Retail Locator AI
Client
<50 employees company
Sector
IT Services
Revenue
€ 4.9M (2024)
Client
<50 employees company
Sector
IT Services
Revenue
€ 4.9M (2024)
From challenge...
Improve call center performance:
- Increase the completeness of store locations across retail chains
- Reduce manual address verification and duplication errors
...to result
The project achieved a 93% first-run success rate across 100 tested retail chains, while automated validation helped scale back manual verification effort by 40%.
From challenge...
Improve call center performance:
- Increase the completeness of store locations across retail chains
- Reduce manual address verification and duplication errors
....to result
The project achieved a 93% first-run success rate across 100 tested retail chains, while automated validation helped scale back manual verification effort by 40%.
The solution
We delivered an AI powered workflow that discovers official store locator pages, extracts locations, and validates them with Google Maps Text Search and Geocoding. Addresses and coordinates are standardized, duplicates and missing stores are flagged, and outputs include an import ready dataset plus an exception report for review.
What we implemented:
- Autonomously discover official store locator pages for each retail chain and extract location data
- Validate and standardize addresses with Google Maps Text Search and Geocoding to ensure accuracy and consistent coordinatesDetect anomalies such as missing stores, duplicates, and inconsistent addresses
- Highlight gaps versus the customer database for targeted fixes
- Deliver an export ready dataset plus an exception report for manual review
Technology stack
- Firecrawl: crawling web ed estrazione su larga scala dalle pagine ufficiali degli store
- Google Maps APIs (Text Search and Geocoding): validazione indirizzi e coordinate geografiche affidabili per ridurre duplicati
- LLM based parsing and anomaly detection pipeline: standardizzazione e segnalazione automatica delle eccezioni per revisione