Spatic is headquartered in India with teams based out of US and India

Spatic's Proprietary AI Models are trained on the association of various retail stores, categorized by industry and brands, with over 100 location attributes to the level of a pin code or locality or street or a 150 m2 grid. So when we customize these recommendation models for a specific retailer, we consider their business-related factors like competitors, complementary brands, their sales or revenue or footfall from current stores. As a result, the AI recommendation model comprehends the impact and significance of each location attribute concerning the retailer's business. Based on this understanding, the model can predict other profitable locations for the retailer.

Location Intelligence is the use of geospatial and business data to fully realize the situation, identify key factors, uncover patterns and relationships, and present possible solutions. Discover contextual insights for location-based challenges or opportunities to gain a competitive advantage. At Spatic, we have added another dimension which is making predictions using AI/ML to get a holistic view.

Nearly all companies can benefit from location intelligence including retail, real estate, CPG, QSR, Restaurants, hospitality, automobile, etc.

Retailers face many challenges in the gathering data for their needs. ⦁ Discovering the right contextual data ⦁ Ensuring the accuracy of the location data as they are a lot of unverified & inaccurate data (For eg: Google maps, data vendors) ⦁ Integrating this external location data with their internal databases to get the right insights.

Foot traffic data is collected though an SDK built in the mobile apps. The SDK is like a piece of code that tracks the user location. This data is aggregated at the trade area level to get meaningful insights without any personal identifiable information(PII). Spatic is fully compliant with GDPR, CCPA, WPA and numerous other legislations across the world.