How to Understand and Use Amazon Vendor Central Reports
Amazon Vendor Central Reports Categories
Amazon Vendor Central datasets can be grouped into eight main categories: Retail Analytics, Sell-in Operations, Co-Op Invoices, Merchandising, Invoices, Remittance, Dispute Management, Direct Fulfillment. Understanding these datasets and performing specific analyses is crucial for Amazon vendors to optimize operations, improve customer satisfaction, and drive success on the platform
You can access most Amazon vendor reports by signing in to Amazon Vendor Central > Navigate to “Reports” > Select “Analytics” > and selecting the reports of your choice.
To see an individual report, you can also click on any of the listed reports on the categories below, and Click on the link under “Vendor Central report path”.
Retail Analytics
Analyze sales, inventory, and traffic data to optimize stock management, marketing strategies, and demand forecasting.
Sell-in Operations
Track purchase orders and shipments to maintain supply chain flow and avoid delays.
Merchandising
Evaluate the performance of promotional campaigns, Vine enrollments, and coupons to refine marketing strategies.
Invoices
Review and audit invoices to ensure accurate billing and efficient financial management.
Remittance
Monitor Amazon’s payments against your invoices to track cash flow and resolve discrepancies.
Dispute Management
Track and resolve invoice-related disputes promptly for smoother financial operations.
CoOp Invoices
Understand charges for cooperative advertising agreements and promotional costs to verify accuracy and manage expenses.
Direct Fulfillment
Monitor performance and compliance for customer-fulfilled orders to improve operational efficiency.
Amazon Vendor Data Nuances: Key Challenges and Guidance for Working with Vendor Central & SP-API data
Working effectively with Amazon vendor sales data requires understanding some key concepts and “nuances” about how Amazon data works—many of them specific to Amazon vendors. If you are a brand considering a service or software partner, make sure they have explicit experience working with 1P vendors and not just 3P sellers. The data challenges are unique, as you will see below:
1. MULTIPLE VENDOR sales METRICS
Amazon has many different ways of measuring a vendor’s “sales,” depending on the context. Each of them is important and relevant for different use cases.
A critical concept for brands: sell-out drives sell-in at Amazon. In other words, Amazon pays close attention to customer demand and uses it as a leading signal for what they purchase from you, 1-2 weeks at a time. This can be a difficult concept to accept for leaders used to a regular PO cadence and negotiated sales outcomes.
If you are working with sales data for the first time,
Sell-in / PCOGS / Purchase Order Amount: what Amazon orders from you as a Vendor, in your preferred currency. (Source: Purchase Order report)
Purchase Order / PO Units: the quantity of product Amazon orders from you. (Source: Purchase Order report)
Ordered Revenue: the value of customer orders, to be paid by the customer to Amazon. Since orders can be canceled until they are shipped, ordered revenue is considered less “settled.” (Source: Retail Analytics sales report)
Ordered Units: the quantity of product ordered by the customer. (Source: Retail Analytics sales report)
Sell-out / Shipped Revenue: the value of what Amazon actually shipped to the customer. Since Amazon only charges for transactions on shipment, shipped revenue is considered more “settled.” (Source: Retail Analytics sales report)
Shipped units: the quantity of product Amazon shipped to the customer. (Source: Retail Analytics sales report)
Net revenue: shipped revenue, minus customer returns. (Source: manual calculation, or tools like BASIS)
2. Distributor Views: Manufacturing vs. Sourcing View
Amazon Vendor Central provides two different types of distributor views for sales and inventory reports.
Sourcing View: Sourcing view provides data on ASINs that were actually purchased from the vendor by Amazon. Data from this view is determined based on an ASIN’s vendor code, which is the same code that purchase orders are placed against.
Manufacturing View: Manufacturing view provides data on all ASIN’s “owned” by a manufacturer’s brand. Data from this view is determined based on an ASIN’s brand code, regardless of whether the ASIN was procured from the vendor.
In Vendor Central, the Manufacturing view aggregates data for a specific ASIN, no matter its source. This is different from the Sourcing view, which aggregates data according to the vendor that supplied the ASIN.
These systems should work in harmony to ensure the right data is reported to the right group at the right time. In reality, Amazon does not implement this consistently; the availability and "cleanliness" of manufacturing data in particular seems to vary by category. If you sell through many channels and distributors, and many of them sell to Amazon, your manufacturing data will be noisier because of all the inputs.
Read more here: Manufacturing vs. Sourcing View in Amazon Vendor Central
3. Programs: Amazon Retail, Amazon Fresh, Amazon Business
Amazon divides retail data into programs based on how the product was sold. By default Amazon only enables Amazon Retail for brands. If you sell in other programs and want access to the data, submit a ticket to Amazon requesting they enable Amazon Business and/or Amazon Fresh in Retail Analytics for you.
Amazon Retail: products shipped to consumers.
Amazon Business: products shipped to business customers.
Amazon Fresh: special products (usually perishable groceries) delivered to customers from an Amazon Fresh store or related delivery channel.
IMPORTANT: In both Vendor Central UI and the SP-API, this program actually contains all of a vendor’s sales, regardless of program. In other words, if you sell in both Retail and Business, the “Amazon Retail” program will contain sales for both Retail and Business.
If you enable the Amazon Business view, it will contain only Amazon Business data, but “Amazon Retail” will still contain sales for both programs.
Read more here: Understanding Programs — Retail, Business, Fresh
4. Time Period: Daily, Weekly, Monthly, and More
In Vendor Central and via the SP-API, Amazon allows you to access Retail Analytics data at daily, weekly, or monthly intervals. However, there can be small discrepancies between different time periods. For example, the total for a week might not match the sum of daily data due to internal variations in how Amazon processes the metrics.
To reduce these inconsistencies, we recommend aligning your reporting to the same views that your team and Vendor Manager use in Amazon systems. But for your own purposes, it’s a good idea to work with the highest level of detail (such as daily data) when possible. This gives you the flexibility to aggregate the data into any time period you need, even if it’s a strange period like “Turkey 5.”
4. Putting it all together: example SQl query for Retail Analytics Sales
Note: these instructions were written with Reason Automation customers in mind, but you can use the same techniques and queries with any SQL database.
You can use these sales data queries in one of two ways:
pgAdmin: Simply copy and paste the queries into pgAdmin to run them directly within your database environment.
Excel with ODBC: Alternatively, you can use SQL queries within Excel by setting up an ODBC connection.
Follow our Excel Setup Guide for step-by-step instructions on configuring ODBC, allowing you to run and analyze queries directly in Excel.
Anytime you query this table, you should filter by period, distributor view, and program to avoid duplication. The example query below will provide ASIN-level Manufacturing sales by day since January 1, 2024.
Change distributor view: search for
and distributor_view = 'Manufacturing'and replace‘Manufacturing’with‘Sourcing’.Change program: search for
and program = ‘Amazon Retail’and replace‘Amazon Retail’with‘Amazon Business’or another program.
select date , asin , shipped_revenue , shipped_cogs , shipped_units from retail_analytics_sales where period = 'DAILY' and distributor_view = 'Manufacturing' and program = 'Amazon Retail' and date >= '2024-01-01' order by 1 desc, 2 asc
manage your amazon business, not Amazon data.
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What sets Reason apart is its commitment to data quality. Founded by ex-Amazon leaders, the platform is designed to handle complexities like distributor views, program-specific filters, and latency issues that often derail other solutions. This makes Reason the ideal choice for companies seeking to elevate their data strategy without the overhead of managing manual processes or fragile scripts.
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