Big Data in Global Retail Market 2021
Global Big Data market is on an upward swing. The industry is maturing and is estimated to do well over the next few years. In the retail sector, the big data market will be growing as well due to the high growth rate by the retail companies in their own sector. More and more people are using big data in retail to use it to their advantage and gain competitive advantages.
This sector offers huge opportunity for firms to grow in future as there is a consistent increase in the customer base. Coupled with that, companies are more than willing to use newer products which will be much more precise and efficient to use. Despite, the high cost of implementation, the revenue earned from the insights given by big data technologies is huge and there is a visible change in revenue of the companies implementing the big data technologies.
Another factor in the industry is the safety and security of the data that is captured by all these retailers. It is expected that the privacy is not breached by them and it should not feel like that the retail company is being too intrusive and are intruding into the personal sphere of the customers. Also, they should be aware of the threat of hackers, who can gain unlawful access to the databases and get away with all the data. So, it is essential that the company should take care of the data that is stored and captured.
Overall the industry will continue to grow. As with any new sector, this industry is also ripe to grow, although a downturn in market might lead to lowering of its growth rate. It’s a mandatory technology for anyone to compete in the retail industry now, the only thing that can differ is the size of the implementation. Customer 360, Fraud detection, recommendations, inventory management, etc. are the various services offered in the retail segment by the big data companies. The number of companies providing big data services are also increasing as the demand is high in this segment.
Scope of the Global Big Data in retail Market 2021 Report
This sector offers huge opportunity for firms to grow in future as there is a consistent increase in the customer base. Coupled with that, companies are more than willing to use newer products which will be much more precise and efficient to use. Despite, the high cost of implementation, the revenue earned from the insights given by big data technologies is huge and there is a visible change in revenue of the companies implementing the big data technologies.
Another factor in the industry is the safety and security of the data that is captured by all these retailers. It is expected that the privacy is not breached by them and it should not feel like that the retail company is being too intrusive and are intruding into the personal sphere of the customers. Also, they should be aware of the threat of hackers, who can gain unlawful access to the databases and get away with all the data. So, it is essential that the company should take care of the data that is stored and captured.
Overall the industry will continue to grow. As with any new sector, this industry is also ripe to grow, although a downturn in market might lead to lowering of its growth rate. It’s a mandatory technology for anyone to compete in the retail industry now, the only thing that can differ is the size of the implementation. Customer 360, Fraud detection, recommendations, inventory management, etc. are the various services offered in the retail segment by the big data companies. The number of companies providing big data services are also increasing as the demand is high in this segment.
Scope of the Global Big Data in retail Market 2021 Report
- This report provides a detailed view of the Global Big Data in retail market scenario.
- This report identifies the need for focusing on Big Data in retail Market
- This report provides detailed information on Global Big Data in retail market with growth forecasts up to 2021.
- This report also focuses on developing a better understanding of the current state of the Big Data in retail market Technology.
- The report identifies the growth drivers and inhibitors for the global Big Data in retail market.
- This report profiles 4 global players related to the Big Data in retail market.
- This report provides future trends for the global Big Data in retail market.
- This report analyses some case studies related to the Big Data in retail market.
- This report also looks at the market opportunities for Big Data in retail market.
- This report also provides recommendations for Big Data Users and service providers in the global big data in retail market.
