Optimize your business using rapid retail analytics data

Meena P., Solutions Architect, Selling Partner API; Rugved D., Solutions Architect, Selling Partner API; Garima A., Solutions Architect, Ads API | October 17, 2023

We live in a world where the speed of information matters. Businesses seek new ways to obtain information faster, gather audience insights more quickly, and make decisions at a rapid pace. Rapid retail analytics is a step in that direction, giving both vendors and sellers access to near real-time retail analytics.

This blog post introduces you to rapid retail analytics data, provides information on the metrics and data provided through rapid retail analytics notifications and reports, and shows you how you can use this data to build stronger advertising and retail operations.

Overview

Rapid retail analytics gives both vendors and sellers access to near real-time retail analytics, unlocking access to retail signals aggregated at the hourly grain and within a few minutes of the end of an hour. Previously, metrics shared with brands could be delayed by 48 hours and only at the daily grain via interfaces like the Selling Partner API's Vendor Sales Report or might be available more frequently but not organized by hour. With this product, the higher granularity and lower latency gives brands more opportunity to optimize their campaigns.

Build stronger advertising and retail operations

Selling Partners can use rapid retail analytics for intraday reporting to understand when shoppers engage with a brand at an ASIN level. For example, a selling partner can see that sales performance is strong during a consistent set of peak hours and adjust advertising campaigns to feature high-performing (and inventory-available) ASINs during these times. Beyond understanding ongoing peak shopping hours, businesses can also use rapid retail analytics during key shopping events, like Prime Day or holidays, to make optimal adjustments to advertising strategies and ensure appropriate inventory and product promotion are in place. Additional applications for this feature can vary, but some common ways rapid retail analytics can be used are:

• Trend analysis: Selling Partners can understand days and hours when shoppers are engaging more frequently with their products, leading to the development of “peak” shopping periods for each ASIN. You can utilize the real-time updated data to check which ASINs are receiving more traffic throughout the day. You can feed this data into analytics tools to generate analysis on trending ASINs over a set period of time or during holiday seasons. This data can be key to restock inventory or adjust ad campaigns to or from ASINs.
• Dayparting: Rapid retail analytics give enhanced flexibility to the optimizations that advertisers can make to campaigns, so advertisers can schedule ads or modify budgets based on expected hourly sales and create custom dayparting algorithms. Having hourly data is key to make adjustments to ad campaigns for optimizing the spend of ads budget on the right products that need more marketing and to reach the appropriate audience based on the trends. For more information on how to automate your Ads business, refer to Amazon Ads API.
• Actual vs. expected analysis: With more control to forecast retail metrics, Selling Partners can review actual performance and understand performance against expectations, helping better refine business goals and measure performance.****

How are rapid retail analytics exposed?

Rapid retail analytics are available through both Selling Partner API notifications and reports. For accessing this information using notifications or reports, you need the Brand Analytics Role. To learn more about roles, including how to update roles, refer to Roles in the Selling Partner API.

Rapid retail analytics notifications work in a similar way to other Selling Partner API Notifications - you configure a subscription and have data automatically pushed to that specified location. Instead of polling for information, your application can receive information directly from Amazon when an event triggers a subscribed notification. Sales, inventory, and traffic metrics are included as part of the notification payload. There are three rapid retail analytics notification types available:

To provide flexibility, the same data is also offered via the Selling Partner API Vendor retail analytics reports:

Across all datasets and through both notifications and reports, updated metrics are available after they are processed and aggregated to provide analytics at the ASIN and hour level. Through notifications, updated metrics are sent on the specified schedule, whereas with reports you can begin requesting data on according to the schedule. When using real time analytics reports, you can send requests for past days or per the lookback window.

What information is included in the datasets?

The rapid retail analytics notifications and reports include ASINs that have relevant activities for that hour. This ensures that included ASINs are relevant, avoids “noisy” payloads (where many ASINs show zero or null), and reduces payload size. If an ASIN is not included in a notification (or a report response) for a given hour, that ASIN did not have any relevant activity for that notification/report type.

Timing and history

The lowest granularity of rapid retail analytics is hourly. It is not possible to receive intra-hour notifications or reports. Notifications are sent near the ‘top of the hour’ (generally within 10 minutes of the close of the hour). Reports can be requested minutes after the close of an hour, with specific thresholds based on dataset.

• For Sales and Inventory, information is available to be requested five minutes after the close of each hour. For example, you can request 8:00 AM - 9:00 AM at 9:05 AM for Sales and Inventory datasets.
• Traffic data is available approximately 65 minutes after the close of an hour. For example, you can request 8:00 AM – 9:00 AM Traffic data at 10:05 AM.

Once you configure a subscription, notifications are delivered on a go-forward basis (for example, you cannot request notifications for last week). During the delivery of notifications, you may occasionally see a small number of latent events which did not fully process earlier. For example, at 11:05 AM, you could see the usual 10 AM – 11 AM metrics, plus a small number of notifications for 9 AM – 10 AM. These will generally be for the trailing 1-2 hours and impact a small number of ASINs and events.

Metric definitions

Rapid retail analytics provides the following metrics in sales, inventory and traffic datasets at near real time.

