United States Retail Analytics Market Report by Function (Customer Management, In-Store Operation, Strategy and Planning, Supply Chain Management, Marketing and Merchandizing, and Others), Component (Software, Services), Deployment Mode (On-premises, Cloud-based), End User (Small and Medium Enterprises, Large Enterprises), and Region 2024-2032

United States Retail Analytics Market Report by Function (Customer Management, In-Store Operation, Strategy and Planning, Supply Chain Management, Marketing and Merchandizing, and Others), Component (Software, Services), Deployment Mode (On-premises, Cloud-based), End User (Small and Medium Enterprises, Large Enterprises), and Region 2024-2032

Report Format: PDF+Excel | Report ID: SR112024A12220
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Market Overview:

The United States retail analytics market size is projected to exhibit a growth rate (CAGR) of 18.7% during 2024-2032. The market is experiencing robust growth, driven by the rise of e-commerce, an emphasis on enhancing customer experience, and the integration of advanced technologies like AI and IoT, with key players continuously innovating to offer comprehensive, real-time analytical solutions.

Report Attribute
Key Statistics
Base Year
Forecast Years
Historical Years
Market Growth Rate (2024-2032) 18.7%

Retail analytics is the practice of using data-driven insights to guide business decisions within the retail industry. By collecting and analyzing data from various sources such as sales transactions, customer behavior, and supply chain movements, retail analytics enables retailers to improve operational efficiency, enhance customer experience, and increase profitability. Currently, sophisticated analytical tools and software are facilitating real-time data processing, which is empowering businesses to make timely and informed decisions. Technologies such as machine learning, artificial intelligence, and predictive modeling are also being incorporated, allowing for advanced trend identification and future forecasting. Retail analytics is offering a competitive edge to end users by transforming raw data into actionable intelligence, thereby helping retailers strategically allocate resources, optimize pricing, and personalize customer engagement.

The United States retail analytics industry is being driven by the integration of Internet of Things (IoT) devices into the retail landscape. These devices generate real-time data that can offer invaluable insights into inventory levels, customer footfall, and in-store behaviors. Another crucial driver is the need for supply chain optimization. In a market increasingly influenced by global factors, effective supply chain management is essential for maintaining competitive pricing and product availability. Retail analytics aids in forecasting demand, planning inventory, and managing supplier relationships, thereby optimizing the entire supply chain. Emerging technologies like artificial intelligence and machine learning are also acting as catalysts. These technologies enable more nuanced analyses, from predictive modeling to natural language processing, making analytics more accurate and insightful. Regulatory factors, such as data protection laws, are also impacting the market by setting the standards for data collection and analysis, ensuring ethical practices. Furthermore, the proliferation of smartphones and mobile applications is enabling retailers to gather more granular data, thereby enriching the quality of analytics.

United States Retail Analytics Market Trends/Drivers:

E-commerce Growth

One of the foremost drivers for the United States retail analytics market is the exponential growth in e-commerce. As online shopping continues to gain traction, retailers are accumulating massive amounts of data through digital platforms. This data includes customer behavior, purchasing patterns, and online traffic sources, among others. Retailers are increasingly relying on analytics to decode this information and make data-driven decisions. The pandemic has accelerated this shift, making e-commerce not just an alternative but often a primary sales channel for many businesses. In this context, analytics tools are critical for optimizing inventory, understanding consumer sentiment, and driving personalized marketing campaigns. The rise of e-commerce necessitates sophisticated analytics solutions, thus propelling the retail analytics market forward.

Customer Experience Enhancement

Another significant market driver is the ongoing emphasis on improving customer experience. Nowadays, consumers are well-informed and have high expectations for personalized services. Retail analytics tools are instrumental in gathering insights on customer preferences and behavior, which can be used to tailor marketing strategies, optimize product placements, and even reconfigure store layouts. Advanced analytics can also help in predicting consumer needs before they explicitly express them, providing a significant competitive advantage. As enhancing customer experience becomes pivotal for brand loyalty and long-term success, the demand for advanced retail analytics solutions is continually increasing, making it a key driver in the market.

United States Retail Analytics Industry Segmentation:

IMARC Group provides an analysis of the key trends in each segment of the United States retail analytics market report, along with forecasts at the country level for 2024-2032. Our report has categorized the market based on function, component, deployment mode, and end user.

