Big Data Analytics in Retail Market Size, Share, and Growth Analysis

Big Data Analytics in Retail Market By Offering (Solutions, Services), By Deployment Mode (On-premises, Cloud), By Application (Customer Analytics, Operational Analytics), By Region -Industry Forecast 2025-2032


Report ID: SQMIG45A2448 | Region: Global | Published Date: February, 2025
Pages: 183 |Tables: 89 |Figures: 76

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Big Data Analytics in Retail Market Insights

Global Big Data Analytics in Retail Market size was valued at USD 5.26 billion in 2023 and is poised to grow from USD 6.38 billion in 2024 to USD 29.70 billion by 2032, growing at a CAGR of 21.2% in the forecast period (2025-2032).

Predictive analytics is a proactive approach whereby retailers can use data from the past to predict expected sales growth due to changes in consumer behaviors and market trends. It can help retailers stay ahead of the curve, compete effectively, and gain considerable global big data analytics in retail market share. Increased emphasis on predictive analytics which can help increase promotional effectiveness, drive cross-selling, and much more to build sustainable relationships with the customers.

Retailers attempt to find innovative ways to draw insights from the ever-increasing amount of structured and unstructured information about consumer behavior. Retailers, both offline and online, are adopting the data- driven approach toward understanding their customers' buying behavior, mapping them to products, and planning marketing strategies to sell their products to increase profits by applying big data analytics at every step of the retail process. Innovative ways such as implementing IPS systems, store automation with self-checkout, robots, and automation in retail drive the market.

Data integration challenges could restrain the market, including data governance, scalability, and problems associated with getting data from multiple sources to have data duplication and transformation rules. However, these can be reduced with the proper systematic set of rules.

Market snapshot - (2025-2032)

Global Market Size

USD 5.26 billion

Largest Segment

Solutions

Fastest Growth

Services

Growth Rate

21.2% CAGR

Global Big Data Analytics in Retail Market ($ Bn)
Country Share for North America Region (%)

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Big Data Analytics in Retail Market Segments Analysis

Global big data analytics in retail market is segmented into offering, deployment mode, application, and region. Based on offering, the market is segmented into solutions and services. Based on deployment mode, the market is segmented into on-premises, cloud and hybrid. Based on application, the market is segmented into customer analytics, operational analytics, quality assessment, supply chain management, production management and others. Based on the region, the market is segmented into North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa.

Analysis by Deployment Mode

The on-premises segment dominated the global big data analytics in retail market due to enhanced data security and control and enhanced data security and control. These improvements are driven by improved data security, regulatory compliance and flexibility to tailor solutions to specific policy needs. Premises solutions provide unparalleled control over critical manufacturing data, ensuring it within the organization’s infrastructure. Industries such as aerospace, defense and pharma rely heavily on this sector to protect intellectual property and meet stringent regulations. Unlike cloud solutions, on-premises infrastructure mitigates external cyber threats, a priority for employees handling proprietary systems or sensitive manufacturing data.

As per global big data analytics in retail market forecast, the cloud segment is the fastest growing segment in the market. Rising adoption of cloud-based software solutions among the organizations is expected to create lucrative market opportunities for big data solution providers in the coming years. Cloud-based big data analytics in manufacturing operations also help to process and analyze the database to improve the production process and inventory management in the retail industry. Cloud-based big data solutions help organizations gain an in-depth understanding of the improvements, trends, and preferences. This understanding is utilized for effective and efficient supply chain management and operational decisions based on analytical outputs.

Analysis by Offering

As per global big data analytics in retail market analysis, the solutions segment dominated with the highest CAGR in the coming year due to rising demand for customer insights. Big data solution provides a platform to analyze the large volume of structured and unstructured data gathered from different sources such as IoT devices, sensors, social networks, and among others. Big data solutions support the retail industry to improvise end-to-end supply chain visibility as well as accelerate information sharing and decision making with the help of cognitive technology. Moreover, predictive analytics is also used for more accurate requirements, forecasts, and reducing buffer inventory. Further, big data analytics in manufacturing help manufacturers to reduce labor-intensive workload, improve operational visibility and gain profound analytics by establishing a single source for all inventory data and reports. As per global big data analytics in retail market outlook, the services segment is the fastest growing in the market due to increasing adoption of big data analytics by several manufacturers to predict equipment failures and maintenance needs. Furthermore, the main advantage of using big data analytics is that it enables manufacturers to monitor and control product quality in real-time, minimizing defects, scrap, and rework, which can lead to substantial savings. Factors such as the increasing consumer expectations for product quality, customization, and delivery `speed are fueling the adoption of big data services by manufacturers to meet these demands efficiently. Hence, such factors are expected to fuel the growth of this segment which, in turn, will drive the big data analytics in retail market growth during the forecast period.

