The dataset is about a retail sales dataset containing information about store sales for various products over time.

The specific variables include: Store: Unique identifier for the store location Date: Calendar date of the sales data Product: Name of the product being sold Weekly Sales: Total number of units sold for the product in a week Inventory Level: Number of units of the product currently in stock at the store Temperature: Average temperature for the week at the store location Past Promotion of Product (in lac): Total value (in lakhs) of any past promotions for the product during the week (1 lac = 100,000) Demand Forecast: Predicted number of units to be sold for the product in the next week (provided for baseline model comparison)

This dataset can be used for various analytical purposes related to retail sales and inventory management, including:

Demand forecasting: By analyzing historical sales data, temperature, past promotions, and other relevant factors, you can build models to predict future demand for products. This information can be used to optimize inventory levels and prevent stock outs or overstocking. Promotion analysis: You can compare sales data during promotional periods with non-promotional periods to assess the effectiveness of different promotions and identify products that respond well to promotions. Product analysis: By analyzing sales data across different stores and time periods, you can identify which products are most popular and in which locations. This information can be used to inform product placement, marketing strategies, and assortment planning. Store performance analysis: You can compare sales performance across different stores to identify top-performing stores and understand factors contributing to their success. This information can be used to identify areas for improvement in underperforming stores.

By utilizing this dataset for these analytical purposes, retail organizations can gain valuable insights into their sales patterns, customer behavior, and inventory management practices. This information can be used to make data-driven decisions that improve sales performance, profitability, and customer satisfaction.

Graph and download economic data for Retailers Inventories (RETAILIMSA) from Jan 1992 to Apr 2025 about inventories, retail, and USA.

China Wholesale & Retail Inventory: Total data was reported at 4,211.718 RMB bn in 2018. This records a decrease from the previous number of 4,339.700 RMB bn for 2017. China Wholesale & Retail Inventory: Total data is updated yearly, averaging 1,536.815 RMB bn from Dec 1998 (Median) to 2018, with 21 observations. The data reached an all-time high of 4,339.700 RMB bn in 2017 and a record low of 352.760 RMB bn in 2004. China Wholesale & Retail Inventory: Total data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.RJA: Wholesale and Retail Inventory: Above Designated Size Enterprise.

Inventory Management Software in Retail Market Outlook

The global inventory management software market in the retail sector was valued at approximately $2 billion in 2023 and is projected to reach around $4.5 billion by 2032, registering a compound annual growth rate (CAGR) of 9.5% over the forecast period. This remarkable growth in market size can be attributed to the increasing adoption of advanced technologies by retailers to enhance operational efficiency, reduce costs, and improve customer satisfaction. The integration of artificial intelligence and machine learning has significantly improved forecasting accuracy, allowing retailers to maintain optimal stock levels and reduce instances of overstocking and stockouts, which are critical growth factors driving the market.

One of the primary growth factors is the rising demand for real-time inventory tracking solutions. As e-commerce continues to boom, the need for precise and efficient inventory management systems becomes ever more crucial. Retailers are moving towards these systems to keep up with the rapid pace of sales and to manage multiple sales channels efficiently. Real-time tracking helps retailers respond swiftly to dynamic market conditions, thereby enhancing customer satisfaction and loyalty. Additionally, the growing trend of omnichannel retailing is demanding more sophisticated inventory management software that can seamlessly integrate across various platforms, further propelling market growth.

Another significant growth driver is the increasing focus on reducing operational costs. Inventory management software helps in minimizing carrying costs, labor costs, and shrinkage by providing accurate data analytics and insights. Retailers are increasingly recognizing the value of data-driven decision-making in inventory management. By leveraging advanced analytics, businesses can optimize their inventory turnover rates, identify slow-moving items, and manage supplier relationships more effectively. This data-centric approach not only reduces operational costs but also enhances the overall profitability of retail businesses, thereby driving the adoption of inventory management solutions.

The advancement in mobile technology and the proliferation of smartphones have also contributed to the market's growth. Retailers are increasingly adopting mobile-based inventory management solutions that provide the flexibility to manage inventory on the go. This trend is particularly prevalent among small and medium enterprises (SMEs) that seek cost-effective solutions to manage their inventory without the need for extensive infrastructure. Mobile solutions also facilitate better communication and coordination among different departments, ensuring a smoother workflow, which is essential in a fast-paced retail environment.

