find_location
ChatGPTFind a location based on an address or description using geocoding. This tool geocodes the provided address/description to coordinates, then searches for nearby locations in the database. Args: description: Address or location description (e.g., "1234 Pike Street, Seattle, WA" or "Starbucks near Times Square, New York") brand_name: Optional brand name to filter results (e.g., "Starbucks", "McDonald's"). If not provided, the tool will attempt to extract it from the description. radius_miles: Search radius in miles (default: 1.0, max: 10) limit: Maximum number of results to return (default: 10, max: 50) include_closed: If True, include locations that have closed (default: False) Returns: List of matching locations sorted by distance from the geocoded point Examples: - "1234 Pike Street, Seattle, WA" - "Starbucks at 123 Main Street, Chicago, IL" - "Times Square, New York, NY"
find_nearby_locations
ChatGPTFind locations near a geographic point. Provide EITHER an address OR latitude/longitude coordinates. Args: address: Street address to search near (e.g., '123 Main St, Seattle, WA') latitude: Latitude coordinate (use with longitude) longitude: Longitude coordinate (use with latitude) radius_miles: Search radius in miles (default: 10, max: 50) brand_name: Optional brand filter (e.g., 'Starbucks') category: Optional category filter (e.g., 'Coffee Shop') limit: Maximum results (default: 20, max: 50) include_closed: If True, include locations that have closed (default: False) Returns: List of nearby locations sorted by distance
get_brand_info
ChatGPTGet comprehensive information about a brand. Args: brand: Brand name (e.g., 'Starbucks') or brand ID (e.g., 'SG_BRAND_123') include_closed: If True, include closed locations in counts (default: False) Returns: Brand information including name, location count, categories, and geographic distribution
get_brand_location_visits
ChatGPTGet visits for individual store locations within a brand. Args: brand: Brand name (e.g., 'Starbucks') or brand ID (e.g., 'SG_BRAND_123') start_date: Start date in YYYY-MM-DD format end_date: End date in YYYY-MM-DD format comparison_type: 'total' for raw visits, 'yoy' for year-over-year comparison top_n: Optional - Return only top N locations by visits bottom_n: Optional - Return only bottom N locations by visits city: Optional - Filter by city name state: Optional - Filter by state code (e.g., 'CA', 'TX') include_closed: If True, include locations that have closed (default: False) Returns: List of store locations with their visit data
get_brand_visitors
ChatGPTGet visitor demographic segments for a brand (aggregated across all locations). Args: brand: Brand name (e.g., 'Starbucks') or brand ID (e.g., 'SG_BRAND_123') dataset: Demographic segment type - 'age', 'income' (default), 'education', 'tenure', or 'industry' start_date: Start date in YYYY-MM-DD format end_date: End date in YYYY-MM-DD format comparison_type: 'total' for percentages, 'state' or 'nation' for difference with reference Returns: Visitor segment data with percentages and human-readable segment names
get_brand_visits
ChatGPTGet foot traffic visits for a brand over a date range. Args: brand: Brand name (e.g., 'Starbucks') or brand ID (e.g., 'SG_BRAND_123') start_date: Start date in YYYY-MM-DD format end_date: End date in YYYY-MM-DD format granularity: Time granularity - 'daily', 'weekly', or 'monthly' comparison_type: 'total' for raw visits, 'yoy' for year-over-year comparison Returns: Visit data by time period with optional YoY comparison
get_location_info
ChatGPTGet comprehensive information about a specific location. Args: location_id: Location identifier (UUID format, e.g., '36c628b0-692e-4645-b328-64b50004eb09') include_closed: If True, include locations that have closed (default: False) Returns: Location information including name, address, brand, categories, and geographic coordinates
get_location_visitors
ChatGPTGet visitor demographic segments for a specific location. Args: location_id: Location identifier (UUID format) dataset: Demographic segment type - 'age', 'income' (default), 'education', 'tenure', or 'industry' start_date: Start date in YYYY-MM-DD format end_date: End date in YYYY-MM-DD format comparison_type: 'total' for percentages, 'state' or 'nation' for difference with reference Returns: Visitor segment data with percentages and human-readable segment names
get_location_visits
ChatGPTGet foot traffic visits for a specific location over a date range. Args: location_id: Location identifier (UUID format, e.g., '285e9c67-1c16-4335-9a45-2570503fe5e1') start_date: Start date in YYYY-MM-DD format end_date: End date in YYYY-MM-DD format granularity: Time granularity - 'daily', 'weekly', or 'monthly' comparison_type: 'total' for raw visits, 'yoy' for year-over-year comparison Returns: Visit data by time period with optional YoY comparison
get_market_info
ChatGPTGet details about a specific market/shopping center. Args: market_id: Market identifier (UUID format, e.g., '36c628b0-692e-4645-b328-64b50004eb09') Returns: Market information including name, type, location
get_market_tenants
ChatGPTGet list of tenant stores within a market/shopping center. Args: market_id: Market identifier (UUID format) limit: Maximum number of tenants to return (default: 50, max: 100) include_closed: If True, include closed tenant locations (default: False) Returns: List of tenant location details
get_market_visitors
ChatGPTGet visitor demographics for a market/shopping center. Args: market_id: Market identifier (UUID format) dataset: Demographic segment type - 'age', 'income' (default), 'education', 'tenure', or 'industry' start_date: Start date in YYYY-MM-DD format end_date: End date in YYYY-MM-DD format Returns: Visitor demographic segments with percentages and human-readable segment names
get_market_visits
ChatGPTGet foot traffic visits for a market/shopping center over time. Args: market_id: Market identifier (UUID format) start_date: Start date in YYYY-MM-DD format end_date: End date in YYYY-MM-DD format granularity: Time granularity - 'daily', 'weekly', or 'monthly' comparison_type: 'total' for raw visits, 'yoy' for year-over-year comparison Returns: Visit data by time period
search_brands
ChatGPTSearch for brands by name using semantic similarity. Uses ML embeddings and vector search to find brands that match the provided name. Returns brands ranked by similarity (lower distance = higher similarity). Args: brand_name: Brand name to search for (e.g., "Starbucks", "McDonald's", "coffee shop") top_k: Number of top matches to return (default: 10, max: 20) Returns: List of matching brands with their IDs and similarity scores
search_markets
ChatGPTSearch for shopping centers and malls by name, location, or proximity. Supports text-based filters (name, city, state, market_type) and/or geographic search via address or coordinates. When an address or coordinates are provided, results are sorted by distance. Args: name: Market name to search for (partial match, e.g., 'Westfield', 'Plaza') city: City name to filter by (e.g., 'San Francisco', 'Los Angeles') state: State code to filter by (e.g., 'CA', 'TX', 'NY') market_type: Market type to filter by (e.g., 'RETAIL_CENTERS', 'RETAIL_CLUSTERS') address: Street address to search near (will geocode to coordinates) latitude: Latitude coordinate (use with longitude) longitude: Longitude coordinate (use with latitude) radius_miles: Search radius in miles when using address/coordinates (default: 25, max: 50) limit: Maximum number of results to return (default: 20, max: 50) Returns: List of matching markets with their IDs and details
