Retail Sales in the United States increased 0.40 percent in October of 2024 over the previous month. This dataset provides - U.S. December Retail Sales Increased More Than Forecast - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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This dataset was created by Rishav dash

Released under Database: Open Database, Contents: © Original Authors

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Retail Analytics Market Outlook 2031

The global retail analytics market size was valued USD 6.32 Billion in 2022 and is anticipated to reach USD 35.66 Billion by 2031 expand at a substantial CAGR 21.2% during the forecast period, 2023 – 2031. Growth of the market is attributed to digitalization, increasing online shopping, rising use of big data, social media, and proliferation of smartphones.



The practice of delivering comprehensive data on inventory trends, supply chain flow, customer appetite, sales, and other factors that are critical for marketing and procurement decisions is known as retail analytics. The demand and supply data mining can be used to manage procurement levels to make marketing decisions.

Retail analytics provides comprehensive consumer feedback and insights into the organization's business procedures. Retail analytics is expected to help traditional brick-and-mortar stores to optimize and forecast, manage and control the inventory, and cluster preparation.

Retail Analytics Market Trends, Drivers, Restraints, and Opportunities:

• Surging internet commerce, increasing digital data, rising use of social media, and growing proliferation of smartphones have made shopping easier for consumers. These factors are driving the market.


• Rise in digitalization has allowed customers to make quick purchases from a range of products, while improving efficiency in the retail industry. As a result, big data's bulk volume, velocity, and range are projected to drive the market.


• The demand for retail analytics is projected to rise, due to technical advancements in this market. The offered tools can be used to monitor consumer buying behavior and satisfy shopping experience of customers, thus driving the retail analytics market.

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This dataset is used for the working paper 'Service Level Anchoring in Demand Forecasting: The Moderating Impact of Retail Promotions and Product Perishability,' authored by Fahimnia, Tan, and Tahirov. The data was collected during a laboratory experiment designed based on data from a real case in the fast-moving consumer goods (FMCG) industry. Each subject was assigned to one of the following treatment groups:

T1 (control group) - forecasts were made for a nonperishable product (shelf life of 9 months), with no service level information.

T2 - forecasts were made for a nonperishable product, with a high service level information.

T3 - the forecasts were still for a nonperishable product, with a lower service level information.

T4 - forecasts were made for a perishable product, with high service level information.

T5 - forecasts were made for a perishable product, with low service level information.

A total of 313 subjects prepared four forecasts each. For each forecast, a subject was provided with 30 weeks of sales data, including both normal and promotional weeks. The promotional weeks were highlighted as 'Promo.' The subjects were asked to provide their forecasts for week 31, basing their forecasts solely on historical data and potential sales promotions. Mean absolute percentage error (MAPE) was used to assess the accuracy of the forecasts. Percentage forecast bias was used to measure the deviation of adjusted forecasts from the normative benchmark forecast.

The new version of dataset includes three Excel files:

Excel file 1 (“DataSet.xlsx”) – This file contains the average adjusted forecast for each subject during both the promotional and non-promotional periods, along with other data such as demographic information, calculated MAPE, forecast bias, service level, and product perishability.

Excel file 2 and 3 (“Pool_1_Perishable” and “Pool_2_Non perishable”) - These files contain all the real datasets for perishable and non-perishable products used during the experiment.

A worldwide survey conducted among retailers revealed that only eight percent of retail companies implemented real-time automated processes when planning and forecasting their supply demand. The replenishiment activities involved machine learning technologies in 12 percent of cases. Most retailers taking part to the survey carried out their demand and replenishment activities using digital automation to a much lower extent. Indeed, 38 percent of them run period analysis for demand planning in the supply chain.

Retail Sales in the United States increased 2.80 percent in October of 2024 over the same month in the previous year. This dataset provides - United States Retail Sales YoY - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The global big data analytics in retail market size was valued at USD 6.25 billion in 2021. It is projected to reach USD 40.88 billion by 2030, growing at a CAGR of 23.2% during the forecast period (2022–2030). Factors like the rising need to d Report Scope:

Explore Smart Retail Market Regional Demand with our comprehensive analysis. Get insights on North America, Asia Pacific, Europe, and other key regions. Access country-level market data and understand market dynamics and growth potential across different regions.

