AWS for Industries

Enhancing Retail Store Inventory Management through RFID Technology & AWS

Guidance for RFID Store Inventory Management on AWS

The need for RFID (Radio Frequency Identification) is growing. Retailers face many challenges in managing their inventory, including out-of-stock situations, misplaced items, and shrinkage. These challenges can impact the bottom line and hurt the customer experience. To address these issues, retailers are increasingly turning to RFID technologies. According to ICD, 80% of retailers will be in the process of (or will already have completed) putting some form of RFID capability in place.

RFID is a wireless technology that allows objects to be identified and tracked using radio waves. By leveraging RFID technology, retailers can track inventory in real-time, making it easier to manage, count, and identify inventory while detecting shrinkage. The use of RFID technology in retail is growing rapidly—driven by the need for better inventory management, the rise of omnichannel retail, and the increasing use of RFID technology in supply chain management.

If you are a retailer looking to implement RFID, Amazon Web Services (AWS) Smart Store solutions can help make it easier for retailers to implement RFID technology. AWS has a range of solutions that can be customized to meet the specific needs of individual retailers. By leveraging AWS Smart Store solutions, retailers can take advantage of the benefits of RFID technology without the need for extensive technical expertise or infrastructure investments.

In this blog, we’ll explore further how RFID technology, as highlighted in our new Solution Guidance for RFID Store Inventory on AWS, can:

  • Revolutionize inventory management
  • Improve store inventory counting
  • Aid in inventory identification
  • Detect shrinkage

We’ll also discuss how AWS Smart Store solutions make it easier to implement RFID technology and the benefits of leveraging RFID in physical stores.

RFID overview and value proposition for Retailers

RFID technology consists of four main components: an RFID tag, an RFID antenna, an RFID reader, and a database.

Figure 1 RFID Technology Summary

Figure 1: RFID Technology Summary

The RFID system consists of several components working together. At the core is the RFID tag, a small device attached to the tracked object, containing a microchip with unique identification data and an antenna to receive radio waves from the reader. The RFID antenna, connected to the reader, emits radio waves to activate the tag and collect its data, offering flexibility in design for various applications. The RFID reader, equipped with a transmitter and receiver, sends a radio signal to detect the tag, collects its data, and can be connected to a computer or integrated into a handheld scanner.

All the information gathered by the system is stored and processed in a database, which can be hosted on-site or in the cloud, enabling authorized personnel to track and report data in real-time. This facilitates inventory management, enhances supply chain efficiency, and improves customer service for retailers.

RFID technology offers numerous benefits for retailers. It enhances inventory management by improving accuracy, reducing time spent on counting, and enabling real-time tracking. This helps retailers promptly address out-of-stock situations, misplaced items, and inventory discrepancies, leading to reduced costs and improved customer satisfaction.

Additionally, RFID facilitates faster and more accurate identification of inventory, enabling quick restocking and increased sales. It also aids in preventing shrinkage by tracking item movement, alerting staff to suspicious activity, and optimizing store layouts. Overall, RFID technology empowers retailers to:

  • Reduce costs
  • Enhance customer satisfaction
  • Increase sales
  • Protect against shrinkage
  • Create a safer shopping environment

We will be providing more details for four different flows in the following sections.

Managing Store Inventory using RFID

Business use case and outcome: 

RFID provides retail brands with improved inventory accuracy and stock reliability, which leads to higher sales and customer satisfaction. It also provides real-time and specific information on inventory levels and stock details such as quantity, models, color, and size. Because RFID tags track all your items, you can eliminate stocking issues and improve security in your store. Scanning products with a RFID reader also lowers the time spent on inventory, resulting in an increase in productivity and less manual work for employees. This allows staff to spend more time on customers and sales than on counting stock. With a handheld scanner, one person can scan multiple items in minutes, leading to more frequent (and faster) stock takes. In-store inventory is synced regularly with global inventory management and other downstream systems to ensure improved operation and forecast planning—leading to a better customer experience.

Figure 2 Reference Architecture for Managing Store Inventory using RFID on AWS

Figure 2: Reference Architecture for Managing Store Inventory using RFID on AWS

Let’s walk through a typical store using RFID to manage inventory on AWS.

Walkthrough

  1. As inventory items are scanned in the store, data is collected and then sent to AWS IoT Core using an encrypted MQTT protocol. This is where the data enters the Inventory Event Hub. These In-store RFID scanners can also link to in-store Point of Sale and Inventory Management systems to enable useful functionality.
  2. The Inventory Event Hub handles the ingestion of inventory scan events and routing to other services. The design of the hub is decoupled allowing for downstream subscribers to be flexible. AWS IoT Core uses AWS Lambda to complete data transformation tasks before being published to Amazon Event Bridge.
  3. The Inventory Analytics layer reads all events coming from Amazon EventBridge. Amazon Kinesis Data Firehose loads data to Amazon Simple Storage Service (Amazon S3) for analytics and machine learning (ML) use cases such as store replenishments.
  4. The Global Inventory Management System subscribes to Amazon EventBridge for the purpose of maintaining near real-time inventory updates in Amazon DynamoDB. As updates take place, AWS AppSync shares them back to the In-Store Inventory Management System for reconciliation.
  5. Amazon EventBridge posts events to other enterprise systems registered as event targets based on defined rules. The Inventory Event Proxy accepts mobile scans (QR codes, NFC, and more) through an Amazon API Gateway. The event is matched to an RFID tag stored in Amazon DynamoDB and passed to the Inventory Ingestion Hub for processing.

