Google Places API Segmented Business Data Extraction
A Python-based Google Places API extraction engine that programmatically segments geographic areas, paginates results, enriches with Place Details, and exports structured Excel-ready datasets. Standard Google Places API queries return limited results per request, making it difficult to extract full business coverage within dense regions using a single search call
Case visual
Add gallery images to show system screenshots, dashboards, workflow outputs, or delivery samples.
Pagination Handling
Grid Subdivisions
Businesses Extracted
Deduplication
Standard Google Places API queries return limited results per request, making it difficult to extract full business coverage within dense regions using a single search call.
Developed a modular Python scraping engine using the official Google Places API (Places Search + Place Details) that divides target locations into smaller geographic bounding boxes, paginates through all available results, deduplicates by place_id, enriches listings, and exports structured Excel files.
After implementation, Segmented, paginated, enriched, and fully exported dataset with near-complete business coverage per defined region.
Behind the Scenes
How the system moved from problem to controlled execution.
Problem
Standard Google Places API queries return limited results per request, making it difficult to extract full business coverage within dense regions using a single search call. Dense urban areas exceed single-query result caps. Manual extraction per ZIP code is inefficient and incomplete. No built-in full-area coverage logic in default API usage. Duplicate results across overlapping radius searches.
System Built
Developed a modular Python scraping engine using the official Google Places API (Places Search + Place Details) that divides target locations into smaller geographic bounding boxes, paginates through all available results, deduplicates by place_id, enriches listings, and exports structured Excel files. Workflow covered: User inputs business type, ZIP code, country code, and radius; Convert ZIP code into latitude/longitude coordinates; Divide radius area into multiple smaller bounding boxes (grid segmentation); Execute Places Search query per grid box; Handle API pagination.
What Changed
100% pagination handled automatically. 9 grid subdivisions for full coverage. 469 businesses extracted (Sample: ZIP 1080, BE). Deduplicated results cleaned via place_id. Algorithmic geographic subdivision for near-complete area coverage. Pagination handling with automatic next_page_token logic.
Before / After
What changed after the system was rebuilt.
Area coverage
Before
Limited single-query results
After
9-grid full coverage
Pagination handling
Before
Manual
After
100% automated
Data quality
Before
Duplicate results
After
Deduplicated via place_id
Output format
Before
Raw API responses
After
Structured Excel export
Delivery Scope
What was included in the system delivery.
Python Google Places extraction engine
Geographic grid segmentation logic
Automated pagination handling
Place Details enrichment
Deduplicated Excel-ready exports
Controls
Checks built in to keep the workflow reliable.
Place ID deduplication across overlapping search grids
Rate-limit aware request timing
Automatic output directory handling
Configurable search inputs for business type and location
Pagination waits for next_page_token availability
Tools & Stack
Tools used to build, connect, and deliver this system
Similar System
Want similar results?
Share the manual process, messy data flow, or system gap you want to fix. We will help you understand what can be rebuilt into a controlled operating system.