Analytics

Overview

Returns Analytics transforms return activity into insights you can act on. From spotting trends in return volumes to breaking down reasons by product, warehouse, or outcome, it gives managers the clarity to see where problems start and the data to fix them. With flexible filters and multiple chart views, it turns returns from a hidden cost into a driver for smarter decisions.

How It Works

Returns Analytics can be accessed directly from the navigation bar under Return Analytics. From here, managers can drill into return activity across warehouses and products, filtering by warehouse, return reason, item ID or name, and custom date ranges.

The module offers several chart types to tailor insights:

• Orders returned over time — track overall return trends and seasonality.

• Number of returned products by reason — identify the leading causes of returns.

• Products returned over time — analyze patterns tied to specific SKUs.

• Products that passed inspection by reason — understand which items are fit to be restocked.

• Products that failed inspection by reason — pinpoint items consistently lost due to damage, quality, or policy issues.

By combining filters with these views, teams can zoom in on specific problems, compare performance across warehouses, and uncover where policies or processes need adjustment.

Why It Matters

• Turn return data into actionable insights instead of letting it sit unused.

• Identify the root causes of returns — from product quality to order accuracy — and fix them upstream.

• Compare warehouses to uncover where processes, training, or policies need improvement.

• Protect margins by tracking inspection outcomes and reducing preventable product losses.

• Support smarter decisions in procurement, merchandising, and customer service with concrete data.

Best Practice

Review return reasons regularly and share insights with procurement or merchandising teams to reduce upstream product issues. Track pass/fail inspection rates by warehouse to identify training needs or gaps in quality control. Use time-based charts to measure the impact of new policies, process changes, or supplier adjustments. Finally, align return trends with shopper feedback to get a complete picture of where improvements will have the biggest impact.