1. EXECUTIVE SUMMARY
Scope of the Global Big Data in retail Market 2021 Report
Research Methodology
2. NEED FOR BIG DATA IN RETAIL INDUSTRY
3. BIG DATA IN RETAIL VALUE CHAIN
4. MARKET SEGMENTS & FORECASTS FOR GLOBAL BIG DATA IN RETAIL MARKET
4.1 Overall Forecast for Global Big Data Market till 2021
4.2 Overall Forecast for Global Big Data in Retail market till 2021
4.3 Big Data in Retail Market Forecast Geography Wise
5.GROWTH DRIVERS & INHIBITORS FOR BIG DATA IN RETAIL INDUSTRY
5.1 Growth Drivers
5.2 Growth Inhibitors
6. PROFILE OF KEY PLAYERS IN GLOBAL BIG DATA IN RETAIL MARKET
6.1 Splunk Inc.
6.1.1 Company Profile
6.1.2 Splunk Inc. in Global Big Data Retail Industry Value Chain
6.1.3 Financial Performance of Splunk Inc.
6.1.4 Business Strategy
6.1.4.1 Product Level Business Strategy
6.1.4.2 Service Level Business Strategy
6.1.5 SWOT Analysis for Splunk Inc.
6.1.6 Key Customers
6.2 Mu Sigma Inc.
6.2.1 Company Profile
6.2.2 Mu Sigma in Global Big Data Retail Industry Value Chain
6.2.3 Financial Performance of Mu Sigma Inc.
6.2.4 Business Strategy
6.2.4.1 Product Level Business Strategy
6.2.4.2 Service Level Business Strategy
6.2.5 SWOT Analysis for MuSigma
6.2.6 Key Customers
6.3 SAS
6.3.1 Company Profile
6.3.2 SAS in Global Big Data in retail Industry
6.3.3 Financial Performance of SAS
6.3.4 Business Strategy
6.3.4.1 Product Level Business Strategy
6.3.4.2 Service Level Business Strategy
6.3.5 SWOT Analysis for SAS
6.4. Retail Next
6.4.1. Company Profile
6.4.2 Retail Next in Global Big Data in Retail Market Value Chain
6.4.3 Financial Performance of Retail Next
6.4.4 Business Strategy
6.4.4.1 Product Level Business Strategy
6.4.4.2 Service Level Business Strategy
6.4.5 SWOT Analysis for Retail Next
6.4.6 Key Customers
7. CASE STUDY
8. ANALYSIS MODELS
8.1 PESTLE Analysis
8.2 Porter’s Five Forces
8.3 SWOT Analysis
9. MARKET OPPORTUNITY OF BIG DATA ANALYTICS IN RETAIL
10. STRATEGIC RECOMMENDATIONS
10.1 For Retail Firms
10.2 For Big Data Service Providers
Scope of the Global Big Data in retail Market 2021 Report
Research Methodology
2. NEED FOR BIG DATA IN RETAIL INDUSTRY
3. BIG DATA IN RETAIL VALUE CHAIN
4. MARKET SEGMENTS & FORECASTS FOR GLOBAL BIG DATA IN RETAIL MARKET
4.1 Overall Forecast for Global Big Data Market till 2021
4.2 Overall Forecast for Global Big Data in Retail market till 2021
4.3 Big Data in Retail Market Forecast Geography Wise
5.GROWTH DRIVERS & INHIBITORS FOR BIG DATA IN RETAIL INDUSTRY
5.1 Growth Drivers
5.2 Growth Inhibitors
6. PROFILE OF KEY PLAYERS IN GLOBAL BIG DATA IN RETAIL MARKET
6.1 Splunk Inc.
6.1.1 Company Profile
6.1.2 Splunk Inc. in Global Big Data Retail Industry Value Chain
6.1.3 Financial Performance of Splunk Inc.
6.1.4 Business Strategy
6.1.4.1 Product Level Business Strategy
6.1.4.2 Service Level Business Strategy
6.1.5 SWOT Analysis for Splunk Inc.
6.1.6 Key Customers
6.2 Mu Sigma Inc.
6.2.1 Company Profile
6.2.2 Mu Sigma in Global Big Data Retail Industry Value Chain
6.2.3 Financial Performance of Mu Sigma Inc.
6.2.4 Business Strategy
6.2.4.1 Product Level Business Strategy
6.2.4.2 Service Level Business Strategy
6.2.5 SWOT Analysis for MuSigma
6.2.6 Key Customers
6.3 SAS
6.3.1 Company Profile
6.3.2 SAS in Global Big Data in retail Industry
6.3.3 Financial Performance of SAS
6.3.4 Business Strategy
6.3.4.1 Product Level Business Strategy
6.3.4.2 Service Level Business Strategy
6.3.5 SWOT Analysis for SAS
6.4. Retail Next
6.4.1. Company Profile
6.4.2 Retail Next in Global Big Data in Retail Market Value Chain
6.4.3 Financial Performance of Retail Next
6.4.4 Business Strategy
6.4.4.1 Product Level Business Strategy
6.4.4.2 Service Level Business Strategy
6.4.5 SWOT Analysis for Retail Next
6.4.6 Key Customers
7. CASE STUDY
8. ANALYSIS MODELS
8.1 PESTLE Analysis
8.2 Porter’s Five Forces
