Big Data Analytics in Retail Market by Component, Deployment, Enterprise Size, and Application : Global Opportunity Analysis and Industry Forecast, 2020–2027

Big Data Analytics in Retail Market by Component, Deployment, Enterprise Size, and Application : Global Opportunity Analysis and Industry Forecast, 2020–2027

  • August 2020 •
  • 274 pages •
  • Report ID: 5976978 •
  • Format: PDF
Big Data Analytics in Retail Market by Component (Software and Services), Deployment (On-premise and Cloud), Enterprise Size (Large Enterprises and Small & Medium-sized Enterprises), and Application (Sales & Marketing Analytics, Supply Chain Operations Management, Merchandising Analytics, Customer Analytics, and Others): Global Opportunity Analysis and Industry Forecast, 2020–2027

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 MARKET SEGMENTS

By Component
• Software
• Services

By Deployment
• On-premise
• Cloud

By Enterprise Size
• Large Enterprises
• Small & Medium Enterprises (SMEs)

By Application
• Sales and marketing analytics
• Supply chain operations management
• Merchandising analytics
• Customer analytics
• Others

By Region
• North America
o U.S.
o Canada
• Europe
o UK
o Germany
o France
o Rest of Europe
• Asia-Pacific
o China
o India
o Japan
o Australia
o Rest of Asia-Pacific
• LAMEA
o Latin America
o Middle East
o Africa

KEY MARKET PLAYERS
• Alteryx Inc.
• IBM
• Microsoft
• Microstrategy Inc.
• Oracle Corporation
• Qlik Technologies Inc.
• RetailNext
• SAP SE
• SAS Institute, Inc.
• Teradata