If your business runs on physical locations (retail stores, dealers, branches, distribution centers, service points) that data probably lives in too many places and you cannot trust any of them to be a golden record. 

The Locations Management Bundle makes Pimcore the single source of truth for location data, and ensures you can keep that data clean, enriched, and syndication-ready.

What's included:

• Location data model covering core identity fields, structured address components, business hours, and open/close dates — fully extensible to match your own schema.
• 
  
• Automated installer that deploys the model into your Pimcore instance without manual class configuration.
• 
  
• Address validation triggered on create and update. Fully configurable mapping lets you point verification services at your pre-existing data model rather than forcing a migration. Reach out to us about support for any specific provider.
• 
  
• Google geocode and time zone services that enrich every address automatically.
• 
  
• Inbound and outbound syndication bundles by TORQ, providing safe syndication. patterns with dedicated status objects — so sync activity is tracked without flooding your object version history with syndication noise
• 
  

Built by TORQ, a Pimcore integration partner, from patterns proven in real enterprise location-data implementations.

Pain Points This Bundle Solves

1. "Our location data lives in five systems and none of them agree." Store hours in one spreadsheet, addresses in the ERP, lat/longs hand-entered in the website CMS, holiday closures in someone's inbox. Every channel shows something slightly different. A MDM-centered location model gives one governed record that every channel draws from.

2. "Bad addresses cost us money after the fact." Undeliverable shipments, returned mail, failed installations, technicians sent to the wrong suite. Most organizations discover an address is wrong only when something fails downstream. Validation on create/update moves the cost of bad data to zero by catching it at entry.

3. "Modeling location data in Pimcore takes time and should be a solved problem." Addresses sound simple until you hit hours-of-operation structures, seasonal open/close dates, multi-country formats, and the question of how addresses attach to existing objects. The bundle ships a proven model and installer so a project starts at "load your data," not "design your schema."

4. "Our store locator and 'open now' logic are always slightly wrong." Missing coordinates, stale time zones, manual lat/long entry that nobody maintains. Automatic geocoding and time zone resolution mean the map pin and the open/closed badge are derived from the address — they can't drift out of sync.

5. "Daylight saving time and multi-region hours break things twice a year." Hard-coded UTC offsets and assumptions about a single time zone fail the moment you operate across regions. Storing resolved time zones per location makes hours display, scheduling, and SLA logic region-aware by default.

6. "Syndication pollutes our version history." Anyone who has synced location data in and out of tools with automated version tracking knows the symptom: object version history buried under system-generated saves, making it impossible to see what a human actually changed. Dedicated syndication status objects keep sync state visible without diluting the audit trail.

7. "We can't adopt a packaged data model because ours already exists." Many bundles force you onto their schema. Configurable mapping of validation services to a pre-existing data model means teams with established Pimcore implementations get the validation and enrichment without a rebuild.

8. "Franchise/dealer onboarding is slow and error-prone." New locations arrive via email and forms, get keyed in manually, and surface on the website weeks later with mistakes. A structured model with entry-time validation and automatic enrichment compresses time-to-live for a new location and removes the manual QA pass.