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North America Retail Analytics Market, Competition, Forecast & Opportunities, 2018-2028

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    Report

  • 130 Pages
  • October 2023
  • Region: North America
  • TechSci Research
  • ID: 4658313
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The North America Retail Analytics Market Was Valued at USD 1.29 Billion in 2022 and is Expected to Grow at a CAGR of 18.23% During the Forecast Period

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The North America retail analytics market was valued at USD 1.29 Billion in 2022 and is expected to grow at a CAGR of 18.23% during the forecast period. The North America retail analytics market has experienced significant growth and transformation in recent years, driven by the rapid evolution of the retail industry and the increasing demand for data-driven insights to enhance business strategies. This dynamic market encompasses a wide range of solutions and services that enable retailers to gain deeper insights into their operations, customer behavior, and market trends. As the retail landscape continues to evolve, retailers are increasingly turning to analytics to gain a competitive edge in a highly competitive market. One of the key drivers of the North America Retail Analytics market's growth is the proliferation of data generated by various retail channels. With the advent of e-commerce, mobile shopping, and social media, retailers are now inundated with vast amounts of data that hold valuable insights. Retail analytics solutions offer the capability to harness this data and turn it into actionable information. Retailers can analyze customer purchase history, website traffic, social media interactions, and even in-store foot traffic to better understand customer preferences and tailor their marketing strategies accordingly. This data-driven approach empowers retailers to offer personalized shopping experiences and optimize their product assortments, pricing strategies, and promotional efforts.

Moreover, the North America retail analytics market is witnessing a surge in demand for predictive analytics. Retailers are increasingly adopting advanced analytics tools to forecast consumer demand and inventory needs accurately. Predictive analytics can help retailers anticipate trends, seasonal fluctuations, and even unforeseen events, enabling them to optimize inventory levels, reduce stockouts, and minimize overstock situations. This not only improves customer satisfaction by ensuring products are available when needed but also reduces operational costs and improves overall supply chain efficiency. In addition to improving inventory management, retail analytics solutions are also empowering retailers to enhance their pricing strategies. Dynamic pricing, fueled by real-time data analysis, allows retailers to adjust prices based on factors such as demand, competitor pricing, and customer behavior. This agility in pricing enables retailers to remain competitive and maximize profits while also meeting customer expectations. The ability to offer personalized promotions and discounts further enhances the customer shopping experience, increasing brand loyalty and repeat business.

The North America retail analytics market is also witnessing significant advancements in the realm of customer analytics. Retailers are leveraging sophisticated analytics tools to gain deeper insights into customer behavior and preferences. By analyzing customer journeys, purchase histories, and demographic information, retailers can create more targeted marketing campaigns and improve customer segmentation. This not only boosts the effectiveness of marketing efforts but also enhances the overall customer experience, fostering long-term customer relationships. Furthermore, the integration of artificial intelligence (AI) and machine learning (ML) technologies is revolutionizing the North America Retail Analytics market. AI and ML algorithms can analyze vast datasets in real-time, identifying patterns and trends that would be impossible for humans to discern. These technologies enable retailers to automate decision-making processes, such as inventory replenishment, fraud detection, and customer service interactions. Chatbots and virtual shopping assistants powered by AI provide customers with personalized recommendations and assistance, enhancing the online shopping experience.

The North America Retail Analytics market is not limited to traditional brick-and-mortar retailers. E-commerce businesses are also capitalizing on analytics solutions to optimize their operations. From managing online advertising campaigns to monitoring website performance and customer behavior, e-commerce retailers rely on analytics to drive growth and profitability. The ability to track shopping cart abandonment rates and identify the reasons behind them allows e-commerce companies to implement strategies to recover potential lost sales. Additionally, the COVID-19 pandemic has accelerated the adoption of retail analytics in North America. The sudden shift in consumer behavior, with a significant increase in online shopping, forced retailers to adapt quickly. Retail analytics played a pivotal role in helping retailers make informed decisions during this challenging period. It allowed them to allocate resources efficiently, adjust supply chains, and tailor marketing strategies to the changing circumstances.

In conclusion, the North America retail analytics market is experiencing robust growth driven by the data-driven transformation of the retail industry. Retailers are increasingly relying on analytics solutions to gain insights into customer behavior, optimize inventory management, enhance pricing strategies, and improve overall operational efficiency. With the integration of AI and ML technologies, the future of retail analytics looks promising, promising even more advanced capabilities to drive innovation and competitiveness in the North American retail sector. As the retail landscape continues to evolve, retail analytics will remain a crucial tool for retailers seeking to thrive in a dynamic and highly competitive market.