Breakup by Function:

  • Customer Management
  • In-Store Operation
  • Strategy and Planning
  • Supply Chain Management
  • Marketing and Merchandizing
  • Others

The report has provided a detailed breakup and analysis of the market based on the function. This includes customer management, in-store operation, strategy and planning, supply chain management, marketing and merchandizing, and others.

Customer management focuses on understanding customer behavior and preferences. Retail analytics in customer management enables personalized marketing strategies and enhances customer engagement, thereby driving sales and improving brand loyalty.

Within in-store operations, retail analytics plays a crucial role in optimizing store layouts, managing in-store traffic, and ensuring the efficiency of sales personnel. Advanced analytics tools help in real-time monitoring of store activities, thereby enabling immediate decision-making for operational improvements.

In the domain of strategy and planning, retail analytics provides insights that assist in long-term decision-making, ranging from store locations to product assortments. By analyzing market trends and consumer demands, retailers can make informed strategic decisions that align with their business objectives.

Retail analytics aids in streamlining operations from suppliers to consumers in supply chain management. It assists in inventory planning, demand forecasting, and supplier relationship management, thereby ensuring that products are available when and where they are needed.

Marketing and merchandising employs retail analytics to optimize pricing strategies, promotional activities, and product placements. Insights derived from analytics enable more effective marketing campaigns and merchandising decisions, thus boosting profitability.

The others category includes miscellaneous functions like employee management and compliance monitoring. Retail analytics in these areas helps in workforce optimization and ensures that retail operations comply with legal regulations, thereby minimizing risks and enhancing operational efficiency.

Breakup by Component:

  • Software
  • Services

A detailed breakup and analysis of the market based on the component has also been provided in the report. This includes software and services.

The software component of the retail analytics market includes various platforms and tools designed for data collection, analysis, and visualization. These software solutions offer functionalities ranging from customer behavior analysis to supply chain optimization, serving as the backbone for data-driven decision-making in retail operations.

Services in the retail analytics industry consist of consulting, implementation, and ongoing maintenance and support. These services are essential for ensuring that the software is tailored to specific retail needs, properly integrated into existing systems, and continuously updated to incorporate new data and analytical techniques.

Breakup by Deployment Mode:

  • On-premises
  • Cloud-based

The report has provided a detailed breakup and analysis of the market based on the deployment mode. This includes on-premises and cloud-based.

In the on-premises deployment mode, retail analytics software is installed and run directly on the hardware within the organization's physical location. This approach offers greater control over data and is often favored by larger retailers with more complex infrastructure and higher security requirements.

Cloud-based deployment allows retailers to access analytics tools via the internet, often on a subscription basis. This mode is more scalable and cost-effective, making it particularly appealing for small to medium-sized businesses or retailers with multiple locations that require centralized data access and analysis.

Breakup by End User:

  • Small and Medium Enterprises
  • Large Enterprises

A detailed breakup and analysis of the market based on the end user has also been provided in the report. This includes small and medium enterprises and large enterprises.

For SMEs, retail analytics solutions often serve as a cost-effective way to gain insights into customer behavior and operational efficiency. Cloud-based deployment options are particularly popular in this segment due to their scalability and lower upfront costs, enabling SMEs to compete effectively in the marketplace without heavy investment in analytics infrastructure.

Large enterprises usually have more complex analytics needs, encompassing multiple departments and often spanning global operations. These organizations typically opt for comprehensive, on-premises solutions that can be customized to fit their specific requirements. Their larger budgets also allow them to invest in advanced features like machine learning and predictive analytics, providing a more in-depth understanding of market trends and customer behavior.

Breakup by Region:

  • Northeast
  • Midwest
  • South
  • West

The report has also provided a comprehensive analysis of all the major regional markets, which include Northeast, Midwest, South, and West.

The Northeast region, which includes major economic hubs like New York and Boston, shows a robust demand for retail analytics due to a high concentration of retail businesses and financial institutions. The presence of technology and analytics firms also stimulates the adoption of advanced analytics solutions, making this region a significant player in the retail analytics market.