From a regional perspective, North America holds the largest share of the inventory management software market in the retail sector. This dominance is attributed to the region's advanced technological infrastructure, high adoption rates of cloud-based solutions, and the presence of major retail giants that continuously strive to optimize their supply chain operations. The Asia-Pacific region, however, is expected to witness the fastest growth during the forecast period, driven by the rapid expansion of the retail sector in emerging economies like China and India, coupled with increasing investments in technology adoption.

Component Analysis

The inventory management software market in retail can be segmented by components into software and services. The software segment is expected to dominate the market throughout the forecast period. With the increasing need for automation and efficiency in retail operations, more businesses are investing in comprehensive software solutions that offer real-time data processing, analytics, and seamless integration with existing systems. These software solutions are designed to handle complex inventory tasks, such as demand forecasting, replenishment planning, and order management, which are critical for maintaining competitive advantage in the retail sector.

Manufacturing Inventory Software is playing a crucial role in transforming the retail inventory management landscape. This software provides retailers with advanced tools to manage their supply chains more effectively, ensuring that products are available when and where they are needed. By utilizing manufacturing inventory software, retailers can gain better visibility

Graph and download economic data for Retailers: Inventories to Sales Ratio (RETAILIRSA) from Jan 1992 to Apr 2025 about ratio, inventories, sales, retail, and USA.

Dataset

This dataset was created by Dahalia Howell

Contents

MealMe provides comprehensive grocery and retail SKU-level product data, including real-time pricing, from the top 100 retailers in the USA and Canada. Our proprietary technology ensures accurate and up-to-date insights, empowering businesses to excel in competitive intelligence, pricing strategies, and market analysis.

Retailers Covered: MealMe’s database includes detailed SKU-level data and pricing from leading grocery and retail chains such as Walmart, Target, Costco, Kroger, Safeway, Publix, Whole Foods, Aldi, ShopRite, BJ’s Wholesale Club, Sprouts Farmers Market, Albertsons, Ralphs, Pavilions, Gelson’s, Vons, Shaw’s, Metro, and many more. Our coverage spans the most influential retailers across North America, ensuring businesses have the insights needed to stay competitive in dynamic markets.

Key Features: SKU-Level Granularity: Access detailed product-level data, including product descriptions, categories, brands, and variations. Real-Time Pricing: Monitor current pricing trends across major retailers for comprehensive market comparisons. Regional Insights: Analyze geographic price variations and inventory availability to identify trends and opportunities. Customizable Solutions: Tailored data delivery options to meet the specific needs of your business or industry. Use Cases: Competitive Intelligence: Gain visibility into pricing, product availability, and assortment strategies of top retailers like Walmart, Costco, and Target. Pricing Optimization: Use real-time data to create dynamic pricing models that respond to market conditions. Market Research: Identify trends, gaps, and consumer preferences by analyzing SKU-level data across leading retailers. Inventory Management: Streamline operations with accurate, real-time inventory availability. Retail Execution: Ensure on-shelf product availability and compliance with merchandising strategies. Industries Benefiting from Our Data CPG (Consumer Packaged Goods): Optimize product positioning, pricing, and distribution strategies. E-commerce Platforms: Enhance online catalogs with precise pricing and inventory information. Market Research Firms: Conduct detailed analyses to uncover industry trends and opportunities. Retailers: Benchmark against competitors like Kroger and Aldi to refine assortments and pricing. AI & Analytics Companies: Fuel predictive models and business intelligence with reliable SKU-level data. Data Delivery and Integration MealMe offers flexible integration options, including APIs and custom data exports, for seamless access to real-time data. Whether you need large-scale analysis or continuous updates, our solutions scale with your business needs.

Why Choose MealMe? Comprehensive Coverage: Data from the top 100 grocery and retail chains in North America, including Walmart, Target, and Costco. Real-Time Accuracy: Up-to-date pricing and product information ensures competitive edge. Customizable Insights: Tailored datasets align with your specific business objectives. Proven Expertise: Trusted by diverse industries for delivering actionable insights. MealMe empowers businesses to unlock their full potential with real-time, high-quality grocery and retail data. For more information or to schedule a demo, contact us today!