Key Market Drivers

Growing E-commerce and Omnichannel Retail

The North America retail analytics market is experiencing robust growth driven by the rapid expansion of e-commerce and the adoption of omnichannel retail strategies. E-commerce has witnessed explosive growth, with consumers increasingly turning to online shopping, especially in the wake of the COVID-19 pandemic. As a result, retailers are investing heavily in digital platforms and technologies to stay competitive. Retail analytics solutions play a critical role in this transformation, providing insights into online consumer behavior, purchase patterns, and preferences. Additionally, retailers are leveraging these analytics tools to bridge the gap between online and offline shopping experiences, creating seamless omnichannel journeys. This evolution in retail dynamics is a key driver of the North America retail analytics market's expansion.

Demand for Customer Personalization and Targeted Marketing

Customer personalization has become a cornerstone of retail success, and this demand is driving the adoption of retail analytics solutions in North America. Consumers expect personalized shopping experiences, and retailers are using data analytics to deliver on these expectations. Retail analytics tools enable retailers to gather and analyze customer data, such as purchase history, browsing behavior, and demographic information, to create targeted marketing campaigns and recommendations. By tailoring offers and product recommendations to individual preferences, retailers can enhance customer loyalty and drive sales. As North American retailers strive to compete in a highly competitive market, the demand for retail analytics to support personalization efforts continues to grow.

Inventory Optimization and Supply Chain Efficiency

Inventory management and supply chain optimization are critical aspects of the retail industry, and they are being revolutionized by analytics solutions in North America. Efficient inventory management is essential to reduce costs, minimize stockouts, and avoid overstock situations. Retail analytics provide insights into demand forecasting, inventory turnover, and order fulfillment, enabling retailers to make data-driven decisions. Moreover, supply chain analytics help in monitoring the entire supply chain, from suppliers to distribution centers to stores, ensuring streamlined operations and timely delivery of products. In the highly competitive North American retail landscape, retailers are recognizing the importance of analytics in inventory and supply chain management, making it a significant market driver.

Enhanced Fraud Detection and Loss Prevention

The North America retail analytics market is also being driven by the need for enhanced fraud detection and loss prevention. Retailers face significant challenges related to theft, fraud, and shrinkage. Retail analytics solutions leverage advanced algorithms and machine learning to identify unusual patterns and anomalies in transaction data, which can indicate fraudulent activities. These tools help retailers detect and prevent theft at both the customer and employee levels. Moreover, by analyzing video surveillance footage and point-of-sale data, retailers can identify suspicious behavior and take proactive measures to reduce losses. As the retail industry in North America grapples with security challenges, retail analytics is increasingly viewed as a vital tool to safeguard assets and profits.

Key Market Challenges

Data Privacy and Security Concerns in the North America Retail Analytics Market

One of the significant challenges facing the North America retail analytics market revolves around data privacy and security concerns. As retailers collect and analyze vast amounts of customer data to drive their analytics initiatives, they must navigate a complex landscape of privacy regulations and safeguard against data breaches. The North American market is subject to stringent data protection laws, including the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), which have implications for both domestic and international retail operations. One major issue retailers face is the ethical and legal use of customer data. While data-driven insights can be incredibly valuable for improving customer experiences and optimizing business operations, there is a fine line between personalized marketing and invasive practices that violate customer privacy. Retailers must strike a delicate balance between data collection and respecting customer rights to privacy. Data breaches are another significant concern. High-profile breaches in various industries have raised awareness about the importance of securing sensitive customer information. Retailers in North America are attractive targets for cyberattacks due to the valuable financial and personal data they store. Any breach can result in severe financial and reputational damage.

Integrating Legacy Systems and Data Silos

Another significant challenge in the North America Retail Analytics market is the integration of legacy systems and the breaking down of data silos. Many retailers in the region have accumulated a mix of legacy IT systems over the years, including point-of-sale (POS) systems, inventory management tools, and customer relationship management (CRM) systems. These systems often operate in isolation, leading to data fragmentation and inefficiencies. To leverage the full potential of retail analytics, retailers must integrate these disparate systems and data sources. Data silos hinder the ability to gain a holistic view of operations and customer behavior, which is essential for making informed decisions and achieving a unified customer experience across channels. However, integrating legacy systems can be a complex and resource-intensive process. It requires careful planning, substantial investments in technology, and often, the need for customized solutions to bridge the gaps between different systems. Additionally, retailers must ensure that data quality and consistency are maintained throughout the integration process to avoid inaccuracies and errors in analytics results. Moreover, legacy systems may not be designed to handle the volume and complexity of data generated in modern retail environments. Retailers may need to upgrade or replace outdated systems to fully harness the capabilities of advanced analytics tools and accommodate the growing demands of e-commerce and omnichannel retail.