Explore Retail Analytics Market Regional Demand with our comprehensive analysis. Get insights on North America, Asia Pacific, Europe, and other key regions. Access country-level market data and understand market dynamics and growth potential across different regions.

Global retail sales were projected to amount to around 32.8 trillion U.S. dollars by 2026, up from approximately 26.4 trillion U.S. dollars in 2021. The retail industry encompasses the journey of a good or service. This typically starts with the manufacturing of a product and ends with said product being purchased by a consumer from a retailer. Retail establishments come in many forms such as grocery stores, restaurants, and bookstores.

American retailers worldwide
As a result of globalization and various trade agreements between markets and countries, many retailers are capable of doing business on a global scale. Many of the world’s leading retailers are American companies. Walmart and Amazon are examples of such American retailers. The success of U.S. retailers can also be seen through their performance in online retail.

Retail in the U.S.
The domestic retail market in the United States is a lucrative market, in which many companies compete. Walmart, a retail chain offering low prices and a wide selection of products, is the leading retailer in the United States. Amazon, The Kroger Co., Costco, and Target are a selection of other leading U.S. retailers.

Demand Planning Software Market size was valued at USD 8.2 Billion in 2023 and is projected to reach USD 15.58 Billion by 2030, growing at a CAGR of 11.5% during the forecast period 2024-2030.

Global Demand Planning Software Market Drivers

The market drivers for the Demand Planning Software Market can be influenced by various factors. These may include:

Globalisation and the Complexity of Supply Chains: Global corporate expansion leads to increasingly complicated supply chains. Demand planning software gives businesses visibility into demand variations across several locations, which aids in the management and optimisation of their supply chains.

Growing Significance of Predictive Precision: Accurate demand forecasting is becoming more and more important as competition and customer expectations rise. Demand planning software improves accuracy through the use of forecasting algorithms and advanced analytics, allowing companies to minimise expenses and optimise inventory levels.

Technological Progress: Demand planning software’s functionality has been enhanced by ongoing technological developments, such as machine learning (ML) and artificial intelligence (AI). Better decision-making, real-time analysis, and more accurate forecasts are made possible by these technologies.

Growth of E-Commerce: The swift expansion of e-commerce has altered consumer buying patterns and elevated the intricacy of supply chain management. Demand planning software offers real-time analytics and predictions, assisting firms in adapting to the dynamic nature of online retail.

Intelligence in business and data analytics: Utilising data analytics and business intelligence tools, demand planning software examines past data, spots trends, and derives useful insights. Companies are realising how important it is to make decisions based on data in order to remain competitive.

Risk management and compliance with regulations: Supply networks now need to manage risk more than ever thanks to stricter regulations. Software for demand planning assists businesses in risk management, regulatory compliance, and ensuring a more responsive and robust supply chain.

Customer-First Strategy: Businesses are implementing customer-centric initiatives in order to provide a better customer experience. Organisations can increase customer satisfaction by matching production and distribution to consumer requests through the use of demand planning software.

Cost-Reduction Strategy: Software for demand planning helps minimise surplus inventory, minimise stockouts, and optimise inventory levels. This increases the overall efficiency of the supply chain, which reduces costs.

Connectivity to Enterprise Resource Planning Systems: ERP (enterprise resource planning) system integration is growing in popularity. This integration makes departmental communication easier, improves data accuracy, and streamlines corporate operations.

Impact of COVID-19 Pandemic : The COVID-19 pandemic’s interruptions brought attention to the necessity of flexible and durable supply systems. Software for demand planning enables companies to better handle demand swings and adjust to unforeseen obstacles.

This dataset is used for the working paper "Service Level Anchoring in Demand Forecasting: The Moderating Impact of Retail Promotions and Product Perishability," authored by Fahimnia, Tan, and Tahirov. The data was collected during a laboratory experiment designed based on data from a real case in the fast-moving consumer goods (FMCG) industry. Each subject was assigned to one of the following treatment groups:

• T1 - forecasts were made for a nonperishable product (shelf life of 9 months), with no service level information.
• T2 - forecasts were made for a perishable product (shelf life 1 day), with no service level information.
• T3 - forecasts were made for a nonperishable product, with a high service level information.
• T4 - the forecasts were still for a nonperishable product, with a lower service level information.
• T5 - forecasts were made for a perishable product, with high service level information.
• T6 - forecasts were made for a perishable product, with low service level information.

