Retail Domain

Grocery-Specific Data Patterns

Alert the user to these common patterns in grocery retail data:

• Seasonality: Weekly (weekend peaks), monthly (payday effects), annual (holidays, summer)
• Promotion effects: Cannibalization across related products, stockpiling behavior, post-promo dip
• Perishability: Fresh categories (bakery, produce, dairy) have different forecasting needs than shelf-stable
• External factors: Weather impacts fresh produce and beverages; fuel prices affect store traffic
• Holiday effects: Easter, Christmas, national holidays create spikes; day-before effects are often larger than the day itself
• Store clustering: Urban vs suburban vs rural stores behave differently; store size matters

Product Family Taxonomy (Common in Grocery)

When working with product categories, use this typical hierarchy:

• Department → Category → Subcategory → Brand → SKU
• Example: Fresh → Dairy → Yogurt → Danone → Danone Natural 500g

Common product families in the tutorial dataset: AUTOMOTIVE, BABY CARE, BEAUTY, BEVERAGES, BOOKS, BREAD/BAKERY, CELEBRATION, CLEANING, DAIRY, DELI, EGGS, FROZEN FOODS, GROCERY I, GROCERY II, HARDWARE, HOME AND KITCHEN, HOME APPLIANCES, HOME CARE, LADIESWEAR, LAWN AND GARDEN, LINGERIE, LIQUOR/WINE/BEER, MAGAZINES, MEATS, PERSONAL CARE, PET SUPPLIES, PLAYERS AND ELECTRONICS, POULTRY, PREPARED FOODS, PRODUCE, SCHOOL AND OFFICE SUPPLIES, SEAFOOD

Forecasting Considerations for Retail

Guide the user toward these best practices:

• Always use a time-based train/test split (never random split for time series)
• Include lag features (sales 7, 14, 28 days ago)
• Include rolling statistics (7-day, 28-day rolling mean/std)
• Day-of-week and month-of-year as cyclical features
• Promotion flags and promotion type as features
• Oil price as a macroeconomic indicator (especially for Ecuadorian data)
• Holiday flags (with lead/lag for pre-holiday shopping)
• Evaluate per store and per product family, not just overall

Personalization Note

This skill contains generic retail knowledge. To adapt for YOUR organization:

• Replace the KPI definitions with your company's specific metric definitions
• Add your product hierarchy and category naming conventions
• Include your company's seasonal calendar and promotion types
• Add store-specific attributes relevant to your chain (format, location tier, etc.)