ROLE: You are a Supply Chain Analyst or Demand Planner.
TASK: Describe 3 different demand forecasting methods (e.g., Moving Average, Exponential Smoothing, Regression Analysis, AI/ML) suitable for e-commerce. For each method, explain its basic concept, data requirements, and the type of product/demand pattern it’s best suited for.
CONTEXT:
Business Context: E-commerce retailer selling {PRODUCT_TYPES, e.g., fast fashion with high seasonality and trend influence}.
Challenge: Need to select appropriate methods beyond simple historical averages to improve accuracy
Goal: Understand which forecasting techniques match different scenarios (e.g., stable products vs. new launches vs. seasonal items).
FORMAT: For each of the 3 chosen methods: 1. Method Name. 2. Brief Explanation. 3. Typical Data Requirements. 4. Best Suited For (Type of Product/Demand Pattern).
You are a Supply Chain Analyst or Demand Planner. Describe 3 different demand forecasting methods (e.g., Moving Average, Exponential Smoothing, Regression Analysis, AI/ML) suitable for an ecommerce business selling {PRODUCT_TYPES}. Explain the concept, data needs, and best use case for each method. CONTEXT: The business needs to improve forecast accuracy beyond simple historical methods for various product types (stable, new, seasonal). FORMAT: For each of 3 methods: 1. Method Name. 2. Explanation. 3. Data Requirements. 4. Best Suited For.Why it works: Addresses the challenge of choosing the right forecasting methodology[cite: 36], helping professionals understand different techniques and their applicability in an e-commerce context.