8.3 SWOT Analysis
9. MARKET OPPORTUNITY OF BIG DATA ANALYTICS IN RETAIL
10. STRATEGIC RECOMMENDATIONS
10.1 For Retail Firms
10.2 For Big Data Service Providers
LIST OF EXHIBITS
Notes
Company Information
Exhibit 3.1 Big Data in Retail Value Chain
Exhibit 4.1 Global Big Data Market Forecast till 2021
Exhibit 4.2 Global Big Data in Retail Forecast till 2021
Exhibit 4.3.1 Global Big Data in Retail Market Forecast Geography wise
Exhibit 4.3.2 Geography wise CAGR
Exhibit 4.3.3 North American Market Growth Forecast till 2021
Exhibit 4.3.4 South American Market Growth Forecast till 2021
Exhibit 4.3.5 Middle East & Africa Market Growth Forecast till 2021
Exhibit 4.3.6 European Market Growth Forecast till 2021
Exhibit 4.3.7 Asia Pacific Market Growth Forecast till 2021
Exhibit 5.1 Growth Drivers & Inhibitors for Big Data in the retail Industry.
Exhibit 6.1.1 Company Profile – Splunk Inc.
Exhibit 6.1.2 Contact Details – Splunk Inc.
Exhibit 6.1.3 Splunk Inc. in Global Big data in retail Value Chain
Exhibit 6.1.4 Splunk Inc. Revenue from 2011-12 to 2015-16
Exhibit 6.1.5 Year-wise Splunk Inc. Revenue Growth from 2011-12 to 2015-16
Exhibit 6.1.6 Estimated Splunk Inc. in Revenue from 2016-17 to 2020-21
Exhibit 6.1.7 Estimated Year-wise Splunk Inc. Revenue Growth from 2016-17 to 2020-21
Exhibit 6.1.8 Major Products and Services of Splunk Inc.
Exhibit 6.1.9 SWOT Analysis of SPLUNK INC.
Exhibit 6.1.10 List of Key Customers of SPLUNK INC.
Exhibit 6.2.1 Company Profile – Mu Sigma
Exhibit 6.2.2 Contact Details – Mu Sigma
Exhibit 6.2.3 Mu Sigma in Global Big Data in Retail Value Chain
Exhibit 6.2.4 Mu Sigma Revenue from 2011-12 to 2015-16
Exhibit 6.2.5 Year-wise Mu Sigma Revenue Growth from 2011-12 to 2015-16
Exhibit 6.2.6 Estimated Mu Sigma in Revenue from 2016-17 to 2020-21
Exhibit 6.2.7 Estimated Year-wise Mu Sigma Revenue Growth from 2016-17 to 2020-21
Exhibit 6.2.8 Major Products and Services of Mu Sigma
Exhibit 6.2.9 SWOT Analysis of Mu Sigma
Exhibit 6.2.10 List of Key Customers of Mu Sigma
Exhibit 6.3.1 Company Profile – SAS
Exhibit 6.3.2 Contact Details – SAS
Exhibit 6.3.3 SAS in Global Big Data in Retail Value Chain
Exhibit 6.3.4 SAS Revenue from 2011-12 to 2015-16
Exhibit 6.3.5 Year-wise SAS Revenue Growth from 2011-12 to 2015-16
Exhibit 6.3.6 Estimated SAS Revenue from 2016-17 to 2020-21
Exhibit 6.3.7 Estimated Year-wise SAS Revenue Growth from 2016-17 to 2020-21
Exhibit 6.3.8 Major Products and Services of SAS
Exhibit 6.3.9 SWOT Analysis of SAS
Exhibit 6.4.1 Company Profile – Retail Next
Exhibit 6.4.2 Contact Details – Retail Next
Exhibit 6.4.3 Retail Next in Global Big Data in Retail Value Chain
Exhibit 6.4.4 Retail Next Revenue from 2011-12 to 2015-16
Exhibit 6.4.5 Year-wise Retail Next Revenue Growth from 2011-12 to 2015-16
Exhibit 6.4.6 Estimated Retail Next Revenue from 2016-17 to 2020-21
Exhibit 6.4.7 Estimated Year-wise Retail Next Revenue Growth from 2016-17- 2020-21
Exhibit 6.4.8 Major Products and Services of Retail Next
Exhibit 6.4.9 SWOT Analysis of Retail Next
Exhibit 6.4.10 List of Key Customers of Retail Next
Exhibit 8.2 Porter’s Five Forces Model
Notes
Company Information
Exhibit 3.1 Big Data in Retail Value Chain
Exhibit 4.1 Global Big Data Market Forecast till 2021
Exhibit 4.2 Global Big Data in Retail Forecast till 2021
Exhibit 4.3.1 Global Big Data in Retail Market Forecast Geography wise
Exhibit 4.3.2 Geography wise CAGR
Exhibit 4.3.3 North American Market Growth Forecast till 2021
Exhibit 4.3.4 South American Market Growth Forecast till 2021
Exhibit 4.3.5 Middle East & Africa Market Growth Forecast till 2021
Exhibit 4.3.6 European Market Growth Forecast till 2021
Exhibit 4.3.7 Asia Pacific Market Growth Forecast till 2021
Exhibit 5.1 Growth Drivers & Inhibitors for Big Data in the retail Industry.