Counting Store Inventory using RFID

Business use case and outcome:

One notable advantage is the significant reduction in human effort required to count inventory accurately. With RFID tags attached to each item, the arduous and time-consuming process of manual counting becomes a thing of the past. This not only saves valuable labor hours but also minimizes the risk of errors, ensuring inventory records remain precise and up to date. Additionally, RFID enables the swift and precise location of items within the store or warehouse. By using RFID readers, staff members can quickly identify the exact whereabouts of each item, eliminating unnecessary search time and enhancing overall operational efficiency. Another crucial advantage is the reduction in missed sales resulting from inaccurate inventory. With RFID’s real-time tracking capabilities, retailers can maintain accurate stock levels, preventing instances of out-of-stock situations, and ensure that customers always find the items they need. By employing RFID for inventory management, retailers can streamline operations, improve customer satisfaction, and boost their bottom line.

Reference architecture Overview:

Figure 3 Reference Architecture for Counting Store Inventory using RFID on AWS

Figure 3: Reference Architecture for Counting Store Inventory using RFID on AWS

Let’s now walk through a typical store using RFID to count inventory on AWS.

Walkthrough

  1. Inventory can be audited quickly by scanning both inventories stocked on shelves and hung on racks. Scanned tag data is sent to AWS IoT Greengrass for pre-processing and de-duplication.
  2. AWS IoT Greengrass is able to notify the In-Store Inventory Management system (IMS) of the inventory scans through the local store network. The In-Store IMS runs on Amazon ECS Anywhere to allow for centralized management and deployment of updates.
  3. AWS IoT Greengrass also sends the inventory scanned IDs along with the store location to the RFID Inventory Ingestion Hub for processing and routing.
  4. The Global IMS subscribes to the inventory scan events in the Inventory Ingestion Hub in order to reconcile any inventory discrepancies.
  5. Once the inventory audit is completed, the Global IMS returns any updates or notifications back to the In-Store IMS completing the asynchronous update loop.
  6. Inventory discrepancies are reconciled at the store within the In-Store IMS, which then updates the Global IMS to ensure that both systems are current and in-sync.

Identifying Inventory using RFID

Business use case and outcome:

Deploying RFID enables retailers to provide personalized item recommendations, potentially leading to higher average purchases. By utilizing RFID tags and readers, retailers can gather detailed information about each customer’s preferences and past purchases, enabling them to offer tailored suggestions and enhance the shopping experience. Moreover, RFID’s real-time tracking capabilities allow retailers to capitalize on items that are temporarily out of stock by recommending alternative products available at nearby locations—boosting sales and customer satisfaction. Another advantage is the ability to gain valuable insights into in-store customer browsing trends. RFID technology provides accurate data on the movement and interaction of products within the store, enabling retailers to identify popular areas, optimize product placement, and make informed decisions to enhance the overall shopping experience.

Reference architecture Overview:

Figure 4 Reference Architecture for Identifying Inventory using RFID on AWS

Figure 4: Reference Architecture for Identifying Inventory using RFID on AWS

Let’s walk through a typical store using RFID to identify inventory on AWS.

Walkthrough

  1. A Store user scans products they are interested in with the Store App.
  2. The Store App then makes an HTTPS request to Amazon Route 53 to provide domain name service (DNS) translation to hosted service. The request is routed to the nearest Amazon CloudFront (CDN) edge location.
  3. An AWS WAF is used to apply rules to the traffic to protect against exploits and attacks.
  4. The static website and assets (html, image, video, and more) stored in Amazon S3 are then returned back to the user.
  5. AWS AppSync handles user queries by routing to resolvers such as AWS Lambda.
  6. AWS Lambda uses ProductID as key to return detailed info such as size, color, options, characteristics and current inventory stored in Amazon DynamoDB. ProductID is the partition key for the DynamoDB table which stores Inventory data.
  7. AWS Lambda is also able to use ProductID to return recommendations for items frequently purchased together from Amazon Personalize. AWS Glue is able to crawl the Product Catalog and Interaction History databases and create a data catalog which is stored in Amazon S3.
  8. Extract Transform and Load (ETL) jobs can be triggered within AWS Glue to transform data to the required format for Amazon Personalize training jobs.
  9. Datasets are added to an S3 bucket and a training cycle is initiated in Amazon Personalize.