United States - Retailers: Inventories to Sales was 1.29000 Ratio in March of 2025, according to the United States Federal Reserve. Historically, United States - Retailers: Inventories to Sales reached a record high of 1.75000 in April of 1995 and a record low of 1.09000 in June of 2021. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Retailers: Inventories to Sales - last updated from the United States Federal Reserve on June of 2025.

The global retail inventory management software market is experiencing robust growth, driven by the increasing need for efficient inventory control and optimization within the retail sector. The market's expansion is fueled by several key factors, including the rising adoption of cloud-based solutions offering scalability and accessibility, the surge in e-commerce activities demanding real-time inventory visibility, and the growing pressure on retailers to minimize operational costs and improve supply chain efficiency. Furthermore, the integration of advanced technologies such as artificial intelligence (AI) and machine learning (ML) is enhancing the capabilities of these software solutions, enabling predictive analytics for demand forecasting and optimized stock management. This is leading to improved inventory accuracy, reduced stockouts and overstocking, and ultimately, higher profitability for retailers. The market is segmented by application (SMEs and large businesses) and deployment type (cloud-based and on-premise), with the cloud-based segment experiencing faster growth due to its flexibility and cost-effectiveness. Major players like Epicor, Oracle, SAP, Microsoft, and NetSuite are competing intensely, driving innovation and shaping the market landscape. While some regions like North America currently hold a significant market share, rapid technological adoption in emerging economies of Asia-Pacific and other regions presents significant growth opportunities. The market is projected to continue its expansion throughout the forecast period (2025-2033), with a consistent compound annual growth rate (CAGR). The competitive landscape is dynamic, with both established players and emerging startups continuously developing and deploying advanced functionalities to cater to the evolving needs of retailers. The competitive landscape is marked by both established players and emerging niche providers. Large vendors leverage their extensive product portfolios and global reach, while smaller companies focus on specific market segments or innovative technological offerings. This dynamic environment drives innovation and ensures that the market caters to the diverse needs of retailers, ranging from small businesses to large multinational corporations. The continued adoption of omnichannel strategies by retailers fuels demand for comprehensive inventory management solutions capable of integrating data across multiple channels, including physical stores, e-commerce platforms, and warehouses. The growing emphasis on data security and compliance regulations also shapes the development and adoption of these solutions. The market’s evolution is characterized by ongoing technological advancements, integration with other retail management systems (like POS and CRM), and a continuous drive towards greater automation and real-time visibility. This creates opportunities for companies to differentiate themselves through enhanced features, superior user experience, and strong customer support.

Wholesale & Retail Inventory: Fujian data was reported at 243.114 RMB bn in 2023. This records a decrease from the previous number of 249.094 RMB bn for 2022. Wholesale & Retail Inventory: Fujian data is updated yearly, averaging 84.854 RMB bn from Dec 1998 (Median) to 2023, with 25 observations. The data reached an all-time high of 249.094 RMB bn in 2022 and a record low of 7.629 RMB bn in 1998. Wholesale & Retail Inventory: Fujian data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.RJA: Wholesale and Retail Inventory: Above Designated Size Enterprise.

Wholesale & Retail Inventory: Hunan data was reported at 89.192 RMB bn in 2023. This records an increase from the previous number of 83.225 RMB bn for 2022. Wholesale & Retail Inventory: Hunan data is updated yearly, averaging 37.899 RMB bn from Dec 1998 (Median) to 2023, with 25 observations. The data reached an all-time high of 175.070 RMB bn in 2015 and a record low of 8.139 RMB bn in 1999. Wholesale & Retail Inventory: Hunan data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.RJA: Wholesale and Retail Inventory: Above Designated Size Enterprise.

United States - Retailers Inventories was 0.80000 % Chg. in February of 2025, according to the United States Federal Reserve. Historically, United States - Retailers Inventories reached a record high of 6.50000 in October of 1995 and a record low of -9.20000 in December of 1995. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Retailers Inventories - last updated from the United States Federal Reserve on June of 2025.

Retail Inventory System Market Outlook

The global retail inventory system market size was valued at approximately USD 2.47 billion in 2023 and is projected to reach USD 4.83 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.5% during the forecast period. The growth of this market is largely driven by the increasing need for efficient inventory management solutions in the retail sector, as businesses strive to optimize their operations and reduce costs. The rise in e-commerce activities and the integration of advanced technologies like IoT and AI into inventory systems are key factors contributing to market growth.

