Pret A Manger Food & Beverage Locations Dataset – UK

Pret A Manger Food & Beverage Locations Dataset – UK

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Pret A Manger is a prominent British sandwich and coffee shop chain that focuses on fresh, handmade food prepared in-shop daily. It is a dominant force in UK city centers and is well-known for its coffee subscription service.

There are 494 Pret A Manger Food & Beverages as of 27 August 2026 in the UK. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Pret A Manger 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: 494 Pret A Manger food & beverages in the UK
  • Contents: Coordinates, addresses, postal codes, administrative divisions, and contact details
  • 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: 27 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.

Map showing the geographical distribution of Pret A Manger locations in UK

Dataset fields included in the CSV:

  • GUID
  • Title
  • Latitude
  • Longitude
  • Street No
  • Street
  • Town
  • Local authority
  • District
  • Postal Code
  • Address
  • Wheelchair
  • Phone
  • Website
  • Opening hours

Data Quality Scorecard

  • Geospatial Accuracy: 98%+ (Verified WGS84 Coordinates)
  • Contact Details (Phone)80%
  • Web Address91%
  • Opening Hours91%

Data Preview: Sample geospatial records from the Pret A Manger dataset in UK

ID Location Title Latitude Longitude Postal Code Full Address
d86aecf... Pret A Manger (Oxford) 51.753053 -1.258350 OX1 3EY 26-27 Cornmarket Street, OX1 3EY, Oxf...
9ca842c... Pret A Manger (Wetherby) 53.946790 -1.368583 LS22 5GT LS22 5GT, North Yorkshire, United Kin...
8298d39... Pret A Manger (Sheffield City Centre) 53.378660 -1.471583 S1 4HN 35 Cambridge Street, S1 4HN, South Yo...
188e08c... Pret A Manger (London) 51.505727 -0.138085 SW1Y 6PP 21 Crown Passage, SW1Y 6PP, Greater L...
1c01a6c... Pret A Manger (London) 51.492034 -0.193067 SW5 9RD 230-232 Earls Court Road, SW5 9RD, Gr...

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 27 August 2026

✅ Data looks right? Add to cart ↑ - or download the free sample first.

Regional Distribution Breakdown

Looking at the geographic distribution, the highest concentration of Pret A Manger locations in the UK is found in England (460 sites). This is followed by Scotland (24 sites) and Wales (4 sites).

Learn more about the brand network in our report: View Report

Also available for the UK

Brand bundle

Top 23 Fast Food and Restaurants Brands in the UK - €560

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 Fast Food and Restaurants Locations in the UK - 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?

  • Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
  • Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
  • Retail Site Selection: Property developers and retail analysts identifying optimal locations, white-spaces, and avoiding cannibalization.
  • Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
  • 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.
  • Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.

Frequently Asked Questions

Q: Is the dataset immediately downloadable after purchase?

A: Yes. The full dataset becomes available for instant digital download immediately after purchase.

Q: Does the dataset include opening hours?

A: Yes, opening hours are included where publicly available and validated during the data standardization process.

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: How recent is this dataset?

A: This dataset was last updated on 27 August 2026 and is periodically refreshed through automated collection and validation workflows.

Analyze this data with AI

Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:

  • "Analyze this Pret A Manger dataset to identify underserved regions in the UK for potential market expansion."
  • "Using this Pret A Manger data, find high-traffic retail corridors in the UK with low food & beverages density for competitive positioning."
  • "Map the concentration of Pret A Manger locations relative to major retail centers and shopping districts in the UK."

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.