Key Market Trends

Predictive Analytics for Inventory Management

One prominent trend in the North America Retail Analytics market is the increasing adoption of predictive analytics for inventory management. Retailers are recognizing the need for more sophisticated inventory control solutions to meet changing consumer demands, especially in the context of e-commerce and omnichannel retail. Predictive analytics leverages historical data, real-time information, and advanced algorithms to forecast future demand accurately. In today's fast-paced retail environment, where product trends and consumer preferences can change rapidly, retailers can't afford to rely solely on historical sales data or manual inventory management processes. Predictive analytics helps retailers anticipate demand fluctuations, seasonal trends, and even unexpected events like the COVID-19 pandemic. This allows them to optimize stock levels, reduce the risk of overstock or stockouts, and ultimately improve profitability. For instance, when a retailer can predict that a particular product is likely to be in high demand during a specific season, they can proactively stock more of that item. Conversely, for slow-moving products, they can adjust pricing or marketing strategies to clear out inventory. This trend is particularly crucial in the North American retail market, where consumer preferences are diverse and can vary significantly by region.

AI-Driven Customer Insights and Personalization

Another notable trend in the North America Retail Analytics market is the integration of artificial intelligence (AI) and machine learning (ML) to derive deeper customer insights and enhance personalization efforts. Retailers are increasingly using AI-powered analytics tools to analyze vast amounts of customer data collected through various touchpoints, such as online stores, mobile apps, and loyalty programs. These analytics solutions can identify patterns and trends in consumer behavior, helping retailers understand what products customers are interested in, when they are likely to make a purchase, and what factors influence their buying decisions. With this knowledge, retailers can create highly personalized shopping experiences, offering tailored product recommendations, customized promotions, and even individualized pricing. North American consumers have come to expect personalized experiences in their interactions with retailers, both online and in physical stores. AI-driven retail analytics empower businesses to meet these expectations, thereby increasing customer satisfaction and loyalty. Furthermore, personalization can lead to higher conversion rates, larger average order values, and ultimately improved revenue streams for retailers operating in North America's competitive market.

Integration of Online and Offline Analytics for Omnichannel Insights

The third significant trend in the North America retail analytics market is the increasing integration of online and offline analytics to gain a comprehensive view of customer behavior and preferences across all channels. As omnichannel retail strategies continue to gain momentum, retailers are recognizing the need to break down the silos between their physical and digital operations. By integrating data from both online and offline sales channels, retailers can understand how consumers move between these touchpoints. For example, a customer might research a product online, visit a physical store to see it in person, and then make the purchase online. With integrated analytics, retailers can track this customer journey and tailor their marketing and sales strategies accordingly. In the North American market, where consumers often switch between online and offline shopping, this trend is particularly relevant. Retailers are investing in technologies that enable them to capture data from various sources, such as e-commerce platforms, mobile apps, in-store point-of-sale systems, and customer loyalty programs. This holistic approach to data analysis not only improves personalization efforts but also helps retailers optimize store layouts, staff allocation, and marketing spend, enhancing the overall shopping experience for customers.

Segmental Insights

Component Insights

Based on the component, the software segment in the North America retail analytics market is dominated in 2022 and is anticipated to maintain its dominance throughout the forecast period. This dominance can be attributed to the pivotal role that software solutions play in enabling retailers to harness the power of data-driven insights. Retailers across North America are increasingly realizing the importance of sophisticated analytics software to gain deeper understanding into customer behavior, optimize inventory management, enhance pricing strategies, and improve overall operational efficiency. These software solutions encompass a wide range of applications, from predictive analytics for demand forecasting to AI-driven tools for customer personalization. As the retail landscape continues to evolve and become increasingly competitive, the demand for advanced software solutions that can provide actionable insights and drive informed decision-making is expected to remain high. Consequently, the software segment is well-positioned to drive innovation and shape the future of the North America retail analytics market.

