Keeping a pulse on purchase orders and product inventory is important. CommerceIQ pulls Amazon purchase orders (PO), inventory health reports, Amazon demand forecast, and product detail page data to help you determine the inventory, ordering, and availability trends for your portfolio.

This article will show you a few ways to keep a handle on it.

Navigate to: CommerceIQ -> Business Overview

Within the Business Overview, you can add ordering and inventory metrics to the performance trend widget.

Once you have a view you like, you can save it as a view so that you can come back to it later.

Navigate to: CommerceIQ -> Reports -> Advanced

Within Reports Builder, you can create customized reports to drill into key aspects of your portfolio. Track Amazon POs, weeks of cover, on-hand inventory, product fill rate, and sell-through, with the ability to filter by category, brand, or SKU level.

The “Inventory & Availability” widget provides a comprehensive view of inventory status at the SKU level. It includes on-hand inventory, open PO quantity, weeks of cover, PO fill rate, and unavailability metrics across your portfolio.

The “Inventory: Low WOC + No Orders” widget template highlights products with less than 4 weeks of cover and no purchase orders in the past 4 weeks. These may indicate potential ordering suppressions. Apply additional filters, such as “active” products or “hero” SKUs, to create a more targeted view.

Navigate to: CommerceIQ -> Recommendations -> Predicted OOS

Within the Predicted OOS recommendation, you can view all items that have less than 4 weeks of cover. The Opportunity to Buy column shows the quantity of inventory needed to bring each item up to 4 weeks of cover.

For example, the product below currently has 0.78 weeks of cover. We recommend supplying 6,618 units to reach the 4-week threshold.

Specifically for this report, weeks of cover is calculated as:

(On Hand Inventory + Open PO Quantity arriving within 14 days) ÷ Average Weekly Sales (trailing 4 weeks)

Navigate to: CommerceIQ -> Sales Forecast

Within this report you can check your sales forecast for the upcoming 26 weeks at each P interval (mean, p70, p80, p90), and review historical performance of amazon's different forecasting algorithms using accuracy metrics (WMAPE, Mean absolute error, Tracking signal, Durbin Watson metric).

We provide several forecasting accuracy metrics to enable you to determine the most accurate forecasting algorithm at the SKU level. This enables your brand to use Amazon's forecast with a higher degree of confidence.

Weighted Mean Absolute Percentage Error.

Formula: [Sum of (Actual-Forecast) * 100) ] / ( Sum of Actuals ) for the chosen time period

Average error in forecast.

Formula: Average of (Actual-Forecast) for the chosen time period

Indicates if there is repeated error in forecast over multiple periods.

Formula: Sum of (Actual - Forecast) / Average of (Forecast - Mean forecast)

Indicates if a forecast error will influence the next forecast.

Formula: (Sum of difference in forecast error between two periods)2 / (Sum of forecast errors)