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Big Data Analytics in Retail-Global Market Insights and Sales Trends 2025
Synopsis
The global Big Data Analytics in Retail market size is expected to reach US$ 8766.1 million by 2029, growing at a CAGR of 17.0% from 2023 to 2029. The market is mainly driven by the significant applications of Big Data Analytics in Retail in various end use industries. The expanding demands from the Merchandising & In-store Analytics, Marketing & Customer Analytics, Supply Chain Analytics and Others, are propelling Big Data Analytics in Retail market. Software & Service, one of the segments analysed in this report, is projected to record % CAGR and reach US$ million by the end of the analysis period. Growth in the Platform segment is estimated at % CAGR for the next seven-year period.
Big data is a massive volume of structured and unstructured data stored on daily basis. Big data analytics technique is used to search hidden patterns, market trends, and other useful information that may help organizations to take effective business decisions.
Report Objectives
This report provides market insight on the different segments, by players, by Type, by Application. Market size and forecast (2018-2029) has been provided in the report. The primary objectives of this report are to provide 1) global market size and forecasts, growth rates, market dynamics, industry structure and developments, market situation, trends; 2) global market share and ranking by company; 3) comprehensive presentation of the global market for Big Data Analytics in Retail, with both quantitative and qualitative analysis through detailed segmentation; 4) detailed value chain analysis and review of growth factors essential for the existing market players and new entrants; 5) emerging opportunities in the market and the future impact of major drivers and restraints of the market.
Key Features of The Study:
This report provides in-depth analysis of the global Big Data Analytics in Retail market, and provides market size (US$ million) and CAGR for the forecast period (2023-2029), considering 2022 as the base year.
This report profiles key players in the global Big Data Analytics in Retail market based on the following parameters - company details (found date, headquarters, manufacturing bases), products portfolio, Big Data Analytics in Retail sales data, market share and ranking.
This report elucidates potential market opportunities across different segments and explains attractive investment proposition matrices for this market.
This report illustrates key insights about market drivers, restraints, opportunities, market trends, regional outlook.
Key companies of Big Data Analytics in Retail covered in this report include IBM, SAP, Microsoft, Oracle, SAS, Adobe, Microstrategy, Information Builders and Tableau Software, etc.
The global Big Data Analytics in Retail market report caters to various stakeholders in this industry including investors, suppliers, product players, distributors, new entrants, and financial analysts.
Market Segmentation
Company Profiles:
IBM
SAP
Microsoft
Oracle
SAS
Adobe
Microstrategy
Information Builders
Tableau Software
Qlik Technologies
RetailNext
Duozhun
Global Big Data Analytics in Retail market, by region:
North America (U.S., Canada, Mexico)
Europe (Germany, France, UK, Italy, etc.)
Asia Pacific (China, Japan, South Korea, Southeast Asia, India, etc.)
South America (Brazil, etc.)
Middle East and Africa (Turkey, GCC Countries, Africa, etc.)
Global Big Data Analytics in Retail market, Segment by Type:
Software & Service
Platform
Global Big Data Analytics in Retail market, by Application
Merchandising & In-store Analytics
Marketing & Customer Analytics
Supply Chain Analytics
Others
Core Chapters
Chapter One: Introduces the report scope of the report, executive summary of global and regional market size and CAGR for the history and forecast period (2018-2023, 2024-2029). It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter Two: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter Three: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter Four: Detailed analysis of Big Data Analytics in Retail companies’ competitive landscape, revenue, market share and ranking, latest development plan, merger, and acquisition information, etc.
Chapter Five: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product introduction, revenue, recent development, etc.
Chapter Six, Seven, Eight, Nine and Ten: North America, Europe, Asia Pacific, Latin America, Middle East & Africa, revenue by country.
Chapter Eleven: this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter Twelve: Research Finding/Conclusion
The global Big Data Analytics in Retail market size is expected to reach US$ 8766.1 million by 2029, growing at a CAGR of 17.0% from 2023 to 2029. The market is mainly driven by the significant applications of Big Data Analytics in Retail in various end use industries. The expanding demands from the Merchandising & In-store Analytics, Marketing & Customer Analytics, Supply Chain Analytics and Others, are propelling Big Data Analytics in Retail market. Software & Service, one of the segments analysed in this report, is projected to record % CAGR and reach US$ million by the end of the analysis period. Growth in the Platform segment is estimated at % CAGR for the next seven-year period.