Global Big Data Analytics in Retail Market By Offering (%)

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Big Data Analytics in Retail Market Regional Insights

North America dominated the market in 2024 due to the rise in data production and retail consumption with corresponding sales increases. The region boasts a strong foothold of big data analytics vendors, which further contributes to the market's growth. Some include IBM Corporation, SAS Institute Inc., Alteryx Inc., and Microstrategy Incorporated. The increasing adoption of industry 4.0 across the retail sector is one of the primary aspects encouraging market growth. In retail 4.0, several operations and processes in the retail industry, like inventory management, customer service, customer accounts, supply chain management, and merchandising management activities, became digitized and automated.

Asia Pacific region is anticipated to grow in terms of CAGR during the forecast period. Many regulatory bodies of the Asia Pacific countries are taking initiatives to deploy advanced technology solutions in the industry. In India, retail has emerged as a high growth sector and is expected to support in growth of the country in the coming years. This growth of the industry in India is likely due to the rising focus of government towards the manufacturing sector. For instance, the Make in India program initiated by the government of India as well as strategic partnerships are expected to increase the development of the manufacturing sector soon. Furthermore, in China, “Made in China 2025” initiative is anticipated to boost the development of the Chinese manufacturing sector in the coming years.

Global Big Data Analytics in Retail Market By Geography
  • Largest
  • Fastest

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Big Data Analytics in Retail Market Dynamics

Drivers

Growth of Big Data Analytics in the Retail Sector

  • E-commerce has impacted traditional brick-and-mortar retailers, reduced their significance and marked the data-driven revolution in the retail sector. An efficient supply chain, the optimized movement of goods from supplier to warehouse to store to the customer, is critical to every business. Therefore, big data analytics is at the core of revolutionizing the retail supply chain, i.e., tracking and tracing product flow and stock levels in real-time, leveraging customer data to predict buying patterns, and even using robots to fulfill orders in vast automated warehouses tirelessly.

Increasing Adoption of Databases

  • The increasing digital solutions across business sectors, such as banking, healthcare, BFSI, retail, agriculture, and telecom/media, significantly increase data. For instance, artificial intelligence brings a noteworthy change in the agriculture sector's risk management, precision farming, and pest control. Smart machines, soil sensors, and GPS-equipped tractors generate massive data sets. In agriculture, big data analytics is applied to analyze huge data sets, such as advanced risk assessment, supply tracks, natural trends, ideal crops, and more.

Restraints

Growing Security Concerns

  • The technology contains major security concerns, including fake data generation, the need for real-time security, and customers’ data privacy and security, among others. Remote storage, weak identity governance, low investment in the system and network security, human error, connected devices, and Internet of Things (IoT) applications are some of the major areas that need to be addressed. Overcoming these challenges is a major task for organizations. The increasing data loss or cyberattacks on stored customer data across industries will likely hamper market growth.

Increased Processing Costs and Data Privacy Concerns

  • One of the main challenges facing big data analytics in retail market is the high cost. Manufacturers need to invest in advanced hardware, advanced software solutions and skilled personnel to integrate and manage big data systems. This huge financial burden is particularly dangerous for small and medium-sized enterprises (SMEs), which often operate under restricted budgets, limiting the widespread use of big data technologies. Another important imperative is data growing privacy and security concerns.

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Big Data Analytics in Retail Market Competitive Landscape

The competitive landscape of the global big data analytics in retail industry is characterized by the presence of prominent technology companies, retail solution providers, and emerging startups driving innovation in the sector. Leading players such as IBM Corporation, Oracle Corporation, Microsoft, Amazon Web Services (AWS), and SAP SE are at the forefront, offering advanced analytics platforms tailored for retail applications. These companies focus on providing end-to-end solutions, including customer behavior analysis, inventory management, and demand forecasting, to enhance operational efficiency and customer experiences. Meanwhile, startups and niche providers are leveraging AI and machine learning to deliver specialized solutions, such as real-time insights, predictive analytics, and automated decision-making.

Top Player’s Company Profiles

  • IBM Corporation
  • Intel Corporation
  • Microsoft Corporation
  • Oracle Corporation
  • SAP SE
  • Cisco Systems, Inc.
  • Hewlett Packard Enterprise
  • Siemens AG
  • Dell Technologies
  • Hitachi, Ltd.
  • Fujitsu Limited
  • PTC, Inc.
  • Teradata Corporation
  • Cloudera, Inc.
  • Alteryx, Inc.
  • Splunk Inc.
  • RapidMiner, Inc.
  • TIBCO Software Inc.
  • Accenture Plc
  • SAS Institute, Inc.

