How Actowiz extracted every USA and Canada location from a Maps-based store locator — business name, address, email, phone, website, and description — via a geographic-grid traversal, delivered as a clean, deduplicated spreadsheet.
A client needing complete business-location data — name, address, email, phone, website, and description — for every USA and Canada entry on a Maps-based store locator, delivered into a spreadsheet.
The client needed a complete, structured dataset of business locations listed on a Maps-based store locator, covering the entire United States and Canada. For each location they required six text fields — Business Name, Address, Email, Phone, Website, and Business Description — organised into a spreadsheet (Excel or Google Sheets), with each field in its own cell.
The core requirement was completeness and cleanliness: every location across both countries captured once, with consistent, ready-to-use fields — not a partial or duplicate-ridden export.
Actowiz built a geographic-grid traversal that systematically exercised the locator across all of the USA and Canada, then extracted, cleaned, and deduplicated every location into a single spreadsheet.
| Field | Description |
|---|---|
| Business Name | Location/business name as listed on the locator |
| Address | Full address for the location |
| Contact email, where available | |
| Phone | Contact phone number, where available |
| Website | Location or business website, where available |
| Business Description | Description text associated with the location |
| Step | Phase | Description |
|---|---|---|
| 1 | Scope & Grid Design | Define the USA + Canada geographic grid (city/zip and postal-code coverage) to exercise the full locator. |
| 2 | Locator Traversal | Query the locator across the grid, collecting all returned locations for both countries. |
| 3 | Field Extraction | Capture the six target fields per location from list and detail views. |
| 4 | Dedup & Cleaning | Collapse duplicates to one row per location; trim fields; apply consistent null handling. |
| 5 | QA & Validation | Validate coverage, field cleanliness, and de-duplication before delivery. |
| 6 | Delivery | Deliver the final Excel / Google Sheets dataset, one row per location. |
| Business Name | Address | Phone | Website |
|---|---|---|---|
| Sample Wellness Clinic | 123 Main St, Austin, TX 78701 | (512) 555-0142 | samplewellness.com |
| Northside Health Co. | 88 King St W, Toronto, ON M5X | (416) 555-0199 | northsidehealth.ca |
| Bay Area Nutrition | 450 Market St, San Francisco, CA | (415) 555-0170 | bayareanutrition.com |
Email and Business Description columns are also included per row (omitted here for width), with blanks where the locator did not list them.
| Validation Check | Rule Applied |
|---|---|
| Coverage completeness | Grid traversal verified to cover all USA + Canada regions |
| Mandatory fields | Business Name and Address always populated |
| Null handling | Email, Website, Description left blank when unavailable — never guessed |
| Deduplication | One row per unique location (name + address key) |
| Field separation | Each field in its own cell, trimmed and clean |
| Country scope | Only USA and Canada locations included |
| Metric | Value |
|---|---|
| Service | Store-locator / business-location data extraction |
| Region | United States & Canada |
| Source | Maps-based store locator |
| Fields | Business Name, Address, Email, Phone, Website, Business Description |
| Method | Geographic-grid traversal + deduplication |
| Data State | Clean, one-row-per-location, validated |
| Output Format | Excel (.xlsx) / Google Sheets |
"We needed every location across the US and Canada, not just whatever a few searches returned. Actowiz handed us one clean sheet — no duplicates, every field in its own column — ready to use the moment we opened it."
— Operations Lead, Client Team
Actowiz Solutions extracts store-locator and map-based business data at scale into clean, deduplicated spreadsheets with rigorous QA. Visit actowizsolutions.com to discuss your data requirement.
Our web scraping expertise is relied on by 4,000+ global enterprises including Zomato, Tata Consumer, Subway, and Expedia — helping them turn web data into growth.
Watch how businesses like yours are using Actowiz data to drive growth.
From Zomato to Expedia — see why global leaders trust us with their data.
Backed by automation, data volume, and enterprise-grade scale — we help businesses from startups to Fortune 500s extract competitive insights across the USA, UK, UAE, and beyond.
We partner with agencies, system integrators, and technology platforms to deliver end-to-end solutions across the retail and digital shelf ecosystem.
Tyres Categories data collection from Lazada and Tuhu App helps businesses track tyre prices, brands, availability, and assortment for market insights.
Track Scrape Ready-to-Cook Cut Veg Product Data from Blinkit TN to monitor prices, availability, SKUs, and trends for smarter retail insights.
Brazil Car Rental Pricing Intelligence Report 2026 reveals rental price trends, market shifts, competitor rates, and opportunities for smarter pricing.
Whether you're a startup or a Fortune 500 — we have the right plan for your data needs.