In the Midwest, traditional retail chains and emerging e-commerce platforms alike are turning to analytics to understand the diverse consumer base. While perhaps not as densely concentrated as other regions, the Midwest has a growing demand for retail analytics tools to optimize supply chains that often crisscross this central region.

The South has a varied retail landscape with a mix of small local businesses and large enterprises. The region is increasingly adopting retail analytics to gain a competitive edge, especially in fast-growing industries like technology and healthcare, where data-driven decision-making is crucial.

The West, home to tech-savvy states like California and Washington, shows a high rate of retail analytics adoption, particularly in e-commerce and tech-focused retail environments. The presence of numerous tech companies and startups in this region drives innovation in analytics, making the West a key market for cutting-edge retail analytics solutions.

Competitive Landscape:

Key players in the market are continuously innovating to stay competitive and meet the evolving needs of retailers. They are focusing on integrating advanced technologies like artificial intelligence, machine learning, and the Internet of Things to offer more comprehensive and real-time analytical solutions. Many are forming strategic partnerships with other tech firms and consulting services to deliver end-to-end solutions, ranging from data collection to actionable insights. Some are also expanding their offerings to include industry-specific analytics tools tailored for sectors such as fashion, grocery, or electronics. By providing scalable, customizable solutions, these market leaders are aiming to facilitate data-driven decision-making across diverse retail environments.

The market research report has provided a comprehensive analysis of the competitive landscape in the market. Detailed profiles of all major companies have also been provided.

United States Retail Analytics Market Report Scope:

Report Features Details
Base Year of the Analysis 2023
 Historical Period 2018-2023
Forecast Period 2024-2032
Units US$ Billion
Scope of the Report Exploration of Historical and Forecast Trends, Industry Catalysts and Challenges, Segment-Wise Historical and Predictive Market Assessment: 
  • Function
  • Component
  • Deployment Mode
  • End User
  • Region 
Functions Covered Customer Management, In-Store Operation, Strategy and Planning, Supply Chain Management, Marketing and Merchandizing, Others
Components Covered Software, Services
Deployment Modes Covered On-premises, Cloud-based
End Users Covered Small and Medium Enterprises, Large Enterprises
Regions Covered Northeast, Midwest, South, West
Customization Scope 10% Free Customization
Report Price and Purchase Option Single User License: US$ 2899
Five User License: US$ 4899
Corporate License: US$ 7899
Post-Sale Analyst Support 10-12 Weeks
Delivery Format PDF and Excel through Email (We can also provide the editable version of the report in PPT/Word format on special request)

Key Questions Answered in This Report:

  • How has the United States retail analytics market performed so far, and how will it perform in the coming years?
  • What are the drivers, restraints, and opportunities in the United States retail analytics market?
  • What is the impact of each driver, restraint, and opportunity on the United States retail analytics market?
  • What is the breakup of the market based on the function?
  • Which is the most attractive function in the United States retail analytics market?
  • What is the breakup of the market based on the component?
  • Which is the most attractive component in the United States retail analytics market?
  • What is the breakup of the market based on the deployment mode?
  • Which is the most attractive deployment mode in the United States retail analytics market?
  • What is the breakup of the market based on the end user?
  • Which is the most attractive end user in the United States retail analytics market?
  • What is the competitive structure of the United States retail analytics market?
  • Who are the key players/companies in the United States retail analytics market?

Key Benefits for Stakeholders:

  • IMARC’s industry report offers a comprehensive quantitative analysis of various market segments, historical and current market trends, market forecasts, and dynamics of the United States retail analytics market from 2018-2032.
  • The research report provides the latest information on the market drivers, challenges, and opportunities in the United States retail analytics market.
  • Porter's five forces analysis assist stakeholders in assessing the impact of new entrants, competitive rivalry, supplier power, buyer power, and the threat of substitution. It helps stakeholders to analyze the level of competition within the United States retail analytics industry and its attractiveness.
  • Competitive landscape allows stakeholders to understand their competitive environment and provides an insight into the current positions of key players in the market. 

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United States Retail Analytics Market Report by Function (Customer Management, In-Store Operation, Strategy and Planning, Supply Chain Management, Marketing and Merchandizing, and Others), Component (Software, Services), Deployment Mode (On-premises, Cloud-based), End User (Small and Medium Enterprises, Large Enterprises), and Region 2024-2032
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