Application Insights

Based on application, merchandising analytics segment emerged as the dominant force in the North America retail analytics market and is projected to sustain its dominance throughout the forecast period. This dominance can be attributed to the pivotal role that merchandising analytics plays in modern retail. North American retailers have recognized that data-driven insights are instrumental in optimizing their product assortments, pricing strategies, and overall merchandising efforts. By harnessing merchandising analytics, retailers can gain a deep understanding of consumer preferences, forecast demand accurately, and make strategic decisions that enhance both in-store and online shopping experiences. The surge in e-commerce, coupled with the complexity of omnichannel retail, has further solidified the importance of merchandising analytics. Retailers are increasingly relying on these tools to curate product offerings tailored to individual customer segments, ensuring that their merchandise aligns perfectly with evolving consumer trends. Additionally, pricing optimization, stock management, and demand forecasting are all areas where merchandising analytics proves indispensable, enabling retailers to maximize profitability and reduce wastage. As the North America retail landscape continues to evolve with changing consumer behaviour and market dynamics, the merchandising analytics segment remains at the forefront of innovation. Its capacity to provide data-driven insights that empower retailers to adapt and thrive in a competitive environment ensures its sustained dominance in the market. This segment will continue to shape the future of retail in North America by fostering efficiency, enhancing customer experiences, and driving strategic decision-making.

Deployment Mode Insights

Based on deployment mode, the cloud deployment mode emerged as the dominant segment in the North America retail analytics market and is anticipated to maintain its dominance throughout the forecast period. This dominance can be attributed to several key factors that align with the evolving needs of retailers in the region. Cloud-based retail analytics solutions offer unparalleled flexibility and scalability, enabling retailers to adapt swiftly to changing market conditions and consumer preferences. One of the primary drivers of the cloud's dominance is its ability to provide real-time access to data and analytics tools from virtually anywhere. This agility is particularly valuable in the fast-paced retail environment, allowing retailers to make informed decisions on the fly. Moreover, the cloud's scalability ensures that retailers can expand their analytics capabilities as their business grows, without the need for substantial upfront investments in hardware and infrastructure. Additionally, cloud deployment offers cost-efficiency, as it eliminates the need for maintaining and upgrading on-premises servers. This allows retailers to allocate resources more effectively and invest in other critical areas of their business. Furthermore, cloud solutions often come with built-in security features and regular updates, which are essential in addressing the evolving challenges of data security and privacy in the North American retail landscape.

Country Insights

United States emerged as the dominant country in the North America retail analytics market and is anticipated to maintain its dominance throughout the forecast period. This dominance can be attributed to several key factors that highlight the United States' position as a global retail powerhouse. With a vast and diverse retail landscape, including brick-and-mortar stores, e-commerce giants, and a thriving omni-channel market, the United States presents a unique set of challenges and opportunities for retailers. As a result, retailers in the U.S. are at the forefront of adopting advanced analytics solutions to gain a competitive edge.

The United States boasts a culture of innovation and technological advancement, which has led to the rapid adoption of data-driven decision-making in the retail sector. Retailers in the U.S. have been quick to recognize the value of analytics in optimizing inventory management, enhancing customer experiences, and improving overall operational efficiency. Additionally, the presence of major technology hubs and a robust ecosystem of analytics providers further propels the growth of the retail analytics market in the United States. Furthermore, the U.S. market's vast size and diversity in consumer preferences make it an ideal testing ground for retail analytics solutions, driving innovation and pushing the boundaries of what is possible in terms of data-driven retail strategies. As the retail industry continues to evolve and adapt to changing consumer behavior and market dynamics, the United States is poised to maintain its dominance in the North America retail analytics market, shaping the future of retail analytics in the region.

Report Scope:

In this report, the North America Retail Analytics Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

North America Retail Analytics Market, By Component:

  • Software
  • Services

North America Retail Analytics Market, By Deployment Mode:

  • Cloud
  • On-Premises

North America Retail Analytics Market, By Organization Size:

  • SME’s
  • Large Organization

North America Retail Analytics Market, By Application:

  • Customer Management
  • Inventory Analysis
  • Yield Analysis
  • Order & Fulfilment Management
  • Merchandising Analysis
  • Performance Analysis
  • Pricing Analysis
  • Cluster Planning & Transportation Management
  • Others

North America Retail Analytics Market, By End User:

  • Offline
  • Online

North America Retail Analytics Market, By Country:

  • United States
  • Canada
  • Mexico

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the North America Retail Analytics Market.

Available Customizations:

North America retail analytics market report with the given market data, the publisher offers customizations according to a company's specific needs.


