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Worldwide Big Data Analytics in Retail Industry to 2027 - Growing Demand of Predictive Analytics in Retail Presents Opportunities

Research and Markets
·8-min read

Dublin, Nov. 13, 2020 (GLOBE NEWSWIRE) -- The "Big Data Analytics in Retail Market by Component, Deployment, Enterprise Size and Application: Global Opportunity Analysis and Industry Forecast, 2020-2027" report has been added to ResearchAndMarkets.com's offering.

Big data analytics in retail can enable detecting customer behavior, discovering customer shopping patterns and trends, improving the quality of customer service, and achieving better customer retention and satisfaction. It can be used by retailers for customer segmentation, customer loyalty analysis, pricing analysis, cross selling, supply chain management, demand forecasting, market basket analysis, finance and fixed asset management and more.

Increase in spending on big data analytics tools, rise in need to deliver personalized customer experience to increase sales, surge in adoption of customer-centric strategies as well as rise in awareness about the benefits of big data analytics in retail are the major factors that fuel the growth of the big data analytics in retail market. In addition, increasing growth of e-commerce sector is also propelling the growth of this market. However, issues in collecting and collating the data from disparate systems is expected to hinder the big data analytics in retail market growth. On the contrary, integration of new technologies such as machine learning and AI in big data analytics in retail is expected to provide lucrative opportunities for the market growth in the coming years.

The big data analytics in retail market is segmented on the basis of component, deployment, organization size, application, and region. By component, the market is categorized into software and service. On the basis of deployment, it is classified into on-premise and cloud. As per organization size, market is divided into large enterprises and small & medium sized enterprises (SMEs). Depending on application, it is divided into sales & marketing analytics, supply chain operations management, merchandising analytics, customer analytics and others. By region, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.

The company profiles in the big data analytics in retail market players included in this report are Alteryx Inc., IBM, Microsoft, Microstrategy Inc., Oracle Corporation, Qlik Technologies Inc., RetailNext, SAP SE, SAS institute, and Teradata.

Key Benefits for Stakeholders

  • The study provides an in-depth analysis of the global big data analytics in retail market along with the current & future trends to elucidate the imminent investment pockets.

  • Information about key drivers, restrains, and opportunities and their impact analyses on the market size is provided in the report.

  • Porter's five forces analysis illustrates the potency of buyers and suppliers operating in the industry.

  • The quantitative analysis of the global big data analytics in retail market from 2019 to 2027 is provided to determine the market potential.

Key Topics Covered:

Chapter 1: Introduction
1.1. Report Description
1.2. Key Benefits for Stakeholders
1.3. Key Market Segments
1.4. Research Methodology
1.4.1. Secondary Research
1.4.2. Primary Research
1.4.3. Analyst Tools & Models

Chapter 2: Executive Summary
2.1. Key Findings
2.1.1. Top Impacting Factors
2.1.2. Top Investment Pockets
2.2. Cxo Perspective

Chapter 3: Market Overview
3.1. Market Definition and Scope
3.2. Porter'S Five Forces Analysis
3.3. Key Player Positioning
3.4. Case Studies
3.4.1. Case Study 01
3.4.2. Case Study 02
3.5. Market Dynamics
3.5.1. Drivers
3.5.1.1. Increase in Spending on Big Data Analytics Tools
3.5.1.2. Rise in Need to Deliver Personalized Customer Experience to Increase Sales
3.5.1.3. Increasing Growth of E-Commerce Sector
3.5.2. Restraints
3.5.2.1. Collecting and Collating the Data from Disparate Systems
3.5.2.2. To Capture Customer Data
3.5.3. Opportunity
3.5.3.1. Integration of New Technologies Such as Iot, Ai and Machine Learning in Big Data Analytics in Retail
3.5.3.2. Growing Demand of Predictive Analytics in Retail
3.6. Impact Analysis: Covid-19 on Big Data in Retail Analytics Market
3.6.1. Impact on Market Size
3.6.2. Consumer Trends, Preferences, and Budget Impact
3.6.3. Regulatory Framework
3.6.4. Economic Impact
3.6.5. Key Player Strategies to Tackle Negative Impact
3.6.6. Opportunity Window (Due to Covid Outbreak)

Chapter 4: Big Data Analytics in Retail Market, by Component
4.1. Overview
4.2. Software
4.2.1. Key Market Trends, Growth Factors, and Opportunities
4.2.2. Market Size and Forecast, by Region
4.2.3. Market Analysis, by Region
4.3. Service
4.3.1. Key Market Trends, Growth Factors, and Opportunities
4.3.2. Market Size and Forecast, by Region
4.3.3. Market Analysis, by Region

Chapter 5: Big Data Analytics in Retail Market, by Deployment
5.1. Overview
5.2. On Premise
5.2.1. Key Market Trends, Growth Factors, and Opportunities
5.2.2. Market Size and Forecast, by Region
5.2.3. Market Analysis, by Region
5.3. Cloud
5.3.1. Key Market Trends, Growth Factors, and Opportunities
5.3.2. Market Size and Forecast, by Region
5.3.3. Market Analysis, by Region