Recent Developments

  • September 2022 - Coresight Research, a global provider of research, data, events, and advisory services for consumer-facing retail technology and real estate companies and investors, acquired Alternative Data Analytics, a leading data strategy, and insights firm. This acquisition will significantly increase data capabilities and further extend expertise in data-driven research.
  • August 2022 - Global Measurement and Data Analytics company Nielsen and Microsoft launched a new enterprise data solution to accelerate innovation in retail using Artificial Intelligence data analytics to create scalable, high-performance data environments.
  • August 2022- Maxis took a significant stake in Malaysian-based retail analytics startup, ComeBy, to empower innovation and digitalization in the retail industry with greater access to technology and the human network to create more economic multipliers for the country.

Big Data Analytics in Retail Key Market Trends

Big Data Analytics in Retail Market SkyQuest Analysis

SkyQuest’s ABIRAW (Advanced Business Intelligence, Research & Analysis Wing) is our Business Information Services team that Collects, Collates, Co-relates, and Analyses the Data collected by means of Primary Exploratory Research backed by the robust Secondary Desk research.

According to SkyQuest analysis, big data analytics in retail industry is growing rapidly, driven by a combination of trends such as IoT and AI-powered analytics. These innovations allow manufacturers to streamline processes, improve predictive maintenance, and align production with market requirements. However, challenges such as high implementation costs and data security concerns pose significant barriers, especially for small businesses. Despite these limitations, the market is poised for significant growth, as companies increasingly recognize the value of data-driven insights to increase operational efficiency and maintain a competitive edge. As the global economy becomes interconnected and complex, companies find it challenging to meet customer expectations.

Report Metric Details
Market size value in Retail USD 5.26 billion
Market size value in 2032 USD 29.70 billion
Growth Rate 21.2%
Base year 2024
Forecast period (2025-2032)
Forecast Unit (Value) USD Billion
Segments covered
  • Offering
    • Solutions and Services
  • Application
    • Customer Analytics, Operational Analytics, Quality Assessment, Supply Chain Management, Production Management and Others
  • Deployment Mode
    • On-premises, Cloud and Hybrid
Regions covered North America (US, Canada), Europe (Germany, France, United Kingdom, Italy, Spain, Rest of Europe), Asia Pacific (China, India, Japan, Rest of Asia-Pacific), Latin America (Brazil, Rest of Latin America), Middle East & Africa (South Africa, GCC Countries, Rest of MEA)
Companies covered
  • IBM Corporation
  • Intel Corporation
  • Microsoft Corporation
  • Oracle Corporation
  • SAP SE
  • Cisco Systems, Inc.
  • Hewlett Packard Enterprise
  • Siemens AG
  • Dell Technologies
  • Hitachi, Ltd.
  • Fujitsu Limited
  • PTC, Inc.
  • Teradata Corporation
  • Cloudera, Inc.
  • Alteryx, Inc.
  • Splunk Inc.
  • RapidMiner, Inc.
  • TIBCO Software Inc.
  • Accenture Plc
  • SAS Institute, Inc.
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Table Of Content

Executive Summary

Market overview

  • Exhibit: Executive Summary – Chart on Market Overview
  • Exhibit: Executive Summary – Data Table on Market Overview
  • Exhibit: Executive Summary – Chart on Big Data Analytics in Retail Market Characteristics
  • Exhibit: Executive Summary – Chart on Market by Geography
  • Exhibit: Executive Summary – Chart on Market Segmentation
  • Exhibit: Executive Summary – Chart on Incremental Growth
  • Exhibit: Executive Summary – Data Table on Incremental Growth
  • Exhibit: Executive Summary – Chart on Vendor Market Positioning

Parent Market Analysis

Market overview

Market size

  • Market Dynamics
    • Exhibit: Impact analysis of DROC, 2021
      • Drivers
      • Opportunities
      • Restraints
      • Challenges
  • SWOT Analysis

