ScraperCity + Google Sheets

What You Can Build

Google Sheets is more than a spreadsheet - it is a real-time collaboration layer for your entire sales team. When you pipe ScraperCity data directly into Sheets, you get a living lead database that your reps can open in a browser with no software install, filter with built-in formulas, and share with a link. Here are the most common pipelines teams build with this integration.

How to Automate Google Sheets with Zapier (Step by Step)

This walkthrough uses the Zapier no-code path. You will end up with a Zap that runs on a schedule, calls the ScraperCity API, and writes every returned lead as a new row in your Google Sheet automatically.

1. 1

   Prepare your Google Sheet

   Create a new Google Sheet. In row 1, add column headers that match the ScraperCity fields you want to capture: Name, Email, Phone, Title, Company, Industry, LinkedIn, Source, Date Added.

   Zapier requires column headers in row 1 to map API response fields to the correct sheet columns. Without headers, the Create Row action will not know where to place each value.

2. 2

   Get your ScraperCity API key

   Log in to ScraperCity and navigate to app.scrapercity.com/dashboard/api-docs. Copy your API key. You will paste it into the Zapier Authorization header as a Bearer token in the format Bearer YOUR_API_KEY.

3. 3

   Create a new Zap with a Schedule trigger

   In Zapier, click Create Zap. Choose Schedule by Zapier as the trigger app. Set the interval - daily at 7am is a common choice for a morning lead sheet. This trigger fires the workflow on your chosen cadence.

4. 4

   Add a Webhooks by Zapier action to call ScraperCity

   Add a Webhooks by Zapier action. Choose the Custom Request event. Set Method to POST and URL to:

   https://app.scrapercity.com/api/v1/apollo

   Set Headers to:

   Authorization: Bearer YOUR_API_KEY
   Content-Type: application/json

   Set the Data (JSON body) to your search parameters. Example for VP of Sales contacts in SaaS:

   {
     "person_titles": ["VP of Sales"],
     "organization_industry_tag_ids": ["Computer Software"],
     "per_page": 100
   }

   Apollo scrapes are asynchronous and take 11-48+ hours to complete. For a daily Zap, you can trigger the scrape one day and download results the next, or use n8n with a polling loop for a fully automated pipeline.

5. 5

   Add a Google Sheets - Create Spreadsheet Row action

   Add a Google Sheets action and choose Create Spreadsheet Row. Connect your Google account and select the spreadsheet and worksheet you prepared in step 1. Zapier will load your column headers automatically.

   Map the ScraperCity response fields to your columns:

   Sheet Column	Map from API response
   Name	full_name
   Email	email
   Phone	mobile_number
   Title	title
   Company	company_name
   Industry	company_industry
   LinkedIn	linkedin_url
   Source	"Apollo" (static text)
   Date Added	Use Formatter > Date > Now

6. 6

   Test and activate

   Click Test step in Zapier to verify a row is created in your sheet with the correct data. If the test succeeds, turn the Zap on. From this point your sheet fills automatically on every scheduled run.

Google Sheets API Tutorial: Python + ScraperCity

If you prefer code, you can connect the ScraperCity API directly to the Google Sheets API using Python. The Google Sheets API is a RESTful interface that lets you read and write spreadsheet data. The spreadsheets.values.append endpoint appends values to the next empty row of an existing table - no row number calculation needed.

Authentication for the Google Sheets API uses OAuth 2.0 with a service account JSON key. For ScraperCity, authentication is a simple Bearer token header. The script below assumes you have already installed google-auth and google-api-python-client.

import requests
import time
from google.oauth2 import service_account
from googleapiclient.discovery import build

# --- Config ---
SCRAPERCITY_API_KEY = "YOUR_SCRAPERCITY_API_KEY"
SPREADSHEET_ID = "YOUR_GOOGLE_SHEET_ID"  # from the sheet URL
SHEET_NAME = "Leads"
SERVICE_ACCOUNT_FILE = "service_account.json"

SCRAPERCITY_BASE = "https://app.scrapercity.com/api/v1"
SCOPES = ["https://www.googleapis.com/auth/spreadsheets"]

# --- Google Sheets client ---
creds = service_account.Credentials.from_service_account_file(
    SERVICE_ACCOUNT_FILE, scopes=SCOPES
)
sheets = build("sheets", "v4", credentials=creds)

# --- Step 1: Trigger a ScraperCity Apollo scrape ---
headers = {
    "Authorization": f"Bearer {SCRAPERCITY_API_KEY}",
    "Content-Type": "application/json",
}
payload = {
    "person_titles": ["VP of Marketing"],
    "organization_industry_tag_ids": ["Computer Software"],
    "per_page": 100,
}
r = requests.post(f"{SCRAPERCITY_BASE}/apollo", json=payload, headers=headers)
run_id = r.json()["runId"]
print(f"Scrape started. runId: {run_id}")

# --- Step 2: Poll until complete (Apollo: 11-48+ hours) ---
while True:
    status_r = requests.get(f"{SCRAPERCITY_BASE}/status/{run_id}", headers=headers)
    status = status_r.json().get("status")
    print(f"Status: {status}")
    if status == "complete":
        break
    time.sleep(1800)  # poll every 30 minutes

# --- Step 3: Download leads ---
dl = requests.get(f"{SCRAPERCITY_BASE}/download/{run_id}", headers=headers)
leads = dl.json().get("data", [])
print(f"Leads returned: {len(leads)}")

# --- Step 4: Append to Google Sheet ---
rows = []
for lead in leads:
    rows.append([
        lead.get("full_name", ""),
        lead.get("email", ""),
        lead.get("mobile_number", ""),
        lead.get("title", ""),
        lead.get("company_name", ""),
        lead.get("company_industry", ""),
        lead.get("linkedin_url", ""),
        "Apollo",
    ])

body = {"values": rows}
sheets.spreadsheets().values().append(
    spreadsheetId=SPREADSHEET_ID,
    range=f"{SHEET_NAME}!A:H",
    valueInputOption="USER_ENTERED",
    insertDataOption="INSERT_ROWS",
    body=body,
).execute()

print(f"Appended {len(rows)} rows to Google Sheets.")

The insertDataOption=INSERT_ROWS parameter tells the Sheets API to insert new rows rather than overwrite existing data. The valueInputOption=USER_ENTERED means values are parsed the same way as if typed manually - dates format correctly and numbers stay as numbers.

Suggested Sheet Structure

Create a Google Sheet with these columns. Each ScraperCity lead maps directly to a row:

Keep the Status and Notes columns at the end and to the right of any auto-populated columns. This way your automation always appends to the correct range without overwriting manual entries.

Troubleshooting Common Issues

The majority of issues with Google Sheets automation scripts fall into three categories: authentication errors, timing problems with async scrapes, and sheet configuration mistakes. Here is how to resolve the most common ones.

Other ScraperCity Data Sources for Your Sheet

Any ScraperCity scraper can feed a Google Sheet. Here are the most commonly used sources beyond Apollo, and what fields they add to your spreadsheet.