A total of 368 subjects prepared four forecasts each. For each forecast, a subject was provided with 30 weeks of sales data, including both normal and promotional weeks. The promotional weeks were highlighted as "Promo." The subjects were asked to provide their forecasts for week 31, basing their forecasts solely on historical data and potential sales promotions. Mean absolute percentage error (MAPE) was used to assess the accuracy of the forecasts. Percentage forecast bias was used to measure the deviation of adjusted forecasts from the normative benchmark forecast.

In 2023, global retail e-commerce sales reached an estimated 5.8 trillion U.S. dollars. Projections indicate a 39 percent growth in this figure over the coming years, with expectations to surpass eight trillion dollars by 2027.

World players Among the key players on the world stage, the Chinese retail giant Alibaba holds the title of the largest e-commerce retailer globally, accounting for a 23 percent market share. Nevertheless, forecasts suggest that by 2027, Seattle-based e-commerce powerhouse Amazon will surpass Alibaba in estimated sales, reaching a staggering 1.2 trillion U.S. dollars in online sales.

Leading e-tailing countries The Chinese e-commerce market was the biggest worldwide in 2023, as internet sales constituted almost half of the country's retail transactions. Indonesia ranked second with the highest share of retail sales online (32 percent), closely trailed by the United Kingdom and South Korea, exceeding the 30 percent mark. That year, the up-and-coming e-commerce markets centered around Asia. The Philippines and India stood out as the swiftest-growing e-commerce markets based on online sales, anticipating a growth rate surpassing 20 percent.

The Retail Industry Report is Segmented by Products (Food, Beverages, and Grocery, Personal and Household Care, Apparel, Footwear and Accessories, Furniture, Toys and Hobby, Electronic and Household Appliances, and Other Products), by Distribution Channel (Supermarkets/Hypermarkets, Convenience Stores, and Department Stores, Specialty Stores, Online, and Other Distribution Channels), and by Geography by (North America, Europe, Asia-Pacific, Latin America, and Middle East and Africa). The Report Offers Market Size and Forecasts for the Retail Market in Value (USD) for all the Above Segments.

Retail Analytics Software Market size was valued at USD 7.5 Billion in 2024 and is projected to reach USD 31.2 Billion by 2031, growing at a CAGR of 17.25% during the forecast period 2024-2031.

Global Retail Analytics Software Market Drivers

The market drivers for the Retail Analytics Software Market can be influenced by various factors. These may include:

Growing E-Commerce Sector: The booming e-commerce industry is a significant driver for retail analytics software, as online retailers need robust tools to analyze vast amounts of data and derive actionable insights for improving customer satisfaction and operational efficiency. With the global e-commerce market expected to continue its rapid growth trajectory, the demand for analytics solutions will only intensify.
Omnichannel Retailing: Retailers are increasingly adopting omnichannel strategies to provide a seamless shopping experience across various platforms, including online, offline, and mobile. Retail analytics software helps in synchronizing data from diverse channels, offering retailers actionable insights to enhance customer experiences and streamline operations, thus driving the market demand.
Personalization and Customer-Centric Strategies: With the growing importance of personalized customer experiences, retailers are leveraging analytics software to gain in-depth understanding of customer behavior and preferences. Real-time analytics enables retailers to tailor offers, recommendations, and marketing campaigns, thereby improving customer loyalty and driving sales growth.
Advancements in AI and Machine Learning: The integration of artificial intelligence and machine learning into retail analytics software offers advanced predictive analytics and automated insights. These technologies help retailers predict market trends, optimize inventory management, and enhance decision-making processes, making the software invaluable and boosting market growth.
Increasing Use of IoT in Retail: The proliferation of IoT devices in retail, such as smart shelves, beacons, and connected POS systems, generates a vast amount of data. Retail analytics software is essential to process and analyze this data, providing valuable insights for inventory management, customer shopping patterns, and operational efficiencies, thereby driving the market upwards.
Enhanced Fraud Detection: Retailers are adopting analytics software to combat fraud and reduce losses. Advanced analytics can detect unusual patterns and flag potential fraudulent activities in real time, enabling retailers to take immediate action. The growing need for robust fraud detection mechanisms is a strong driver for the retail analytics software market.
Dynamic Pricing Strategies: Retailers are increasingly using analytics software to implement dynamic pricing strategies, adjusting prices based on factors such as demand, competitor pricing, and market conditions. This capability helps retailers maximize profits and market competitiveness, driving the adoption of retail analytics solutions.
Data-Driven Inventory Management: Efficient inventory management is crucial for retail profitability. Retail analytics software provides critical insights into stock levels, turnover rates, and demand forecasting, helping retailers minimize stockouts and overstock situations. The push for more efficient inventory management systems fuels the demand for advanced analytics solutions in the retail sector.
Increased Adoption of Cloud-Based Solutions: The trend towards cloud computing has made retail analytics software more accessible and scalable for businesses of all sizes. Cloud-based solutions offer flexibility, cost savings, and ease of integration with other systems, driving higher adoption rates among retailers and propelling market growth.
Competitive Market Landscape: In a highly competitive retail environment, businesses strive for a competitive edge. Retail analytics software offers a strategic advantage by providing deep insights and detailed performance metrics, helping retailers to stay ahead of the competition. This competitive pressure compels more retailers to adopt analytics solutions, spurring market expansion.