One of the major growth factors for the retail inventory system market is the rapid digitization of the retail sector. With the proliferation of digital technologies, retailers are increasingly adopting sophisticated inventory management systems to streamline their operations. These systems not only help in managing stock levels but also provide real-time data analytics that aid in making informed business decisions. The growing trend of omnichannel retailing, which demands seamless integration of online and offline inventory, is further accelerating the adoption of advanced inventory systems.

Another significant driver is the increasing complexity of supply chains. As retailers expand their operations globally, managing inventory across multiple locations becomes a daunting task. Advanced inventory systems equipped with real-time tracking and predictive analytics capabilities are essential for effectively managing these complex supply chains. These systems help in reducing stockouts and overstock situations, thereby improving overall operational efficiency. Moreover, the rising consumer expectations for faster delivery and better product availability are pushing retailers to invest in robust inventory systems.

The integration of advanced technologies like artificial intelligence (AI) and the Internet of Things (IoT) is also playing a crucial role in the growth of the retail inventory system market. AI-powered systems can predict demand patterns, optimize stock levels, and reduce wastage, while IoT-enabled devices provide real-time data on inventory status. These technological advancements are not only enhancing the capabilities of inventory management systems but also providing retailers with a competitive edge by enabling more efficient and responsive operations.

The adoption of an Inventory Optimization Tool is becoming increasingly crucial for retailers aiming to maintain a competitive edge in the dynamic market landscape. These tools leverage advanced algorithms and data analytics to ensure that stock levels are aligned with consumer demand, minimizing the risks of overstocking and stockouts. By providing real-time insights into inventory status and demand patterns, these tools empower retailers to make informed decisions, optimize their supply chain processes, and enhance overall operational efficiency. As the retail sector continues to evolve with the integration of digital technologies, the role of inventory optimization tools in driving business success cannot be overstated.

From a regional perspective, North America currently holds the largest market share, driven by the presence of major retail giants and advanced technological infrastructure. The Asia Pacific region, however, is expected to witness the highest growth rate during the forecast period, fueled by the rapid expansion of the retail sector and increasing adoption of digital solutions. Europe also presents significant growth opportunities, particularly in countries like Germany, the UK, and France, where the retail industry is undergoing substantial transformation. The Middle East & Africa and Latin America are also emerging markets, with growing investments in retail infrastructure and technology.

Component Analysis

When analyzing the retail inventory system market by component, it is essential to consider the three primary segments: software, hardware, and services. Each of these components plays a vital role in the overall functionality and efficiency of inventory management systems. The software segment includes various types of inventory management software solutions, such as inventory tracking, order management, and demand forecasting software. These solutions are crucial for automating and optimizing inventory-related processes. The hardware segment encompasses devices like barcode scanners, RFID tags, and handheld terminals, wh

This dataset contains a list of sales and movement data by item and department appended monthly. Update Frequency : Monthly

Wholesale & Retail Inventory: Guangxi data was reported at 79.227 RMB bn in 2023. This records an increase from the previous number of 65.386 RMB bn for 2022. Wholesale & Retail Inventory: Guangxi data is updated yearly, averaging 30.233 RMB bn from Dec 1998 (Median) to 2023, with 25 observations. The data reached an all-time high of 79.227 RMB bn in 2023 and a record low of 3.540 RMB bn in 2003. Wholesale & Retail Inventory: Guangxi data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.RJA: Wholesale and Retail Inventory: Above Designated Size Enterprise.

Retail data 2016/2017 Excerpt for the city of Bremen from the survey of the retail inventory survey in the Bremen region 2016/2017. The data were collected at the level of each individual company (about 3,300), but summarised here by main product groups (industry).

The Retail Inventory Management Software market has become a critical component for businesses aiming to streamline operations in an increasingly competitive landscape. This software solution empowers retailers to efficiently track inventory levels, manage stock across multiple locations, and analyze sales trends, u

this graph was created in R and Canva :

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The dataset offers a comprehensive view of grocery inventory, covering 990 products across multiple categories such as Grains & Pulses, Beverages, Fruits & Vegetables, and more. It includes crucial details about each product, such as its unique identifier (Product_ID), name, category, and supplier information, including Supplier_ID and Supplier_Name. This dataset is particularly valuable for businesses aiming to optimize inventory management, sales tracking, and supply chain efficiency.