Big data is a massive volume of structured and unstructured data stored on daily basis. Big data analytics technique is used to search hidden patterns, market trends, and other useful information that may help organizations to take effective business decisions.
Report Objectives
This report provides market insight on the different segments, by players, by Type, by Application. Market size and forecast (2018-2029) has been provided in the report. The primary objectives of this report are to provide 1) global market size and forecasts, growth rates, market dynamics, industry structure and developments, market situation, trends; 2) global market share and ranking by company; 3) comprehensive presentation of the global market for Big Data Analytics in Retail, with both quantitative and qualitative analysis through detailed segmentation; 4) detailed value chain analysis and review of growth factors essential for the existing market players and new entrants; 5) emerging opportunities in the market and the future impact of major drivers and restraints of the market.
Key Features of The Study:
This report provides in-depth analysis of the global Big Data Analytics in Retail market, and provides market size (US$ million) and CAGR for the forecast period (2023-2029), considering 2022 as the base year.
This report profiles key players in the global Big Data Analytics in Retail market based on the following parameters - company details (found date, headquarters, manufacturing bases), products portfolio, Big Data Analytics in Retail sales data, market share and ranking.
This report elucidates potential market opportunities across different segments and explains attractive investment proposition matrices for this market.
This report illustrates key insights about market drivers, restraints, opportunities, market trends, regional outlook.
Key companies of Big Data Analytics in Retail covered in this report include IBM, SAP, Microsoft, Oracle, SAS, Adobe, Microstrategy, Information Builders and Tableau Software, etc.
The global Big Data Analytics in Retail market report caters to various stakeholders in this industry including investors, suppliers, product players, distributors, new entrants, and financial analysts.
Market Segmentation
Company Profiles:
IBM
SAP
Microsoft
Oracle
SAS
Adobe
Microstrategy
Information Builders
Tableau Software
Qlik Technologies
RetailNext
Duozhun
Global Big Data Analytics in Retail market, by region:
North America (U.S., Canada, Mexico)
Europe (Germany, France, UK, Italy, etc.)
Asia Pacific (China, Japan, South Korea, Southeast Asia, India, etc.)
South America (Brazil, etc.)
Middle East and Africa (Turkey, GCC Countries, Africa, etc.)
Global Big Data Analytics in Retail market, Segment by Type:
Software & Service
Platform
Global Big Data Analytics in Retail market, by Application
Merchandising & In-store Analytics
Marketing & Customer Analytics
Supply Chain Analytics
Others
Core Chapters
Chapter One: Introduces the report scope of the report, executive summary of global and regional market size and CAGR for the history and forecast period (2018-2023, 2024-2029). It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter Two: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter Three: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter Four: Detailed analysis of Big Data Analytics in Retail companies’ competitive landscape, revenue, market share and ranking, latest development plan, merger, and acquisition information, etc.
Chapter Five: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product introduction, revenue, recent development, etc.
Chapter Six, Seven, Eight, Nine and Ten: North America, Europe, Asia Pacific, Latin America, Middle East & Africa, revenue by country.
