
BrowserAct Geo-Search Automation Flow

Brief
A Make.com Workflow for Automated Geo-Based Service Discovery
BrowserAct Geo-Search Automation Flow is a Make.com–based automation designed to help teams automatically discover, analyze, and deliver local service provider data based on user-defined services and geographic locations.
Instead of manually searching Google Maps, scrolling through listings, and collecting contact details one by one, this workflow centralizes the entire geo-search and lead discovery process inside Make—combining AI-driven input validation, BrowserAct-powered web navigation, and structured result delivery into a single automated flow.
What Does BrowserAct Geo-Search Automation Flow Do?
BrowserAct Geo-Search Automation Flow enables users to request local service providers (such as plumbers, contractors, or other service businesses) using natural language, and automatically receive structured, high-quality results without manual browsing.
Finding reliable local providers typically requires repeated Google Maps searches, scrolling through long result lists, opening profiles, and copying details manually. This workflow replaces that process with an end-to-end automation orchestrated entirely inside Make.
Once triggered, Make validates the user’s intent, determines whether the required service and location are provided, and only then initiates a BrowserAct-powered geo-search. The extracted data is further processed by AI and delivered back to the user in a clean, readable format.
Key Features of BrowserAct Geo-Search Automation Flow
- AI-Based Input Validation
Uses AI inside Make to determine whether the user message represents a valid service search, incomplete input, or casual conversation. - Conditional Routing Logic
Automatically routes requests based on input quality, ensuring BrowserAct only runs when required parameters are present. - Automated Google Maps Navigation
Executes geo-based searches on Google Maps through BrowserAct, including scrolling and iterative result loading. - Service Provider Data Extraction
Collects structured business data such as name, rating, phone number, address, and website. - AI-Powered Output Formatting
Converts raw extracted JSON into Telegram-ready HTML messages with strict length control. - Make-Orchestrated Execution
All logic—including routing, iteration, AI calls, and delivery—is managed inside Make for stability and scalability.
What Data Can You Extract with This Workflow?
With BrowserAct Geo-Search Automation Flow, you can collect publicly available local business data from Google Maps, focused on service discovery and lead generation.
Extracted Business Data
- Business name
- Service category
- Rating and review indicators
- Phone number (if available)
- Physical address
- Website URL
How to Use BrowserAct Geo-Search Automation Flow in One Click
Using BrowserAct Geo-Search Automation Flow requires no manual setup or technical configuration.
Users simply send a service request via Telegram (for example, a service type and location). Make automatically validates the request, triggers BrowserAct for geo-based data extraction, processes the results with AI, and sends the formatted response back—without manual searching, copying, or formatting.
Why Automate Geo-Based Service Search?
Manual local service discovery is time-consuming, inconsistent, and difficult to scale. Automating this process allows teams to:
- Discover local service providers faster
- Reduce repetitive manual Google Maps searches
- Ensure consistent data structure and formatting
- Deliver results instantly via messaging platforms
- Scale lead discovery without increasing manual effort
Input & Output
Input
- Natural language service request (service type + location)
Output
- A structured, Telegram-ready message containing:
- Service provider name
- Rating
- Contact details (if available)
- Address
- Website link
Who Is BrowserAct Geo-Search Automation Flow For?
BrowserAct Geo-Search Automation Flow is ideal for:
- Local service marketplaces
- Lead generation and sales teams
- Customer support and concierge bots
- Agencies sourcing local suppliers
- Automation builders using Make and BrowserAct
Working Principle (How It Works)
- Trigger (Telegram)
The workflow starts when a user sends a service-related request via Telegram. - Intent Gating (AI)
Make uses AI to determine whether the input represents a valid service and location request. - If incomplete, the user is prompted for clarification.
- If casual chat, the system responds conversationally.
- Conditional Routing (Make Router)
Based on AI evaluation, Make routes the request to the appropriate execution path. - Geo-Based Data Collection (BrowserAct)
Make triggers BrowserAct to search Google Maps using the validated service and location, scroll results, and extract provider data. - Output Synthesis (AI)
AI converts the extracted JSON into a clean, Telegram-compatible HTML message with character limits enforced. - Result Delivery (Telegram)
Make sends the final formatted results back to the user.