The Highly Available Inventory Units metric is part of the Inventory related notification/report. This represents the number of units for a given ASIN available to be sold on the website with the fastest shipping speed (generally Prime) based on units in Amazon Fulfillment Centers. The units must be in sellable condition and not in customer shopping carts or otherwise bound for other orders (for example, known Subscribe & Save orders) from that given selling partner(either retail or an FBA seller). In other words, when an Amazon shopper notices the product available in the Buy Box as Ships and Sold by Amazon (vendors) or Ships from Amazon (FBA seller), that quantity is reflected in this metric. In a near real-time context, reflecting what shoppers notice allows vendors and FBA sellers to tailor their activities accordingly.

The Glance Views metric is part of the traffic dataset and are reported where a given selling partner is the featured offer. For vendors, this is when retail is the featured offer. Rapid retail analytics captures glance views on detail pages with a variety of offers, including if there is a “multi-offer” Buy Box (featured offer). This means hourly metrics include this shopper activity when there are different offers like Subscribe & Save or Used in addition to the primary offer.

The Ordered Units metric is part of the sales dataset and includes Retail, Fresh and Business. Retail orders of physical products includes bundled ASINs and cancellations. Excluded activity includes:

• Digital orders (for example, Prime Video or Audible orders)
• Free replacement products
• Try-Before-You-Buy (formerly Prime Wardrobe) is not considered an order until the shopper completes the purchase (product is bought out).
• Returns that occur asynchronously and some time after a purchase is confirmed and shipped. This is less relevant in a near-real time context since the sales event (for example, the order) did occur and at some later time/date the shopper decided to initiate a return.

The Ordered Revenue metric, which is part of the sales dataset, represents non-discounted, tax-exclusive price (often called Our Price).

Comparison with retail analytics datasets

Highly available inventory units is different from sellable units in the retail analytics dataset because highly available inventory units factors in known demand considering the count of units that are actually available for sale when making advertising or marketing optimizations. Sellable units is calculated differently and provides the actual units available for sale without factoring the known demand.

Glance views differ from retail datasets particularly due to the methods used to identify traffic from shoppers and remove robotic traffic. Many signals contribute to identifying and classifying traffic from shoppers vs. robotic traffic. Although the best available signals are used to classify traffic intra-day, additional information may lead to glance views being reclassified in the future. This can result in differences (positive or negative) when comparing datasets across granularity (hourly vs. daily, weekly). Also, rapid retail analytics captures glance views on detail pages with a variety of offers like Subscribe & Save or Used (including the primary offer). Amazon Retail Analytics represents glance views differently at a daily or weekly grain excluding the offers.

The rapid retail analytics sales dataset reflects gross activity, while the retail analytics sales dataset reflects ordering activity as the net of quantity changes, order cancellations and returns. This can lead to differences when trying to compare the volume of ordered units between the two. Ordered revenue in the hourly dataset represents non-discounted, tax-exclusive price similar to retail analytics.

How are cancellations handled?

The rapid retail analytics notifications and reports includes all cancellations, including partial cancellations. In a near real-time context, cancellations are an important factor of sales activity which may influence how selling partners make ad optimization decisions. Ordered units may be negative or zero for a given hour and ASIN combination.

Rapid retail analytics represents cancellations based on the time of the cancellation. For example, consider an ASIN B123456789 with an order for one unit and a full cancellation:

Example A

In Example A, the order and cancellation within the same hour would net to 0 for that hour and ASIN combination (+1 quantity, followed by -1 quantity) and the output payload would be:

[
  {
     “startTime”:”2022-07-12T08:00:00Z”,
     “endTime”:”2022-07-12T09:00:00Z”,
     “asin”:”B123456789”,
     “orderedUnits”:0,
     “orderedRevenue”:0
  }
]

Example B

In Example B, the output would have each event (order and cancellation) represented against the hour in which they occurred. The report output would be:

[
  {
     “startTime”:”2022-07-12T08:00:00Z”,
     “endTime”:”2022-07-12T09:00:00Z”,
     “asin”:”B123456789”,
     “orderedUnits”:1,
     “orderedRevenue”:18.99
  },
  {
     “startTime”:”2022-07-12T09:00:00Z”,
     “endTime”:”2022-07-12T10:00:00Z”,
     “asin”:”B123456789”,
     “orderedUnits”:-1,
     “orderedRevenue”:-18.99
  },
]

Example C

In Example C, the output payload would be the same as Example B. The output payload will represent each event (order and cancellation) as they occur. With no events in the 10:00 am hour, this hour and ASIN combination is omitted. Zero values would only return if events occur and net to zero as in Example A.

[
  {
     “startTime”:”2022-07-12T08:00:00Z”,
     “endTime”:”2022-07-12T09:00:00Z”,
     “asin”:”B123456789”,
     “orderedUnits”:1,
     “orderedRevenue”:18.99
  },
  {
     “startTime”:”2022-07-12T09:00:00Z”,
     “endTime”:”2022-07-12T10:00:00Z”,
     “asin”:”B123456789”,
     “orderedUnits”:-1,
     “orderedRevenue”:-18.99
  },
]

Conclusion

This blog provided an overview of rapid retail analytics and how selling partners use real-time retail analytics data that provides the last hour’s insights within minutes for sales, traffic and inventory. For more information on how to get started with reports and notifications, refer to the following resources:

• Reports API Use Case Guide
• Notifications API Use Case Guide
• Reports and Notifications Setup YouTube video

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