salesforce export, raw job titles from a survey. You need PDL to enrich it, or you need to pull a fresh prospect list out of PDL into that sheet, and you need it done without an afternoon of API docs.

People Data Labs is good at resolving partial contact and company records into complete, structured profiles. But moving data between PDL and your spreadsheet is more work than it should be. The usual flow is: export a CSV, run a script or use the API console, paste results back, fix the column alignment, repeat.

Below are the four common ways teams handle this. Only the last one scales.

Method 1: Manual Copy-Paste

The default. You grab a handful of rows from your sheet, drop them into PDL's UI or run a curl command, get the enriched JSON back, and copy the fields you need into the right columns. For three records, that's fine.

For 200 records, you are doing data entry. Each row means another lookup, another copy, another paste. Your columns drift. You lose track of which rows you already ran. By row 40 you're running the same records twice and wondering if the job title in column D came from PDL or the original form.

The friction compounds with every pass. PDL data is meant to be the starting point for outreach, not the ending point of an afternoon's manual labor.

Method 2: Zapier or Make

Both platforms have People Data Labs connector options. You can wire up a trigger on a new sheet row, call the PDL enrichment endpoint, and write the enriched fields back into the sheet.

Before you go further — do you know what a webhook trigger is? A multi-step Zap? Field mapping between JSON responses and specific spreadsheet columns? Authentication tokens and API key storage? If those terms feel foreign, Method 3 and 4 will serve you better. Stop here and skip ahead.

If you're still here, the workflow does work. You set the trigger, map the input fields PDL needs, map the response fields back into your sheet columns, handle edge cases for rows where PDL can't find a match. The setup takes a few hours, assuming you know the platform.

The structural problem: this fires one row at a time.

If you want to enrich 300 contacts, that is 300 individual API calls, 300 Zap tasks, and a task history that becomes impossible to audit when row 147 returns no match and the rest silently skip.

You probably just need the enriched company data to finish building the territory plan. You probably have no idea how to set up a multi-step Make scenario with custom API modules — and you shouldn't have to. So you flag it for whoever on your team handles automations, and now you're waiting on a Slack message that may or may not come before Thursday.

And the moment you need to filter, group, or join enriched results with another tab, you've left the automation's native capabilities entirely.

Method 3: The Previous Generation — Connector Add-Ons

Until recently, the best option for repeatable spreadsheet-to-PDL workflows was a category of add-ons that let you configure column mappings, set the enrichment type, and run the job from a sidebar menu. You picked your range, mapped your fields, saved your config, hit run.

That was a real step up from copying JSON by hand. The output was consistent, configs were reusable, and you could run the same enrichment again next week without redoing the setup.

But you were still responsible for designing the field mapping, handling the missing-match rows, writing the conditional logic for which records to include, and fixing the config every time your sheet structure changed. The tool moved the data; the thinking stayed on you. And when PDL added a new field you wanted, someone had to go back in and update the template.

This is the previous generation. Solid, but operator-heavy.

The Easy Way: Using SheetXAI in Google Sheets

There is a different way entirely. SheetXAI is an AI agent that lives inside your Google Sheet. It reads the sheet, understands what you are looking at, and through its built-in People Data Labs integration it can enrich your records, run searches, clean your data, and write results back — all from a single prompt.

Example 1: Bulk enrich a lead list

Enrich each row in this sheet using PDL: use the email in column A to look up the person and write their job title, company name, and LinkedIn URL into columns C, D, and E.

PDL matches each email to a person profile and writes the enriched fields back into the right columns. Rows where PDL finds no match get flagged in column F so you can review them separately.

Example 2: Import a company search result set

Search People Data Labs for US e-commerce companies with 20 to 200 employees founded after 2015, return 300 results, and write each company's name, website, employee count, and LinkedIn URL into this sheet.

The pattern: instead of pulling data first and then cleaning it, you describe the target and the output shape in one prompt. SheetXAI handles the query construction and the write-back inline.

Try It

Get the 7-day free trial of SheetXAI and open any Google Sheet with a contact or account list, then ask it to enrich your rows or run a PDL search. The People Data Labs integration is included in every SheetXAI plan.