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Display for Retail Applications Market Size 2024-2028

The Display for Retail Applications Market size is forecast to increase by USD 1.09 billion, at a CAGR of 4.36% between 2023 and 2028. The Display for Retail Applications market is experiencing significant growth due to several key factors. Firstly, digital signage offers advantages over traditional advertising methods, including the ability to deliver targeted messages, real-time content updates, and cost savings. Secondly, the increasing demand for a convenient and user-friendly shopping environment is driving retailers to adopt digital signage solutions. Lastly, the evolution of shopping as a form of entertainment is also contributing to the market's growth. Digital signage provides an engaging and interactive experience for customers, enhancing their overall shopping journey. With these trends continuing to shape the retail industry, the Display for Retail Applications market is poised for continued expansion.

What will be the Size of the Display Market For Retail Applications During the Forecast Period?

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Market Dynamics

In the retail industry, non-touch-screen retail displays and non-touch displays offer a practical solution for product merchandising in apparels stores, footwear specialty stores, and jewelry stores. For bags and luggage specialty stores and watch specialty stores, creative and innovative displays enhance window displays and in-store displays. Visual merchandising strategies incorporate touch-enabled displays and augmented reality to attract customers and improve engagement. Retailers are increasingly focusing on sustainable displays and environmentally friendly materials to align with green practices. POS systems and ATMs streamline transactions, while e-commerce platforms complement physical store efforts. Independent small grocers benefit from thoughtful store design and effective merchandise placement to enhance customer experience and sales. By integrating these diverse elements, retailers create dynamic shopping environments that cater to modern consumer preferences and technological advancements.

Driver

Rising demand for convenient and user-friendly shopping environments is notably driving the market growth. The retail industry has been evolving to meet customers' needs for convenience and a user-friendly shopping environment. Supermarkets and hypermarkets are globally popular channels because of their convenience. The retail sector has increasingly adopted digital displays, leading to a higher demand for user-friendly interfaces like self-help kiosks, interactive store maps, and automatic ticket counters. Consumers visiting retail outlets prefer touchscreens on kiosks, which retailers have adopted to assist customers and enhance their shopping experience.

In addition, interfaces are designed according to consumer requirements to improve functionality. Therefore, due to the increasing demand for convenience and user-friendly shopping environments, the global display market for retail applications will continue to grow during the forecast period.

Trends

The growing adoption of 3D displays for advertising is an emerging trend shaping the market growth. Retailers are increasingly using 3D content in their stores because of its growing popularity and visual impact. They are using innovative technologies to attract customers' attention and increase sales, margins, and earnings. Retail firms believe that point-of-purchase advertising is essential to their businesses, as more than 70% of purchase decisions are made in-store. This type of advertising is highly effective as the target audience within a store tends to be more attentive and receptive to the messages presented.

