Scrape physician profiles from BrowserAct into Google Sheets and notify Slack

Open on n8n.io

$20/month : Unlimited workflows

2500 executions/month

Try free

THE #1 IN WEB SCRAPING

Scrape any website without limits

Try free

HOSTINGER

Early Deal
DISCOUNT 20%

Self-hosted n8n

Unlimited workflows - from $4.99/mo

Try free

#1 hub for scraping, AI & automation

6000+ actors - $5 credits/mo

Try free

Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Scrape physician profiles from BrowserAct to Google Sheets This workflow automates the process of building a targeted database of healthcare providers by scraping physician details for a specific l...

Best for

Lead Generation automation workflows
intermediate n8n builders looking for reusable templates

Tools used

n8n-nodes-base.code, n8n-nodes-base.set, n8n-nodes-base.stickynote, n8n-nodes-base.googlesheets, n8n-nodes-base.slack, n8n-nodes-browseract.browseract, n8n-nodes-base.manualtrigger

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Madame AI Team | Kai.

Original n8n.io source

1.1 Workflow description

Title: Scrape physician profiles from BrowserAct into Google Sheets and notify Slack
Workflow name: Scrape physician profiles from BrowserAct into Google Sheets and notify Slack

Scrape physician profiles from BrowserAct to Google Sheets

This workflow automates the process of building a targeted database of healthcare providers by scraping physician details for a specific location and syncing them to your records. It leverages BrowserAct to extract data from healthcare directories and ensures your database stays clean by preventing duplicate entries.

Target Audience

Medical recruiters, pharmaceutical sales representatives, lead generation specialists, and healthcare data analysts.

How it works

Define Location: The workflow starts by setting the target Location and State in a Set node.
Scrape Data: A BrowserAct node executes a task (using the "Physician Profile Enricher" template) to search a healthcare directory (e.g., Healow) for doctors matching the criteria.
Parse JSON: A Code node takes the raw string output from the scraper and parses it into individual JSON objects.
Update Database: The workflow uses a Google Sheets node to append new records or update existing ones based on the physician's name, preventing duplicates.
Notify Team: A Slack node sends a message to a specific channel to confirm the batch job has finished successfully.

How to set up

Configure Credentials: Connect your BrowserAct, Google Sheets, and Slack accounts in n8n.
Prepare BrowserAct: Ensure the Physician Profile Enricher template is saved in your BrowserAct account.
Setup Google Sheet: Create a new Google Sheet with the required headers (listed below).
Select Spreadsheet: Open the Google Sheets node and select your newly created file and sheet.
Set Variables: Open the Define Location node and input your target Location (City) and State.
Configure Notification: Open the Slack node and select the channel where you want to receive alerts.

Google Sheet Headers

To use this workflow, create a Google Sheet with the following headers:

Name
Specialty
Address

Requirements

BrowserAct account with the Physician Profile Enricher template.
Google Sheets account.
Slack account.

How to customize the workflow

Change the Data Source: Modify the BrowserAct template to scrape a different directory (e.g., Zocdoc or WebMD) and update the Google Sheet columns accordingly.
Switch Notifications: Replace the Slack node with a Microsoft Teams, Discord, or Email node to suit your team's communication preferences.
Enrich Data: Add an AI Agent node after the Code node to format addresses or research the specific clinics listed.

Need Help?

Workflow Guidance and Showcase Video

Automate Medical Lead Gen: Scrape Healow to Google Sheets & Slack

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Splitting Items

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 2 - Define Location

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 3 - Documentation

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 4 - Step 1 Explanation

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 5 - Step 2 Explanation

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 6 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 7 - Update Leads

Type / Role: n8n-nodes-base.googleSheets - googleSheets
Config choices: Version 4.7

Block 8 - Alert Team

Type / Role: n8n-nodes-base.slack - slack
Config choices: Version 2.4

Block 9 - Run BrowserAct Workflow

Type / Role: n8n-nodes-browseract.browserAct - browserAct
Config choices: Version 1

Block 10 - On-Demand Execution

Type / Role: n8n-nodes-base.manualTrigger - manualTrigger
Config choices: Version 1

Block 11 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

3. Summary Table

Workflow	Scrape physician profiles from BrowserAct into Google Sheets and notify Slack
Complexity	intermediate
Nodes	11
Categories	Lead Generation
Author	Madame AI Team \| Kai
Published	01 Jan 2026

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/12345/12345.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Lead Generation workflows

Frequently asked questions

What does Scrape physician profiles from BrowserAct into Google Sheets and notify Slack do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Lead Generation use case.

Madame AI Team | Kai

50 workflows

Nodes

n8n-nodes-base.code n8n-nodes-base.set n8n-nodes-base.stickynote n8n-nodes-base.googlesheets n8n-nodes-base.slack n8n-nodes-browseract.browseract n8n-nodes-base.manualtrigger

Complexity

intermediate

Published 01 Jan 2026

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/12345/12345.json

Share Your Workflow

Have a useful automation to share? Publish it and help the community.

