Overview

Amazon provides sellers with tools to manage two important aspects of inventory lifecycle: seasonal demand patterns and end-of-life product designation. Understanding how Amazon classifies your products as seasonal — and knowing when to flag a SKU as non-replenishable — can help you avoid costly stockouts during peak periods and reduce storage fees on products you're phasing out.

Key Points / What Sellers Need to Know

• Amazon automatically classifies seasonal products — Using historical sales data, category trends, keyword analysis, and comparisons with similar items, Amazon identifies which of your products follow seasonal demand cycles.
• Two seasonal flags appear in your dashboard — A "Pre" flag warns you weeks before your product's peak season begins, while an "In" flag indicates the high-demand period is currently active.
• Seasonality tags update monthly — Amazon's backend model refreshes during the last week of each month, incorporating the latest market trends and sales history into your products' seasonal classifications.
• End-of-life (EOL) status is SKU-specific — You can mark individual SKUs as non-replenishable when you plan to sell through remaining inventory without reordering, which stops restock recommendations for that item.
• EOL does not affect active selling — Marking a SKU as end-of-life only changes replenishment-related alerts and recommendations. Listing management, fulfillment, and reporting all continue as normal.

How Seasonal Classification Works

Amazon uses a multi-factor, data-driven approach to determine which products exhibit seasonal demand patterns. The system analyzes multiple years of sales history to find recurring trends, evaluates whether a product's category has established seasonal cycles, and scans listing titles and descriptions for keywords that suggest seasonality. It also compares your product against similar items that have already been flagged as seasonal. For each product that qualifies, Amazon identifies the specific event driving demand — whether that's a holiday, a weather pattern, or a sports season — along with the timing parameters such as season start date, peak periods, and end date. This classification model is continuously refined as Amazon collects more performance data across seasons.