TheBig Data Analytics in Retail Market report 2019 provides a basic outline of the industry including definitions, classifications, applications and industry chain structure. The Big Data Analytics in Retail market analysis is provided for the global market including growth history, competitive background analysis, and major regions’ development status.

In the retail sector, Big Data analytics is being used at every stage of the retail process to understand the customer behavior, predict demand, and optimize pricing. Most of the Big Data applications in retail are for system-wide cost reduction, improving online and in-store customer experience, data-driven adaptive supply chains, and real-time analytics and targeting. In terms of application, big data analytics in retail sector is being segregated as merchandising & supply chain analytics, social media analytics, customer analytics & operational intelligence which is being used in small and medium enterprises & large-scale organizations.

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Key Market Trends:

Merchandising and Supply Chain Analytics Segment Expected to Hold Significant Share

– E-commerce has had an impact on the traditional brick and mortar retailers reducing their significance marking the data-driven revolution in the retail sector.
– An efficient supply chain, the optimised movement of goods from supplier to warehouse to store to customer, is very critical to every business. Therefore, big data analytics is at the core of revolutionising retail supply chain i.e tracking and tracing product flow and stock levels in real-time, leveraging customer data to predict buying patterns, even using robots to tirelessly fulfil orders in vast automated warehouses.
– In th UK, the supply chain Big Data analytics for retail is expected to grow significantly over the forecast period following manufacturing and energy sector.
– Owing to this, it is further expected that predictive analytics and machine learning AI will revolutionize the retail supply chain.

North America Region Expected to Hold the Largest Share

– The retail sector in the region is huge and is witnessing an increase in the sales. In the US, according to the National Retail Federation (NRF), retail sales are expected to rise between 3.8% and 4.4% to more than USD 3.8 trillion in 2019, citing high consumer confidence, low unemployment and rising wages.
– Besides, North America is among the leading innovators and pioneers, in terms of adoption, for Big Data analytics. The region boasts of a strong foothold of Big Data analytics vendors, which further contributes to the growth of the market. Some of them include IBM Corporation, SAS Institute, Inc., Alteryx, Inc., and Microstrategy Incorporated among others.
– With this increase in the creation and consumption of data in retail (with increased sales) that continues to grow rapidly calls for more significant investments in big data analytics hardware, software, and services.

Highlights of Big Data Analytics in Retail Market report:

  • Big Data Analytics in Retail Market Overview and Trends includes Porter’s Five Force Framework: Bargaining Power of Suppliers, Bargaining Power of Consumers, Threat of New Entrants, Threat of Substitute Products and Services, Competitive Rivalry within the Industry
  • Report includes Big Data Analytics in Retail Market Dynamics comprises of Drivers, Restraints, Opportunities
  • Big Data Analytics in Retail Market Key Vendor Analysis with (Overview, Products & Services, Strategies)
  • Competitive Landscape Analysis which includes Mergers & Acquisition Analysis, Agreements, Collaborations, and Partnerships, New Products Launches

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Big Data Analytics in Retail Market Report Contains Following Points in Table of Content:

1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study

2.1 Analysis Methodology
2.2 Research Phases


4.1 Market Overview
4.2 Introduction to Market Drivers and Restraints
4.3 Market Drivers
4.3.1 Increased Emphasis on Predictive Analytics
4.3.2 Increased Innovations in Retail Digitalization Techniques
4.4 Market Restraints
4.4.1 Complexities in Collecting and Collating the Data From Disparate Systems
4.5 Industry Attractiveness – Porter’s Five Force Analysis
4.5.1 Threat of New Entrants
4.5.2 Bargaining Power of Buyers/Consumers
4.5.3 Bargaining Power of Suppliers
4.5.4 Threat of Substitute Products
4.5.5 Intensity of Competitive Rivalry

5.1 By Application
5.1.1 Merchandising & Supply Chain Analytics
5.1.2 Social Media Analytics
5.1.3 Customer Analytics
5.1.4 Operational Intelligence
5.1.5 Other Applications
5.2 By Business Type
5.2.1 Small and Medium Enterprises
5.2.2 Large-scale Organizations
5.3 Geography
5.3.1 North America
5.3.2 Europe
5.3.3 Asia-Pacific
5.3.4 Rest of the World

6.1 Company Profiles
6.1.1 SAP SE
6.1.2 Oracle Corporation
6.1.3 Qlik Technologies Inc.
6.1.4 Zoho Corporation
6.1.5 IBM Corporation
6.1.6 Retail Next Inc.
6.1.7 Alteryx Inc.
6.1.8 Tableau Software, Inc.
6.1.9 Adobe Systems Incorporated
6.1.10 Microstrategy Inc.
6.1.11 Hitachi Vantara Corporation
6.1.12 Fuzzy Logix LLC




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(Excerpt) Read more Here | 2019-11-17 05:49:15
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