Submit Your Template How to Submit

Related Workflows

Find LinkedIn engagement opportunities with Apify, Gemini, Google Sheets and Slack

## Quick overview Youtube Video: https://youtu.be/ehsagyRmri4 This workflow runs on a schedule to scrape recent LinkedIn posts with Apify, stores and evaluates them in Google Sheets using Google Gemini, then enriches shortlisted authors with Apify profile data, saves profile results to a second Sheet, and sends Slack alerts for comment and connection opportunities. ## How it works 1. Runs on a schedule and sets the Ideal Customer Profile (ICP) text used for evaluation. 2. Scrapes LinkedIn posts from Apify using the configured search query and merges the results with existing rows from a Google Sheets “Linkedin_Outreach_oppurtunities” sheet. 3. Limits processing to two posts, upserts the post details into Google Sheets, and sends each post’s content to Google Gemini to score whether it is a comment opportunity. 4. If the post is marked as an opportunity with a confidence score above 80, the workflow updates the corresponding Google Sheets row with the AI reasoning and suggested comment angle. 5. Aggregates the qualified opportunities, compares their author profile URLs against an existing “Profile_scraper” Google Sheet, and keeps only authors that are not already present. 6. Scrapes each new author profile with an Apify profile scraper, uses Google Gemini to score ICP match, saves the profile details and qualification summary to the “Profile_scraper” Google Sheet, and posts a Slack message with the shortlisted profile link. 7. Separately, a Google Sheets trigger watches the opportunities sheet for row updates and sends a Slack alert containing the post link, reasoning, and comment angle. ## Setup 1. Add Apify credentials and verify the actor IDs and input parameters for the LinkedIn post scraper and the profile scraper. 2. Configure Google Sheets access (service account for read/write nodes and a Google Sheets Trigger OAuth connection) and update the document IDs/sheet tabs for both the opportunities sheet and the profile sheet. 3. Add Google Gemini (Google PaLM) credentials and confirm the selected Gemini model names in both AI evaluation steps. 4. Add Slack credentials, choose the target channel, and adjust the Slack message text if needed. 5. Customize the ICP text and the LinkedIn search query/posted time window to match the audience and volume you want to monitor.

View

Enrich existing HubSpot company records with Veridion

## Quick Overview This workflow manually enriches existing HubSpot companies using Veridion, skipping records already marked as enriched and updating HubSpot with matched company details like industry, location, and key firmographics. ## How it works 1. Runs when you manually execute the workflow. 2. Fetches up to 100 companies from HubSpot and includes key properties such as name, domain, phone, and the custom veridion_enriched flag. 3. Stops with a clear error if the veridion_enriched property is missing, otherwise filters to only companies not yet marked as enriched. 4. Retrieves full details for each selected HubSpot company and sends its name, domain/website, and phone to Veridion for enrichment. 5. Checks whether Veridion returns a match and skips companies without a match. 6. Maps key Veridion fields and updates the HubSpot company record with enriched details and sets veridion_enriched to true. ## Setup 1. Create the HubSpot company custom properties veridion_enriched (boolean/checkbox) and veridion_industry (single-line text). 2. Add HubSpot App Token credentials and ensure the HubSpot company list request includes veridion_enriched, veridion_industry, name, domain/website, phone, and hs_object_id. 3. Add Veridion API credentials and confirm your HubSpot companies have at least a name plus a domain/website or phone for best matching.

View

Identify company decision makers with Coresignal and Google Sheets

## Quick Overview This workflow manually pulls company website data from Google Sheets, finds matching companies in Coresignal, and searches for decision-maker employees. It then writes the resulting contact and company details back to a dedicated “Decision makers” sheet in Google Sheets. ## How it works 1. Manually starts the workflow and reads company rows from a Google Sheets spreadsheet. 2. Normalizes each company website URL into a clean domain and searches Coresignal for the matching company by website domain. 3. Processes companies in batches and writes placeholder “no employee found” company details to the “Decision makers” sheet in Google Sheets. 4. For each matched company, searches Coresignal for current employees whose titles match common executive and leadership roles. 5. If the title-based search does not return a single employee ID, runs a broader Coresignal decision-maker search that excludes HR-related roles and departments. 6. Retrieves detailed employee (and, when needed, company) fields from Coresignal and appends or updates the “Decision makers” sheet with names, titles, emails, LinkedIn URLs, and company information. ## Setup 1. Create a Google Sheets OAuth2 connection and set the source sheet (companies with a Website field) and the target “Decision makers” sheet in the Google Sheets nodes. 2. Create a Coresignal API credential in n8n and ensure your plan supports company and employee Elasticsearch DSL search and profile retrieval. 3. Confirm your input sheet includes a website column named either Website or website, and adjust the Coresignal title/department filters to match the decision-maker roles you want to capture.

View

Need Custom Automation?

Get help designing a custom n8n workflow that connects your stack and fits your process.

Scrape physician profiles from BrowserAct into Google Sheets and notify Slack

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Scrape physician profiles from BrowserAct to Google Sheets

Target Audience

How it works

How to set up

Google Sheet Headers

Requirements

How to customize the workflow

Need Help?

Workflow Guidance and Showcase Video

Automate Medical Lead Gen: Scrape Healow to Google Sheets & Slack

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Splitting Items

Block 2 - Define Location

Block 3 - Documentation

Block 4 - Step 1 Explanation

Block 5 - Step 2 Explanation

Block 6 - Sticky Note

Block 7 - Update Leads

Block 8 - Alert Team

Block 9 - Run BrowserAct Workflow

Block 10 - On-Demand Execution

Block 11 - Sticky Note1

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions