The global big data analytics in retail market reached a market size of USD 4.56 Billion in 2020 and is expected to register a robust CAGR of 21.2% over the forecast period, according to latest analysis by Emergen Research. Growing need to enhance customer experience with personalized offerings in the retail industry is among some of the key factors expected to drive growth of the global big data analytics in retail market during the forecast period. Retail businesses analyze in-store surveillance recordings and data from sensors to enhance consumer experience.
However, concerns related to storing and processing data from disparate applications are expected to restraint global big data analytics in retail market growth to a certain extent over the forecast period.
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Key Highlights of Report
- Due to high presence of international players such as Oracle Corporation, Zoho Corporation, and International Business Machines Corporation in countries in North America, the market in the region is expected to account for comparatively higher revenue share among other regional markets during the forecast period.
- Key market players include Oracle Corporation, Zoho Corporation, SAP SE, Qlik Technologies Inc., International Business Machines Corporation, Retail Next Inc., Salesforce.com Inc., Microstrategy Inc., Alteryx Inc., and Fuzzy Logix LLC.
- In May 2019, SAP SE declared that NPC International (NPC), which is the world’s leading Pizza Hut and Wendy’s franchisee, deployed SuccessFactors SAS applications for human capital management and SAP S/4HANA Cloud solutions for enterprise resource planning. Through applications rolled out to 40,000 U.S. workforce, NPC has effectively simplified its activities and built a digital roadmap toward the future.
Big Data Analytics in Retail Market Segmentation:
Emergen Research has segmented the global big data analytics in retail market on the basis of component, deployment, application, and region.
- Component Outlook (Revenue, USD Billion; 2024–2028)
- Services
- Software
- Deployment Outlook (Revenue, USD Billion; 2024–2028)
- Cloud-Based
- On-Premises
- Application Outlook (Revenue, USD Billion; 2024–2028)
- Customer Analytics
- Sales & Marketing Analytics
- Merchandising Analytics
- Supply Chain Operations Management
- Social Media Analytics
- Others
Key Geographical Segments:
- North America (U.S., Canada)
- Europe (U.K., Italy, Germany, France, Rest of EU)
- Asia Pacific (India, Japan, China, South Korea, Australia, Rest of APAC)
- Latin America (Chile, Brazil, Argentina, Rest of Latin America)
- Middle East & Africa (Saudi Arabia, U.A.E., South Africa, Rest of MEA)
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Major Objectives of the Study:
- To offer a comprehensive analysis of the market scenario to derive an accurate forecast of the market and its major segments
- Accurate insights into the future growth prospects of the market through an analysis of the influencing factors
- Analysis of vital aspects of the market including cost analysis, supply chain analysis, Porter’s Five Forces analysis, SWOT analysis, and investment return analysis
- Extensive historical and forecast estimation of the market revenue based on its key segments and key regions
- Comprehensive analysis of the competitive landscape of the market along with exhaustive profiling of the key competitors, product portfolio, and manufacturing and production capabilities
- An accurate and comprehensive 8-year forecast for the Big Data Analytics in Retail industry vertical on both regional and global scale
Table of Content:
Chapter 1. Methodology & Sources
1.1. Market Definition
1.2. Research Scope
1.3. Methodology
1.4. Research Sources
1.4.1. Primary
1.4.2. Secondary
1.4.3. Paid Sources
1.5. Market Estimation Technique
Chapter 2. Executive Summary
2.1. Summary Snapshot, 2020-2028
Chapter 3. Key Insights
Chapter 4. Big Data Analytics in Retail Market Segmentation & Impact Analysis
4.1. Big Data Analytics in Retail Market Segmentation Analysis
4.2. Industrial Outlook
4.2.1. Market indicators analysis
4.2.2. Market drivers analysis
4.2.2.1. Increasing focus on data-driven decision making for store layout and staff management
4.2.2.2. Growing need to enhance customer experience with personalized offering
4.2.2.3. Rising demand for price optimization in retail industry
4.2.2.4. Increasing demand for predictive analytics in retail industry
4.2.3. Market restraints analysis
4.2.3.1. Concerns in storing and processing data from disparate applications
4.2.3.2. Challenges in the capture of consumer information
4.3. Technological Insights
4.4. Regulatory Framework
4.5. Porter’s Five Forces Analysis
4.6. Competitive Metric Space Analysis
4.7. Price trend Analysis
4.8. Covid-19 Impact Analysis
READ MORE…!
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