Chapter Eleven: this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter Twelve: Research Finding/Conclusion
Index1 Market Overview of Big Data Analytics in Retail
1.1 Big Data Analytics in Retail Market Overview
1.1.1 Big Data Analytics in Retail Product Scope
1.1.2 Big Data Analytics in Retail Market Status and Outlook
1.2 Global Big Data Analytics in Retail Market Size Overview by Region 2018 VS 2022 VS 2029
1.3 Global Big Data Analytics in Retail Market Size by Region (2018-2029)
1.4 Global Big Data Analytics in Retail Historic Market Size by Region (2018-2023)
1.5 Global Big Data Analytics in Retail Market Size Forecast by Region (2024-2029)
1.6 Key Regions, Big Data Analytics in Retail Market Size (2018-2029)
1.6.1 North America Big Data Analytics in Retail Market Size (2018-2029)
1.6.2 Europe Big Data Analytics in Retail Market Size (2018-2029)
1.6.3 Asia-Pacific Big Data Analytics in Retail Market Size (2018-2029)
1.6.4 Latin America Big Data Analytics in Retail Market Size (2018-2029)
1.6.5 Middle East & Africa Big Data Analytics in Retail Market Size (2018-2029)
2 Big Data Analytics in Retail Market by Type
2.1 Introduction
2.1.1 Software & Service
2.1.2 Platform
2.2 Global Big Data Analytics in Retail Market Size by Type: 2018 VS 2022 VS 2029
2.2.1 Global Big Data Analytics in Retail Historic Market Size by Type (2018-2023)
2.2.2 Global Big Data Analytics in Retail Forecasted Market Size by Type (2024-2029)
2.3 Key Regions Market Size by Type
2.3.1 North America Big Data Analytics in Retail Revenue Breakdown by Type (2018-2029)
2.3.2 Europe Big Data Analytics in Retail Revenue Breakdown by Type (2018-2029)
2.3.3 Asia-Pacific Big Data Analytics in Retail Revenue Breakdown by Type (2018-2029)
2.3.4 Latin America Big Data Analytics in Retail Revenue Breakdown by Type (2018-2029)
2.3.5 Middle East and Africa Big Data Analytics in Retail Revenue Breakdown by Type (2018-2029)
3 Big Data Analytics in Retail Market Overview by Application
3.1 Introduction
3.1.1 Merchandising & In-store Analytics
3.1.2 Marketing & Customer Analytics
3.1.3 Supply Chain Analytics
3.1.4 Others
3.2 Global Big Data Analytics in Retail Market Size by Application: 2018 VS 2022 VS 2029
3.2.1 Global Big Data Analytics in Retail Historic Market Size by Application (2018-2023)
3.2.2 Global Big Data Analytics in Retail Forecasted Market Size by Application (2024-2029)
3.3 Key Regions Market Size by Application
3.3.1 North America Big Data Analytics in Retail Revenue Breakdown by Application (2018-2029)
3.3.2 Europe Big Data Analytics in Retail Revenue Breakdown by Application (2018-2029)
3.3.3 Asia-Pacific Big Data Analytics in Retail Revenue Breakdown by Application (2018-2029)
3.3.4 Latin America Big Data Analytics in Retail Revenue Breakdown by Application (2018-2029)
3.3.5 Middle East and Africa Big Data Analytics in Retail Revenue Breakdown by Application (2018-2029)
4 Big Data Analytics in Retail Competition Analysis by Players
4.1 Global Big Data Analytics in Retail Market Size by Players (2018-2023)
4.2 Global Top Players by Company Type (Tier 1, Tier 2 and Tier 3) & (based on the Revenue in Big Data Analytics in Retail as of 2022)
4.3 Date of Key Players Enter into Big Data Analytics in Retail Market
4.4 Global Top Players Big Data Analytics in Retail Headquarters and Area Served
4.5 Key Players Big Data Analytics in Retail Product Solution and Service
4.6 Competitive Status
4.6.1 Big Data Analytics in Retail Market Concentration Rate
4.6.2 Mergers & Acquisitions, Expansion Plans
5 Company (Top Players) Profiles
5.1 IBM
5.1.1 IBM Profile
5.1.2 IBM Main Business
5.1.3 IBM Big Data Analytics in Retail Products, Services and Solutions
5.1.4 IBM Big Data Analytics in Retail Revenue (US$ Million) & (2018-2023)
5.1.5 IBM Recent Developments
5.2 SAP
5.2.1 SAP Profile
5.2.2 SAP Main Business
5.2.3 SAP Big Data Analytics in Retail Products, Services and Solutions
5.2.4 SAP Big Data Analytics in Retail Revenue (US$ Million) & (2018-2023)
5.2.5 SAP Recent Developments
5.3 Microsoft
5.3.1 Microsoft Profile
5.3.2 Microsoft Main Business