Moreover, the inclusion of 3D technology in point-of-purchase advertising helps to grab the customer's attention and increase engagement. The market for 3D displays, such as the patented Holo 3D floating image display by Provision Interactive Technologies, is set to grow in the future. As a result, the increasing adoption of 3D displays for advertising will drive the growth of the global display market for retail applications during the forecast period

Restrain

High power consumption in retail displays is a significant challenge hindering market growth. In a retail environment, digital displays are typically operational throughout the workday without interruption. These displays are usually large to ensure maximum visibility. However, due to their size and weight, the battery capacity of retail display devices is limited. Additionally, most display devices at retail outlets consume a significant amount of power due to their big screens and high resolutions. Moreover, many outlets keep their retail displays switched on even after the stores are closed, which further increases power consumption. High-resolution displays require more power and as a result,

According to Cognitive Market Research, the global Artificial Intelligence in Retail market size is USD 4951.2 million in 2023and will expand at a compound annual growth rate (CAGR) of 39.50% from 2023 to 2030.

Enhanced customer personalization to provide viable market output
Demand for online remains higher in Artificial Intelligence in the Retail market.
The machine learning and deep learning category held the highest Artificial Intelligence in Retail market revenue share in 2023.
North American Artificial Intelligence In Retail will continue to lead, whereas the Asia-Pacific Artificial Intelligence In Retail market will experience the most substantial growth until 2030.

Enhanced Customer Personalization to Provide Viable Market Output

A primary driver of Artificial Intelligence in the Retail market is the pursuit of enhanced customer personalization. A.I. algorithms analyze vast datasets of customer behaviors, preferences, and purchase history to deliver highly personalized shopping experiences. Retailers leverage this insight to offer tailored product recommendations, targeted marketing campaigns, and personalized promotions. The drive for superior customer personalization not only enhances customer satisfaction but also increases engagement and boosts sales. This focus on individualized interactions through A.I. applications is a key driver shaping the dynamic landscape of A.I. in the retail market.

January 2023 - Microsoft and digital start-up AiFi worked together to offer Smart Store Analytics. It is a cloud-based tracking solution that helps merchants with operational and shopper insights for intelligent, cashierless stores.

Source-techcrunch.com/2023/01/10/aifi-microsoft-smart-store-analytics/

Improved Operational Efficiency to Propel Market Growth

Another pivotal driver is the quest for improved operational efficiency within the retail sector. A.I. technologies streamline various aspects of retail operations, from inventory management and demand forecasting to supply chain optimization and cashier-less checkout systems. By automating routine tasks and leveraging predictive analytics, retailers can enhance efficiency, reduce costs, and minimize errors. The pursuit of improved operational efficiency is a key motivator for retailers to invest in AI solutions, enabling them to stay competitive, adapt to dynamic market conditions, and meet the evolving demands of modern consumers in the highly competitive artificial intelligence (AI) retail market.

January 2023 - The EY Retail Intelligence solution, which is based on Microsoft Cloud, was introduced by the Fintech business EY to give customers a safe and efficient shopping experience. In order to deliver insightful information, this solution makes use of Microsoft Cloud for Retail and its technologies, which include image recognition, analytics, and artificial intelligence (A.I.).

Source-www.ey.com/en_gl/news/2023/01/ey-announces-launch-of-retail-solution-that-builds-on-the-microsoft-cloud-to-help-achieve-seamless-consumer-shopping-experiences

Market Dynamics of the Artificial Intelligence in the Retail market

Data Security Concerns to Restrict Market Growth

A prominent restraint in Artificial Intelligence in the Retail market is the pervasive concern over data security. As retailers increasingly rely on A.I. to process vast amounts of customer data for personalized experiences, there is a growing apprehension regarding the protection of sensitive information. The potential for data breaches and cyberattacks poses a significant challenge, as retailers must navigate the delicate balance between utilizing customer data for AI-driven initiatives and safeguarding it against potential security threats. Addressing these concerns is crucial to building and maintaining consumer trust in A.I. applications within the retail sector.

Impact of COVID–19 on the Artificial Intelligence in the Retail market

The COVID-19 pandemic significantly influenced artificial intelligence in the retail market, accelerating the adoption of A.I. technologies across the industry. With lockdowns, social distancing measures, and a surge in online shopping, retailers turned to A.I. to navigate the challenges posed by the pandemic. AI-powered solutions played a crucial role in optimizing supply chain management, predicting shifts in consumer behavior, and enhancing e-commerce experiences. Retailers lever...

Dataset

This dataset was created by Aravinda Raman J

Released under MIT

Contents

Explore Artificial Intelligence in Retail Market Regional Demand with our comprehensive analysis. Get insights on North America, Asia Pacific, Europe, and other key regions. Access country-level market data and understand market dynamics and growth potential across different regions.