KEY MARKET INSIGHTS

  • Technology Analysis
    • (Exhibit: Data Table: Name of technology and details)
  • Pricing Analysis
    • (Exhibit: Data Table: Name of technology and pricing details)
  • Supply Chain Analysis
    • (Exhibit: Detailed Supply Chain Presentation)
  • Value Chain Analysis
    • (Exhibit: Detailed Value Chain Presentation)
  • Ecosystem Of the Market
    • Exhibit: Parent Market Ecosystem Market Analysis
    • Exhibit: Market Characteristics of Parent Market
  • IP Analysis
    • (Exhibit: Data Table: Name of product/technology, patents filed, inventor/company name, acquiring firm)
  • Trade Analysis
    • (Exhibit: Data Table: Import and Export data details)
  • Startup Analysis
    • (Exhibit: Data Table: Emerging startups details)
  • Raw Material Analysis
    • (Exhibit: Data Table: Mapping of key raw materials)
  • Innovation Matrix
    • (Exhibit: Positioning Matrix: Mapping of new and existing technologies)
  • Pipeline product Analysis
    • (Exhibit: Data Table: Name of companies and pipeline products, regional mapping)
  • Macroeconomic Indicators

COVID IMPACT

  • Introduction
  • Impact On Economy—scenario Assessment
    • Exhibit: Data on GDP - Year-over-year growth 2016-2022 (%)
  • Revised Market Size
    • Exhibit: Data Table on Big Data Analytics in Retail Market size and forecast 2021-2027 ($ million)
  • Impact Of COVID On Key Segments
    • Exhibit: Data Table on Segment Market size and forecast 2021-2027 ($ million)
  • COVID Strategies By Company
    • Exhibit: Analysis on key strategies adopted by companies

MARKET DYNAMICS & OUTLOOK

  • Market Dynamics
    • Exhibit: Impact analysis of DROC, 2021
      • Drivers
      • Opportunities
      • Restraints
      • Challenges
  • Regulatory Landscape
    • Exhibit: Data Table on regulation from different region
  • SWOT Analysis
  • Porters Analysis
    • Competitive rivalry
      • Exhibit: Competitive rivalry Impact of key factors, 2021
    • Threat of substitute products
      • Exhibit: Threat of Substitute Products Impact of key factors, 2021
    • Bargaining power of buyers
      • Exhibit: buyers bargaining power Impact of key factors, 2021
    • Threat of new entrants
      • Exhibit: Threat of new entrants Impact of key factors, 2021
    • Bargaining power of suppliers
      • Exhibit: Threat of suppliers bargaining power Impact of key factors, 2021
  • Skyquest special insights on future disruptions
    • Political Impact
    • Economic impact
    • Social Impact
    • Technical Impact
    • Environmental Impact
    • Legal Impact

Market Size by Region

  • Chart on Market share by geography 2021-2027 (%)
  • Data Table on Market share by geography 2021-2027(%)
  • North America
    • Chart on Market share by country 2021-2027 (%)
    • Data Table on Market share by country 2021-2027(%)
    • USA
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
    • Canada
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
  • Europe
    • Chart on Market share by country 2021-2027 (%)
    • Data Table on Market share by country 2021-2027(%)
    • Germany
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
    • Spain
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
    • France
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
    • UK
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
    • Rest of Europe
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
  • Asia Pacific
    • Chart on Market share by country 2021-2027 (%)
    • Data Table on Market share by country 2021-2027(%)
    • China
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
    • India
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
    • Japan
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
    • South Korea
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
    • Rest of Asia Pacific
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
  • Latin America
    • Chart on Market share by country 2021-2027 (%)
    • Data Table on Market share by country 2021-2027(%)
    • Brazil
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
    • Rest of South America
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
  • Middle East & Africa (MEA)
    • Chart on Market share by country 2021-2027 (%)
    • Data Table on Market share by country 2021-2027(%)
    • GCC Countries
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
    • South Africa
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)
    • Rest of MEA
      • Exhibit: Chart on Market share 2021-2027 (%)
      • Exhibit: Market size and forecast 2021-2027 ($ million)

KEY COMPANY PROFILES

  • Competitive Landscape
    • Total number of companies covered
      • Exhibit: companies covered in the report, 2021
    • Top companies market positioning
      • Exhibit: company positioning matrix, 2021
    • Top companies market Share
      • Exhibit: Pie chart analysis on company market share, 2021(%)

Methodology

For the Big Data Analytics in Retail Market, our research methodology involved a mixture of primary and secondary data sources. Key steps involved in the research process are listed below:

1. Information Procurement: This stage involved the procurement of Market data or related information via primary and secondary sources. The various secondary sources used included various company websites, annual reports, trade databases, and paid databases such as Hoover's, Bloomberg Business, Factiva, and Avention. Our team did 45 primary interactions Globally which included several stakeholders such as manufacturers, customers, key opinion leaders, etc. Overall, information procurement was one of the most extensive stages in our research process.

