Save-On-Foods Supermarket Locations Dataset – Canada
Save-On-Foods Supermarket Locations Dataset – Canada
Save-On-Foods is a major Western Canadian grocery chain headquartered in British Columbia and owned by the Pattison Food Group. It is recognized for its "Western Family" private label and strong focus on local sourcing and loyalty rewards.
There are 188 Save-On-Foods Supermarkets as of 5 August 2026 in Canada. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Save-On-Foods locations, including full address details, administrative divisions, and precise WGS84 latitude/longitude coordinates - structured for GIS, retail analytics, mapping, and AI/RAG workflows.
Dataset Summary
- Dataset Coverage: 188 Save-On-Foods supermarkets in Canada
- Contents: Coordinates, addresses, postal codes, administrative divisions, contact details, and popularity scores
- File Format: Fully geocoded CSV dataset (UTF-8)
- Free Sample: Instantly accessible dataset to verify structure and data quality
- Use Cases: Suitable for GIS, retail analytics, site selection, and AI/RAG workflows
- Last Updated: 5 August 2026
Dataset Methodology:
This dataset is compiled from publicly available business listings, official company sources, and geospatial validation workflows. Automated quality checks and manual analyst reviews are applied to improve coordinate precision, address standardisation, duplicate detection, and overall analytical consistency.
It is periodically reviewed and updated to reflect known network changes, closures, relocations, and newly identified locations.
Dataset fields included in the CSV:
- GUID
- Title
- Latitude
- Longitude
- Street No
- Street
- City
- Admin_level_1
- Admin_level_2
- Postal Code
- Address
- Wheelchair
- Popularity Score
- Phone
- Website
- Opening hours
Data Quality Scorecard
- Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
- Contact Details (Phone)99%
- Web Address99%
- Opening Hours99%
- Popularity Score100%
Data Preview: Sample geospatial records from the Save-On-Foods dataset in Canada
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| 7f120c1... | Save-On-Foods (Sherwood Park) | 53.543697 | -113.316600 | T8H 2A2 | 60 Broadway Boulevard, Sherwood Park,... |
| 33974c5... | Save-On-Foods (Calgary) | 50.881332 | -113.959200 | T3M 1T4 | 19489 Seton Crescent Southeast, Calga... |
| 038037f... | Save-On-Foods (Edmonton) | 53.455410 | -113.380300 | T6T 0G9 | 2390 24 Street Northwest, Edmonton, T... |
| ba7af32... | Save-On-Foods (Chilliwack) | 49.112096 | -121.954700 | V2R 5M4 | 6014 Vedder Road, Chilliwack, V2R 5M4... |
| 583bf0d... | Save-On-Foods (Kamloops) | 50.677252 | -120.331100 | V2C 1Y3 | 450 Lansdowne Street, Kamloops, V2C 1... |
Note: Only a subset of the full dataset fields are displayed here. Download the free sample (option above) to view all fields and verify the data structure.
Why download from Geolocet?
- Instant download - full dataset available immediately after purchase, no waiting, no manual fulfilment
- Free sample first - verify structure, fields, and coordinate precision before you commit
- Analysis-ready CSV - clean, standardised, and compatible with Excel, Python, QGIS, Power BI, and PostgreSQL out of the box
- Regularly updated - last updated 5 August 2026
✅ Data looks right? Add to cart ↑ - or download the free sample first.
Learn more about the brand network in our report: View Report
Also available for Canada
Brand bundle
Top 17 Grocery Brands in Canada - €480
All major chains in one standardised dataset. Best for competitive benchmarking, network analysis, and market sizing across the leading brands.
View Top Brands dataset →Full market coverage
All Grocery Locations in Canada - complete POI dataset
Includes everything in the brand bundle plus independent operators, smaller chains, and local businesses not covered by the top brands. Best for full market mapping, territory planning, and white-space analysis.
View full POI dataset →Need the data in another format?
We can deliver this dataset in alternative formats upon request (GeoJSON, Shapefile, Excel, PostgreSQL import files, etc.). Contact us at contact@geolocet.com.
Who uses this data?
- Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
- Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
- Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
- Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.
- Vendor Distribution: FMCG and wholesale suppliers identifying specific retail locations for direct-store-delivery (DSD) pitching.
- Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
- Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
Frequently Asked Questions
Q: How are addresses standardized?
A: Addresses are cleaned and normalized through automated formatting and validation workflows to improve consistency and usability.
Q: Can this dataset support territory optimization?
A: Yes. The dataset is suitable for defining service territories, balancing regional coverage, and optimizing operational footprints.
Q: What coordinate reference system is used?
A: Coordinates are provided in the global WGS84 geographic coordinate system (EPSG:4326).
Q: Can this data be combined with demographics datasets?
A: Yes. Many customers combine these locations with demographics, income, mobility, and administrative boundary datasets for deeper spatial analysis.
Q: Can this dataset be used for logistics planning?
A: Yes. Many customers use these datasets to optimize delivery territories, distribution networks, route planning, and last-mile logistics analysis.
Q: Is this dataset useful for franchise analysis?
A: Yes. The dataset can support franchise territory planning, network expansion analysis, and regional performance benchmarking.
Q: Is this dataset useful for accessibility studies?
A: Yes. Analysts can combine the coordinates with mobility, transport, and demographics datasets to evaluate accessibility and service coverage.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this Save-On-Foods dataset to identify underserved regions in Canada for potential market expansion.""Rank the top-performing urban areas in Canada for future Save-On-Foods expansion based on existing location density and regional population.""Evaluate how evenly Save-On-Foods locations are distributed across provinces, districts, or municipalities in Canada."
Disclaimer: All brand logos and trademarks displayed are the property of their respective owners and are used strictly for identification purposes. This product consists of geospatial location data only; no images, logos, or trademark rights are included in the downloadable files.