Key inventory-related fields include Stock_Quantity, which indicates the current stock level, and Reorder_Level, which determines when a product should be reordered. The Reorder_Quantity specifies how much stock to order when inventory falls below the reorder threshold. Additionally, Unit_Price provides insight into pricing, helping businesses analyze cost trends and profitability.

To manage product flow, the dataset includes dates such as Date_Received, which tracks when the product was added to the warehouse, and Last_Order_Date, marking the most recent procurement. For perishable goods, the Expiration_Date column is critical, allowing businesses to minimize waste by monitoring shelf life. The Warehouse_Location specifies where each product is stored, facilitating efficient inventory handling.

Sales and performance metrics are also included. The Sales_Volume column records the total number of units sold, providing insights into consumer demand. Inventory_Turnover_Rate helps businesses assess how quickly a product sells and is replenished, ensuring better stock management. The dataset also tracks the Status of each product, indicating whether it is Active, Discontinued, or Backordered.

The dataset serves multiple purposes in inventory management, sales performance evaluation, supplier analysis, and product lifecycle tracking. Businesses can leverage this data to refine reorder strategies, ensuring optimal stock levels and avoiding stockouts or excessive inventory. Sales analysis can help identify high-demand products and slow-moving items, enabling better decision-making in pricing and promotions. Evaluating suppliers based on their performance, pricing, and delivery efficiency helps streamline procurement and improve overall supply chain operations.

Furthermore, the dataset can support predictive analytics by employing machine learning techniques to estimate reorder quantities, forecast demand, and optimize stock replenishment. Inventory turnover insights can aid in maintaining a balanced supply, preventing unnecessary overstocking or shortages. By tracking trends in sales, businesses can refine their marketing and distribution strategies, ensuring sustained profitability.

This dataset is designed for educational and demonstration purposes, offering fictional data under the Creative Commons Attribution 4.0 International License. Users are free to analyze, modify, and apply the data while providing proper attribution. Additionally, certain products are marked as discontinued or backordered, reflecting real-world inventory dynamics. Businesses dealing with perishable goods should closely monitor expiration and last order dates to avoid losses due to spoilage.

Overall, this dataset provides a versatile resource for those interested in inventory management, sales analysis, and supply chain optimization. By leveraging the structured data, businesses can make data-driven decisions to enhance operational efficiency and maximize profitability.

The on-shelf availability (OSA) market is experiencing robust growth, driven by the increasing need for retailers to optimize inventory management and enhance customer experience. The market's expansion is fueled by the rising adoption of advanced technologies like RFID, IoT sensors, and sophisticated analytics platforms. These technologies provide real-time visibility into inventory levels, enabling retailers to identify and address stockouts promptly. Furthermore, the growing emphasis on data-driven decision-making within retail operations contributes significantly to the market's upward trajectory. Companies are investing heavily in solutions that provide actionable insights into product placement, demand forecasting, and supply chain efficiency, ultimately improving OSA and reducing losses due to out-of-stocks. The competitive landscape is dynamic, with established players like IBM and SAP alongside specialized solution providers. The market's segmentation likely includes solutions tailored to specific retail verticals (grocery, apparel, electronics, etc.), deployment models (cloud-based vs. on-premise), and functionalities (basic inventory tracking vs. advanced analytics). The geographical distribution of the market will vary, with regions having higher retail density and technological advancement (North America and Europe) experiencing faster growth. While precise figures are unavailable, assuming a conservative CAGR of 15% (a reasonable estimate for a technology-driven market segment with significant growth potential), and a 2025 market size of $5 billion (a logical estimation based on the scale of the retail industry and the importance of OSA), the market is projected to reach approximately $10 billion by 2033. This projection takes into account potential market restraints, such as the initial investment costs associated with implementing new technologies and the need for robust data infrastructure to support advanced analytics. However, the long-term benefits of improved OSA, including increased sales, reduced waste, and enhanced customer satisfaction, are expected to outweigh these challenges. The ongoing digital transformation within the retail sector ensures continued strong demand for innovative OSA solutions in the coming years.

United States - Retailers Inventories was 804272.00000 Mil. of $ in April of 2025, according to the United States Federal Reserve. Historically, United States - Retailers Inventories reached a record high of 809705.00000 in November of 2024 and a record low of 234641.00000 in January of 1992. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Retailers Inventories - last updated from the United States Federal Reserve on July of 2025.