Step-by-Step: Scraping Google Maps for Local B2B Data with aiFetchly

Direct Answer: Data analysts harvest clean local business intelligence in aiFetchly by configuring Google Maps scraping tasks with targeted keyword categories and geographic coordinates. Through automated headless browser infinite scrolling, rotating SOCKS5 proxy armor, and direct SQLite persistence, analysts extract verified business names, telephone numbers, websites, and review metrics with zero per-record API fees.

In 2026, commercial business brokers and static contact lists suffer severe decay rates exceeding 20% annually. For data analysts mapping regional competitors, identifying local suppliers, or building outbound pipelines for service businesses, static databases fail to capture active storefronts, updated operating hours, and live customer sentiment.

Meanwhile, official Places APIs charge punitive rate-limited per-request fees ($17 to $30 per thousand requests) and restrict data caching.

The aiFetchly desktop application resolves this bottleneck by bringing local data mining onto your physical machine. With native Google Maps extraction, analysts collect structured geospatial datasets without recurring API costs.

Here is a step-by-step tutorial for configuring, running, and exporting Google Maps scraping pipelines in aiFetchly.

Step 1: Define Your Geospatial Scope and Keywords#

1. Open aiFetchly and navigate to the Google Maps module from the left navigation sidebar.
2. Click Create New Task and configure your target parameters:
   • Target Industry / Niche: Enter specific category keywords (e.g., "Commercial Roofing Contractors", "Specialty Dental Clinics").
   • Geographic Focus: Define your search radius around a target city, postal zone, or coordinate center.
3. Name your task descriptively to organize historical sweeps in your project library.

Step 2: Configure Proxy Armor and Behavioral Delays#

To extract hundreds of listings without triggering Google’s anti-bot blocks:

1. Connect your proxy pool in the task settings. As outlined in the aiFetchly platform manual, binding rotating HTTPS or SOCKS5 proxies distributes requests across unflagged IP ranges.
2. Enable randomized delay jitter (2–5 seconds) to emulate natural human scrolling behaviors.
3. Configure your 2Captcha API key in system preferences to resolve automated visual challenges if encountered.

Step 3: Launch Headless DOM Extraction#

Click Start Extraction. aiFetchly initiates a background headless browser instance that interacts with Google Maps directly:

• Infinite Scroll Traversal: Systematically scrolls through the results pane, triggering client-side hydration until all listings in the target radius are captured.
• Structured Field Normalization: Automatically parses each business card into a clean relational schema: Legal Business Name, Category, Physical Street Address, Primary Phone Number, Official Website URL, Star Rating, and Total Review Count.

Step 4: Deduplicate and Stream to Local SQLite#

1. As listings are scraped, aiFetchly streams records in real time into an embedded local SQLite database on your machine.
2. The engine automatically cross-references phone numbers and Google Place IDs to drop duplicate listings across overlapping search grids.
3. Export clean datasets into CSV or JSON formats for downstream modeling, or hand off website URLs directly to Contact Profile Insights for subpage email extraction.

By coupling geospatial targeting with local SQLite storage, aiFetchly empowers data analysts to build pristine, up-to-date business directories entirely from their desktop.

---

Tip: start with one city + one niche keyword, verify 50 rows in SQLite, then widen the radius.