2. Information Analysis: This step involved triangulation of data through bottom-up and top-down approaches to estimate and validate the total size and future estimate of the Big Data Analytics in Retail Market.

3. Report Formulation: The final step entailed the placement of data points in appropriate Market spaces in an attempt to deduce viable conclusions.

4. Validation & Publishing: Validation is the most important step in the process. Validation & re-validation via an intricately designed process helped us finalize data points to be used for final calculations. The final Market estimates and forecasts were then aligned and sent to our panel of industry experts for validation of data. Once the validation was done the report was sent to our Quality Assurance team to ensure adherence to style guides, consistency & design.

Analyst Support

Customization Options

With the given market data, our dedicated team of analysts can offer you the following customization options are available for the Big Data Analytics in Retail Market:

Product Analysis: Product matrix, which offers a detailed comparison of the product portfolio of companies.

Regional Analysis: Further analysis of the Big Data Analytics in Retail Market for additional countries.

Competitive Analysis: Detailed analysis and profiling of additional Market players & comparative analysis of competitive products.

Go to Market Strategy: Find the high-growth channels to invest your marketing efforts and increase your customer base.

Innovation Mapping: Identify racial solutions and innovation, connected to deep ecosystems of innovators, start-ups, academics, and strategic partners.

Category Intelligence: Customized intelligence that is relevant to their supply Markets will enable them to make smarter sourcing decisions and improve their category management.

Public Company Transcript Analysis: To improve the investment performance by generating new alpha and making better-informed decisions.

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FAQs

Global Big Data Analytics in Retail Market size was valued at USD 5.26 billion in 2023 and is poised to grow from USD 6.38 billion in 2024 to USD 29.70 billion by 2032, growing at a CAGR of 21.2% in the forecast period (2025-2032).

The competitive landscape of the global big data analytics in retail industry is characterized by the presence of prominent technology companies, retail solution providers, and emerging startups driving innovation in the sector. Leading players such as IBM Corporation, Oracle Corporation, Microsoft, Amazon Web Services (AWS), and SAP SE are at the forefront, offering advanced analytics platforms tailored for retail applications. These companies focus on providing end-to-end solutions, including customer behavior analysis, inventory management, and demand forecasting, to enhance operational efficiency and customer experiences. Meanwhile, startups and niche providers are leveraging AI and machine learning to deliver specialized solutions, such as real-time insights, predictive analytics, and automated decision-making. 'IBM Corporation ', 'Intel Corporation ', 'Microsoft Corporation ', 'Oracle Corporation ', 'SAP SE ', 'Cisco Systems, Inc. ', 'Hewlett Packard Enterprise ', 'Siemens AG ', 'Dell Technologies ', 'Hitachi, Ltd. ', 'Fujitsu Limited ', 'PTC, Inc. ', 'Teradata Corporation ', 'Cloudera, Inc. ', 'Alteryx, Inc. ', 'Splunk Inc. ', 'RapidMiner, Inc. ', 'TIBCO Software Inc. ', 'Accenture Plc ', 'SAS Institute, Inc.'

E-commerce has impacted traditional brick-and-mortar retailers, reduced their significance and marked the data-driven revolution in the retail sector. An efficient supply chain, the optimized movement of goods from supplier to warehouse to store to the customer, is critical to every business. Therefore, big data analytics is at the core of revolutionizing the retail supply chain, i.e., tracking and tracing product flow and stock levels in real-time, leveraging customer data to predict buying patterns, and even using robots to fulfill orders in vast automated warehouses tirelessly.

Growing Trend of Edge Computing to Surge Big Data Analytics Tools Demand: The increasing number of connected IoT devices is fueled by the expanding adoption of Machine Learning (ML) algorithms, Artificial Intelligence (AI), and the Internet of Things (IoT). According to the International Data Corporation (IDC) data, 152,200 IoT devices will connect per minute by 2025. The increasing requirement for connected devices accelerates the execution of edge computing. Edge computing solutions are defined as a structure where the processors are placed closer to the destination or source for data instead of clouds.

North America dominated the market in 2024 due to the rise in data production and retail consumption with corresponding sales increases. The region boasts a strong foothold of big data analytics vendors, which further contributes to the market's growth. Some include IBM Corporation, SAS Institute Inc., Alteryx Inc., and Microstrategy Incorporated. The increasing adoption of industry 4.0 across the retail sector is one of the primary aspects encouraging market growth. In retail 4.0, several operations and processes in the retail industry, like inventory management, customer service, customer accounts, supply chain management, and merchandising management activities, became digitized and automated.

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