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Table of Contents

1. Service Overview
1.1. Market Definition
1.2. Scope of the Market
1.2.1. Markets Covered
1.2.2. Years Considered for Study
1.2.3. Key Market Segmentations
2. Research Methodology
2.1. Objective of the Study
2.2. Baseline Methodology
2.3. Key Industry Partners
2.4. Major Association and Secondary Sources
2.5. Forecasting Methodology
2.6. Data Triangulation & Validation
2.7. Assumptions and Limitations
3. Executive Summary4. Impact of COVID-19 on North America Retail Analytics Market5. Voice of Customer6. North America Retail Analytics Market Overview
7. North America Retail Analytics Market Outlook
7.1. Market Size & Forecast
7.1.1. By Value
7.2. Market Share & Forecast
7.2.1. By Component (Software, Service)
7.2.2. By Deployment Mode (Cloud, On-Premises)
7.2.3. By Organization Size (SME’s, Large Organization)
7.2.4. By Application (Customer Management, Inventory Analysis, Yield Analysis, Order & Fulfilment Management, Merchandising Analysis, Performance Analysis, Pricing Analysis, Cluster Planning & Transportation Management, and Others)
7.2.5. By End User (Offline, Online)
7.2.6. By Country (United States, Canada, and Mexico)
7.3. By Company (2022)
7.4. Market Map
8. United States Retail Analytics Market Outlook
8.1. Market Size & Forecast
8.1.1. By Value
8.2. Market Share & Forecast
8.2.1. By Component
8.2.2. By Deployment Mode
8.2.3. By Organization Size
8.2.4. By Application
8.2.5. By End User
9. Canada Retail Analytics Market Outlook
9.1. Market Size & Forecast
9.1.1. By Value
9.2. Market Share & Forecast
9.2.1. By Component
9.2.2. By Deployment Mode
9.2.3. By Organization Size
9.2.4. By Application
9.2.5. By End User
10. Mexico Retail Analytics Market Outlook
10.1. Market Size & Forecast
10.1.1. By Value
10.2. Market Share & Forecast
10.2.1. By Component
10.2.2. By Deployment Mode
10.2.3. By Organization Size
10.2.4. By Application
10.2.5. By End User
11. Market Dynamics
11.1. Drivers
11.2. Challenges
12. Market Trends and Developments
13. Company Profiles
13.1. IBM (International Business Machines Corporation)
13.1.1. Business Overview
13.1.2. Key Revenue and Financials
13.1.3. Recent Developments
13.1.4. Key Personnel
13.1.5. Key Product/Services Offered
13.2. SAS Institute Inc.
13.2.1. Business Overview
13.2.2. Key Revenue and Financials
13.2.3. Recent Developments
13.2.4. Key Personnel
13.2.5. Key Product/Services Offered
13.3. Oracle America, Inc.
13.3.1. Business Overview
13.3.2. Key Revenue and Financials
13.3.3. Recent Developments
13.3.4. Key Personnel
13.3.5. Key Product/Services Offered
13.4. SAP America Inc.
13.4.1. Business Overview
13.4.2. Key Revenue and Financials
13.4.3. Recent Developments
13.4.4. Key Personnel
13.4.5. Key Product/Services Offered
13.5. Microsoft Corporation
13.5.1. Business Overview
13.5.2. Key Revenue and Financials
13.5.3. Recent Developments
13.5.4. Key Personnel
13.5.5. Key Product/Services Offered
13.6. Teradata Corporation
13.6.1. Business Overview
13.6.2. Key Revenue and Financials
13.6.3. Recent Developments
13.6.4. Key Personnel
13.6.5. Key Product/Services Offered
13.7. MicroStrategy Incorporated
13.7.1. Business Overview
13.7.2. Key Revenue and Financials
13.7.3. Recent Developments
13.7.4. Key Personnel
13.7.5. Key Product/Services Offered
13.8. Tableau Software LLC (a Salesforce Company)
13.8.1. Business Overview
13.8.2. Key Revenue and Financials
13.8.3. Recent Developments
13.8.4. Key Personnel
13.8.5. Key Product/Services Offered
13.9. Qlik Technologies Inc.
13.9.1. Business Overview
13.9.2. Key Revenue and Financials
13.9.3. Recent Developments
13.9.4. Key Personnel
13.9.5. Key Product/Services Offered
13.10. Domo, Inc.
13.10.1. Business Overview
13.10.2. Key Revenue and Financials
13.10.3. Recent Developments
13.10.4. Key Personnel
13.10.5. Key Product/Services Offered
14. Strategic Recommendations15. About the Publisher & Disclaimer

Companies Mentioned (Partial List)

A selection of companies mentioned in this report includes, but is not limited to:

  • IBM (International Business Machines Corporation)
  • SAS Institute Inc.
  • Oracle America, Inc.
  • SAP America, Inc.
  • Microsoft Corporation
  • Teradata Corporation
  • MicroStrategy Incorporated
  • Tableau Software Inc.
  • Qlik Technologies Inc.
  • Domo, Inc.

Table Information