Chapter 6: Big Data Analytics in Retail Market, by Organization Size
6.1. Overview
6.2. Large Enterprises
6.2.1. Key Market Trends, Growth Factors, and Opportunities
6.2.2. Market Size and Forecast, by Region
6.2.3. Market Analysis, by Region
6.3. Smes
6.3.1. Key Market Trends, Growth Factors, and Opportunities
6.3.2. Market Size and Forecast, by Region
6.3.3. Market Analysis, by Region

Chapter 7: Big Data Analytics in Retail Market, by Application
7.1. Overview
7.2. Sales and Marketing Analytics
7.2.1. Key Market Trends, Growth Factors, and Opportunities
7.2.2. Market Size and Forecast, by Region
7.2.3. Market Analysis, by Region
7.3. Supply Chain Operations Management
7.3.1. Key Market Trends, Growth Factors, and Opportunities
7.3.2. Market Size and Forecast, by Region
7.3.3. Market Analysis, by Region
7.4. Merchandising Analytics
7.4.1. Key Market Trends, Growth Factors, and Opportunities
7.4.2. Market Size and Forecast, by Region
7.4.3. Market Analysis, by Region
7.5. Customer Analytics
7.5.1. Key Market Trends, Growth Factors, and Opportunities
7.5.2. Market Size and Forecast, by Region
7.5.3. Market Analysis, by Region
7.6. Others
7.6.1. Key Market Trends, Growth Factors, and Opportunities
7.6.2. Market Size and Forecast, by Region
7.6.3. Market Analysis, by Region

Chapter 8: Big Data Analytics in Retail Market, by Region
8.1. Overview
8.2. North America
8.3. Europe
8.4. Asia-Pacific
8.5. LAMEA

Chapter 9: Competitive Landscape
9.1. Competitive Dashboard
9.2. Top Winning Strategies
9.3. Key Developments
9.3.1. New Product Launches
9.3.2. Partnership
9.3.3. Acquisition
9.3.4. Product Development
9.3.5. Business Expansion
9.3.6. Collaboration
9.3.7. Agreement

Chapter 10: Company Profile
10.1. Adobe Inc.
10.1.1. Company Overview
10.1.2. Key Executives
10.1.3. Company Snapshot
10.1.4. Operating Business Segments
10.1.5. Product Portfolio
10.1.6. R&D Expenditure
10.1.7. Business Performance
10.1.8. Key Strategic Moves and Developments
10.2. Cisco Systems, Inc.
10.2.1. Company Overview
10.2.2. Key Executives
10.2.3. Company Snapshot
10.2.4. Product Portfolio
10.2.5. R&D Expenditure
10.2.6. Business Performance
10.2.7. Key Strategic Moves and Developments
10.3. International Business Machines Corporation
10.3.1. Company Overview
10.3.2. Key Executives
10.3.3. Company Snapshot
10.3.4. Operating Business Segments
10.3.5. Product Portfolio
10.3.6. R&D Expenditure
10.3.7. Business Performance
10.3.8. Key Strategic Moves and Developments
10.4. Oracle Corporation
10.4.1. Company Overview
10.4.2. Key Executives
10.4.3. Company Snapshot
10.4.4. Operating Business Segments
10.4.5. Product Portfolio
10.4.6. R&D Expenditure
10.4.7. Business Performance
10.4.8. Key Strategic Moves and Developments
10.5. Sap Se
10.5.1. Company Overview
10.5.2. Key Executives
10.5.3. Company Snapshot
10.5.4. Operating Business Segments
10.5.5. Product Portfolio
10.5.6. R&D Expenditure
10.5.7. Business Performance
10.5.8. Key Strategic Moves and Developments
10.6. Sas Institute Inc.
10.6.1. Company Overview
10.6.2. Key Executives
10.6.3. Company Snapshot
10.6.4. Product Portfolio
10.6.5. Business Performance
10.6.6. Key Strategic Moves and Developments
10.7. Sisense Inc.
10.7.1. Company Overview
10.7.2. Key Executives
10.7.3. Company Snapshot
10.7.4. Product Portfolio
10.7.5. Key Strategic Moves and Developments
10.8. Teradata Corporation
10.8.1. Company Overview
10.8.2. Key Executives
10.8.3. Company Snapshot
10.8.4. Product Portfolio
10.8.5. Key Strategic Moves and Developments
10.9. Tibco Software Inc.
10.9.1. Company Overview
10.9.2. Key Executives
10.9.3. Company Snapshot
10.9.4. Product Portfolio
10.9.5. Key Strategic Moves and Developments
10.10. Tableau Software
10.10.1. Company Overview
10.10.2. Key Executives
10.10.3. Company Snapshot
10.10.4. Product Portfolio
10.10.5. R&D Expenditure
10.10.6. Business Performance
10.10.7. Key Strategic Moves and Developments

For more information about this report visit https://www.researchandmarkets.com/r/j0jncr

Research and Markets also offers Custom Research services providing focused, comprehensive and tailored research.

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