Apollo contact scraper sub-workflow for Google Sheets

Apollo contact scraper sub-workflow for Google Sheets

An n8n sub-workflow. Another workflow calls it with job titles, places and business keywords. It turns them into an
Apollo people search address, has an Apify Actor read the contacts from that search, and saves each contact to a Google
Sheet. It answers the caller with one line that says how many contacts were saved.

Read "The Actor is gone" below before you build on it: the Actor named in the file no longer answers.

What is inside

• workflow.json: the workflow as n8n exports it, eight nodes and no sticky notes. It holds no credential.
• README.md: these notes.

What we changed from the original copy

• Apollo Scraper carried an Apify token in its address, beside a placeholder in its query parameters. The token is gone,
  and the parameter now says <YOUR_APIFY_TOKEN>.
• Apollo Scraper had no method set, so n8n would send a GET, and Apify's API takes an Actor's input only in a POST. It
  is POST now.
• The original copy's Create URL code had lost a backslash: its regex read /+/g, which JavaScript rejects. This one
  has /\+/g back.
• The author's sheet and its tab id are gone. Google Sheets stores scraped data asks for YOUR_SHEET_ID and finds the
  tab by the name Leads.

Before you start

• An n8n instance, on n8n Cloud or your own server, and a workflow that will call this one.
• An Apify account and its API token, with credit, and an Actor that reads contacts from an Apollo search address (below).
• A Google account, and a Google Sheet for the contacts.

The Actor is gone

The file calls code_crafter~apollo-scraper. On 2 November 2026 Apify's API answered 404 Not Found for that Actor, and
its store address showed a page of Apollo scraper alternatives instead. Until you replace it, Apollo Scraper fails.

To replace it, pick an Actor on Apify that takes an Apollo people search address. Put its ID in the address of
Apollo Scraper, keep run-sync-get-dataset-items at the end, and write the body its input page asks for. The file
sends url, totalRecords of 500, and getPersonalEmails and getWorkEmails set to true. Then run it once and match
the fields in Extract Info to what the new Actor returns.

Set it up

1. In n8n, create a workflow, open its menu and choose Import from File. Pick workflow.json.
2. Make a Google Sheet with a tab named Leads. Put these headers in row 1, since the sheet node maps fields to columns
   by name: fullName, emailAddress, linkedInURL, seniority, jobTitle, companyName, location, country,
   Number, websiteURL, businessIndustry. In Extract Info, the seniority field's name ends in a space. Delete
   that space so the field finds its column.
3. Copy the sheet's ID: the long part of its address between /d/ and /edit.
4. Add a Google Sheets OAuth2 credential. In Google Sheets stores scraped data, select it and replace YOUR_SHEET_ID
   with the ID. Then pick emailAddress as the column to match on. The file has none set.
5. Replace the Actor in Apollo Scraper (above). In its query parameters, replace <YOUR_APIFY_TOKEN> with your token.
6. Save. In the workflow that calls this one, add an Execute Workflow node, choose this workflow and send it a query.

What it receives and returns

When Executed by Another Workflow accepts any input. The next node reads one field, query: a list whose first item
holds three lists. Inside a term, a plus sign stands for a space.

{
  "query": [
    {
      "job_title": ["marketing+manager", "head+of+marketing"],
      "location": ["sydney+australia"],
      "business": ["software"]
    }
  ]
}

query can also arrive as that list written out as JSON text, the way an AI agent's workflow tool may pass it. The
workflow answers with one item:

{ "output": "37 new contacts have been added to the Google Sheet!" }

How a run goes

1. JSON puts the incoming query into a field of its own.
2. Create URL builds the search address on https://app.apollo.io/#/people. Job titles become personTitles[],
   places personLocations[] and business keywords qOrganizationKeywordTags[]. It also sorts by Apollo's
   recommendation score and starts on page 1.
3. Apollo Scraper sends that address to the Actor and waits for the contacts.
4. Extract Info keeps eleven fields for each contact. They are the name, the email, the LinkedIn address and the
   seniority, then the title and company of the first job in the contact's history, and the city and state. The rest are
   the country, the company's phone and website, and the first business keyword with its plus signs turned into spaces.
5. Google Sheets stores scraped data writes each contact to the sheet.
6. Edit Fields counts the contacts it wrote, and Limit keeps one item, so the caller gets a single line back.

Change the search

• Who is searched: the query the calling workflow sends.
• How many contacts: totalRecords in the body of Apollo Scraper, 500 in the file.
• Which emails: getPersonalEmails and getWorkEmails in the same body, if your Actor takes them.
• What is saved: the fields in Extract Info, and the headers in your sheet.

Good to know

• Create URL reads only the first item of query. Send one search for each call.
• The count in the reply covers every contact written, updates included.
• Apify ends a synchronous call after 300 seconds, according to its API reference. A large search can time out before the
  contacts come back, so lower totalRecords if it does.
• The file asks for personal emails as well as work ones. Personal addresses and phone numbers are personal data, so
  check the rules where you and your contacts are before you write to anyone.
• The list comes out of Apollo's search through a third party's scraper. Read Apollo's terms before you rely on it.
• The Apify token sits in a query parameter, so take it out before you share the workflow.