Detecting Shrink using RFID

Business use case and outcome:

By implementing RFID systems, stores can effectively deter theft by triggering alarms when unpaid items leave the premises, leading to a substantial reduction in inventory shrinkage. Moreover, the integration of RFID with business intelligence tools allows for in-depth analysis of shrinkage patterns. Through shrinkage timing analysis, retailers can gain valuable insights into the frequency and timing of shrinkage incidents. Furthermore, individual product shrink analysis helps identify which specific items are more prone to shrinkage, enabling targeted preventive measures. Additionally, by conducting shrinkage pathway analysis, retailers can understand the pathways within the store that contribute to shrinkage, enabling them to optimize store layouts and security measures accordingly. Overall, RFID systems provide a comprehensive approach to shrink detection and analysis, empowering retailers to better manage their inventory and mitigate losses.

Reference Architecture Overview:

Figure 5 Reference Architecture for Detecting Shrink using RFID on AWS

Figure 5: Reference Architecture for Detecting Shrink using RFID on AWS

Let’s now walk through a typical store using RFID to detect inventory shrinkage on AWS.

Walkthrough

  1. When an item is ready to be purchased, that item will be presented to the Point of Sale (POS). The SKU/RFID will be scanned at the POS to complete the purchasing transaction. The POS will update the In-Store IMS. The process updates the inventory to reflect that the item has been purchased.
  2. The In-Store IMS publishes the sale activity details to AWS IoT Greengrass. AWS IoT Greengrass sends the inventory scanned IDs, along with the store location, to the RFID Inventory Ingestion Hub for processing and routing.
  3. When the transaction is completed and a customer is leaving the store with the item, the item will be scanned again by stationary RFID readers located at the doorways.
  4. The stationary doorway RFID readers pass the RFID tag information to AWS IoT Greengrass which will leverage AWS Lambda to check the In-Store IMS.
  5. The results of the AWS Lambda inventory check will return either that the item has been purchase or not. If the item has not been purchased, AWS IoT Greengrass can then trigger an in-store alarm and sends the event to the RFID Inventory Ingestion Hub for further processing.
  6. RFID events in the RFID Inventory Ingestion Hub can trigger additional event driven processing. Items purchased will update the Global IMS specifically the DynamoDB to ensure the inventory data is updated with appropriate status.
  7. Items passing the stationary RFID readers at the doorways unpaid for will trigger an alert through Amazon Simple Notification Service (Amazon SNS) to the security team.
  8. The Global IMS will be updated with items purchased and items unpaid for. The security team will be able to further review and visualize the data to understand how items are leaving the store through Amazon QuickSight.

Unlocking the Potential of RFID with AWS

In conclusion, the benefits of RFID technology for retailers are clear. By improving inventory accuracy and efficiency, identifying inventory, detecting shrinkage, and improving store inventory counting, retailers can reduce costs, increase sales, and improve the overall customer experience. Furthermore, AWS Smart Store solutions make it easier for retailers to implement RFID technology and take advantage of these benefits.

If you’re a retailer looking to improve your inventory management, and provide a better customer experience, it’s time to consider the advantages of RFID technology. With the growing adoption of this technology and the clear benefits it offers, now is the perfect time to start exploring how RFID and AWS Smart Store solutions can help your business thrive. Don’t wait—take the first step towards revolutionizing your inventory management today. Engage with our new Solution Guidance for RFID Store Inventory on AWS now.

Help from AWS Partners

In addition, retailers can connect with AWS Retail Competency Partners, offering retail solutions and expertise on AWS. These AWS Partner offerings have been validated for demonstrated technical proficiency and proven retail customer success in specialized areas, such as advanced retail data science and edge computing.

Every use case is different, and every project requires a unique approach. The reference architecture presented in this document is an illustration of a systematic approach to a typical RFID business potential. In some cases, users can skip certain stages or combine them—or perhaps there might be additional steps in the journey. Try out these approaches to fully embrace the business potential of leveraging RFID in conjunction with power of the AWS cloud.

Find out how AWS can support your retail transformation with Smart Store solutions. Learn more at aws.amazon.com/retail/.

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Neelam Koshiya

Neelam Koshiya

Neelam Koshiya is an enterprise solutions architect at AWS. With a background in software engineering, she moved organically into an architecture role. Her current focus is to help enterprise customers with their cloud-adoption journeys for strategic business outcomes. She is passionate about innovation and inclusion. In her spare time, she enjoys reading and being outdoors.

Damon Dryden

Damon Dryden

Damon Dryden is a skilled enterprise solutions architect at Amazon Web Services (AWS). With a strong background in networking, he loves working on retail projects and updating the shopping experience. He was born and raised in North Idaho, where he and his family run a small farm. He graduated from Boise State University and enjoys connecting with his customers, often lightening the mood with his collection of cow jokes.

Jacob Cravinho

Jacob Cravinho

Jacob Cravinho is an enterprise solutions architect at AWS. He comes from a background in software engineering focusing on the retail vertical. He loves a challenge and is always in search of the next great meal.

Justin Swagler

Justin Swagler

Justin Swagler is worldwide head of Physical Retail at AWS, where he leads the global strategy and thought leadership for physical retailing. Justin has 15+ years of consumer packaged goods, retail, and strategy experience spanning innovation strategy, retail operations, product development, and executive leadership. He is passionate about shepherding organizations to strategically innovate and reinvent consumer experiences. He holds an undergraduate degree from the University of Illinois at Urbana-Champaign and an MBA from the Kellogg School of Management.