Exhibit 6.1.1 Company Profile – Splunk Inc.
Exhibit 6.1.2 Contact Details – Splunk Inc.
Exhibit 6.1.3 Splunk Inc. in Global Big data in retail Value Chain
Exhibit 6.1.4 Splunk Inc. Revenue from 2011-12 to 2015-16
Exhibit 6.1.5 Year-wise Splunk Inc. Revenue Growth from 2011-12 to 2015-16
Exhibit 6.1.6 Estimated Splunk Inc. in Revenue from 2016-17 to 2020-21
Exhibit 6.1.7 Estimated Year-wise Splunk Inc. Revenue Growth from 2016-17 to 2020-21
Exhibit 6.1.8 Major Products and Services of Splunk Inc.
Exhibit 6.1.9 SWOT Analysis of SPLUNK INC.
Exhibit 6.1.10 List of Key Customers of SPLUNK INC.
Exhibit 6.2.1 Company Profile – Mu Sigma
Exhibit 6.2.2 Contact Details – Mu Sigma
Exhibit 6.2.3 Mu Sigma in Global Big Data in Retail Value Chain
Exhibit 6.2.4 Mu Sigma Revenue from 2011-12 to 2015-16
Exhibit 6.2.5 Year-wise Mu Sigma Revenue Growth from 2011-12 to 2015-16
Exhibit 6.2.6 Estimated Mu Sigma in Revenue from 2016-17 to 2020-21
Exhibit 6.2.7 Estimated Year-wise Mu Sigma Revenue Growth from 2016-17 to 2020-21
Exhibit 6.2.8 Major Products and Services of Mu Sigma
Exhibit 6.2.9 SWOT Analysis of Mu Sigma
Exhibit 6.2.10 List of Key Customers of Mu Sigma
Exhibit 6.3.1 Company Profile – SAS
Exhibit 6.3.2 Contact Details – SAS
Exhibit 6.3.3 SAS in Global Big Data in Retail Value Chain
Exhibit 6.3.4 SAS Revenue from 2011-12 to 2015-16
Exhibit 6.3.5 Year-wise SAS Revenue Growth from 2011-12 to 2015-16
Exhibit 6.3.6 Estimated SAS Revenue from 2016-17 to 2020-21
Exhibit 6.3.7 Estimated Year-wise SAS Revenue Growth from 2016-17 to 2020-21
Exhibit 6.3.8 Major Products and Services of SAS
Exhibit 6.3.9 SWOT Analysis of SAS
Exhibit 6.4.1 Company Profile – Retail Next
Exhibit 6.4.2 Contact Details – Retail Next
Exhibit 6.4.3 Retail Next in Global Big Data in Retail Value Chain
Exhibit 6.4.4 Retail Next Revenue from 2011-12 to 2015-16
Exhibit 6.4.5 Year-wise Retail Next Revenue Growth from 2011-12 to 2015-16
Exhibit 6.4.6 Estimated Retail Next Revenue from 2016-17 to 2020-21
Exhibit 6.4.7 Estimated Year-wise Retail Next Revenue Growth from 2016-17- 2020-21
Exhibit 6.4.8 Major Products and Services of Retail Next
Exhibit 6.4.9 SWOT Analysis of Retail Next
Exhibit 6.4.10 List of Key Customers of Retail Next
Exhibit 8.2 Porter’s Five Forces Model
