New Research Report on “Big Data Analytics in Retail Market” presents an in-depth analysis of Big Data Analytics in Retail which includes market size, share, growth, and demand forecast until 2024 (in USD billion). The report sheds light on latest market developments and prominent trends of the market. Big Data Analytics in Retail market report includes research methodology, value chain analysis, industry analysis by the power of suppliers and consumers. Big Data Analytics in Retail market report also includes new upcoming technology of Big Data Analytics in Retail Industry that will help our clients.
Big Data Analytics in Retail Market Covers manufacturers on the basis of market status, production, consumption, and forecast details.
Scope of the Report:
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.
Big Data Analytics in Retail Market Report contents include:
- Analysis of the laboratory balance market including revenues, future growth, market outlook
- Historical data and forecast
- Regional analysis including growth estimates
- Analyzes the end user markets including growth estimates.
- Profiles on laboratory balance including products, sales/revenues, and market position
- Market structure, market drivers and restraints.
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Detailed TOC of Big Data Analytics in Retail Market Report 2020-2024:
1 INTRODUCTION
1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study
2 RESEARCH METHODOLOGY
2.1 Analysis Methodology
2.2 Research Phases
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
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 MARKET SEGMENTATION
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 COMPETITIVE LANDSCAPE
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
7 INVESTMENT ANALYSIS
8 MARKET OPPORTUNITIES AND FUTURE TRENDS
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