5.3.3 Microsoft Big Data Analytics in Retail Products, Services and Solutions
5.3.4 Microsoft Big Data Analytics in Retail Revenue (US$ Million) & (2018-2023)
5.3.5 Oracle Recent Developments
5.4 Oracle
5.4.1 Oracle Profile
5.4.2 Oracle Main Business
5.4.3 Oracle Big Data Analytics in Retail Products, Services and Solutions
5.4.4 Oracle Big Data Analytics in Retail Revenue (US$ Million) & (2018-2023)
5.4.5 Oracle Recent Developments
5.5 SAS
5.5.1 SAS Profile
5.5.2 SAS Main Business
5.5.3 SAS Big Data Analytics in Retail Products, Services and Solutions
5.5.4 SAS Big Data Analytics in Retail Revenue (US$ Million) & (2018-2023)
5.5.5 SAS Recent Developments
5.6 Adobe
5.6.1 Adobe Profile
5.6.2 Adobe Main Business
5.6.3 Adobe Big Data Analytics in Retail Products, Services and Solutions
5.6.4 Adobe Big Data Analytics in Retail Revenue (US$ Million) & (2018-2023)
5.6.5 Adobe Recent Developments
5.7 Microstrategy
5.7.1 Microstrategy Profile
5.7.2 Microstrategy Main Business
5.7.3 Microstrategy Big Data Analytics in Retail Products, Services and Solutions
5.7.4 Microstrategy Big Data Analytics in Retail Revenue (US$ Million) & (2018-2023)
5.7.5 Microstrategy Recent Developments
5.8 Information Builders
5.8.1 Information Builders Profile
5.8.2 Information Builders Main Business
5.8.3 Information Builders Big Data Analytics in Retail Products, Services and Solutions
5.8.4 Information Builders Big Data Analytics in Retail Revenue (US$ Million) & (2018-2023)
5.8.5 Information Builders Recent Developments
5.9 Tableau Software
5.9.1 Tableau Software Profile
5.9.2 Tableau Software Main Business
5.9.3 Tableau Software Big Data Analytics in Retail Products, Services and Solutions
5.9.4 Tableau Software Big Data Analytics in Retail Revenue (US$ Million) & (2018-2023)
5.9.5 Tableau Software Recent Developments
5.10 Qlik Technologies
5.10.1 Qlik Technologies Profile
5.10.2 Qlik Technologies Main Business
5.10.3 Qlik Technologies Big Data Analytics in Retail Products, Services and Solutions
5.10.4 Qlik Technologies Big Data Analytics in Retail Revenue (US$ Million) & (2018-2023)
5.10.5 Qlik Technologies Recent Developments
5.11 RetailNext
5.11.1 RetailNext Profile
5.11.2 RetailNext Main Business
5.11.3 RetailNext Big Data Analytics in Retail Products, Services and Solutions
5.11.4 RetailNext Big Data Analytics in Retail Revenue (US$ Million) & (2018-2023)
5.11.5 RetailNext Recent Developments
5.12 Duozhun
5.12.1 Duozhun Profile
5.12.2 Duozhun Main Business
5.12.3 Duozhun Big Data Analytics in Retail Products, Services and Solutions
5.12.4 Duozhun Big Data Analytics in Retail Revenue (US$ Million) & (2018-2023)
5.12.5 Duozhun Recent Developments
6 North America
6.1 North America Big Data Analytics in Retail Market Size by Country (2018-2029)
6.2 U.S.
6.3 Canada
7 Europe
7.1 Europe Big Data Analytics in Retail Market Size by Country (2018-2029)
7.2 Germany
7.3 France
7.4 U.K.
7.5 Italy
7.6 Russia
7.7 Nordic Countries
7.8 Rest of Europe
8 Asia-Pacific
8.1 Asia-Pacific Big Data Analytics in Retail Market Size by Region (2018-2029)
8.2 China
8.3 Japan
8.4 South Korea
8.5 Southeast Asia
8.6 India
8.7 Australia
8.8 Rest of Asia-Pacific
9 Latin America
9.1 Latin America Big Data Analytics in Retail Market Size by Country (2018-2029)
9.2 Mexico
9.3 Brazil
9.4 Rest of Latin America
10 Middle East & Africa
10.1 Middle East & Africa Big Data Analytics in Retail Market Size by Country (2018-2029)
10.2 Turkey
10.3 Saudi Arabia
10.4 UAE
10.5 Rest of Middle East & Africa
11 Big Data Analytics in Retail Market Dynamics
11.1 Big Data Analytics in Retail Industry Trends
11.2 Big Data Analytics in Retail Market Drivers
11.3 Big Data Analytics in Retail Market Challenges
11.4 Big Data Analytics in Retail Market Restraints
12 Research Finding /Conclusion
13 Methodology and Data Source
13.1 Methodology/Research Approach
13.1.1 Research Programs/Design
13.1.2 Market Size Estimation
13.1.3 Market Breakdown and Data Triangulation
13.2 Data Source
13.2.1 Secondary Sources
13.2.2 Primary Sources
13.3 Disclaimer
13.4 Author List
Published By : QY Research
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