Global Big Data Analytics in Retail Market Size Study, by Component, by Deployment, by Organization Size, by Application and Regional Forecasts 2022-2032

Description

The global big data analytics in retail market is valued at approximately USD 9.02 billion in 2023 and is anticipated to grow with a healthy growth rate of 22.97% over the forecast period 2024-2032. Big data analytics in retail empowers retailers to detect customer behavior, discover shopping patterns and trends, improve customer service quality, and achieve better customer retention and satisfaction. The technology can be employed for customer segmentation, loyalty analysis, pricing analysis, cross-selling, supply chain management, demand forecasting, market basket analysis, and finance and fixed asset management. The adoption of big data analytics in retail has surged over time, enhancing the decision-making capabilities of organizations and providing valuable business insights. Its ability to offer various business opportunities and gain new insights has increased its popularity among end-users. Additionally, the growth of e-commerce, the rise in demand for predictive analytics, and the integration of technologies such as IoT, AI, and machine learning in big data analytics are driving the market growth.

The increase in spending on big data analytics tools is significantly driving demand for the global big data analytics in retail market. Retailers are increasingly investing in advanced analytics solutions to gain deeper insights into customer behaviour, streamline operations, and enhance decision-making. With the growing volume of data generated from various sources such as online transactions, social media, and in-store interactions, businesses are seeking sophisticated tools to analyse and leverage this information effectively. This investment helps retailers personalize marketing strategies, optimize inventory management, and improve customer experiences. Additionally, advancements in artificial intelligence (AI) and machine learning (ML) are boosting the capabilities of big data analytics tools, making them more valuable for retail applications. Consequently, increased spending on these tools is fuelling robust growth in the global big data analytics in retail market. However, issues in collecting data from disparate systems and presence of free & open-source VFX software can restrain growth of the market during the forecast period 2024-2032.

The key region in the Global Big Data Analytics in Retail Market includes North America, Europe, Asia Pacific, Latin America and Middle East & Africa. In 2023, North America dominates the market in terms of revenue. the region's advanced technological infrastructure and high adoption rates of data-driven strategies among retailers. The presence of leading tech companies and big data solution providers fuels innovation and development of sophisticated analytics tools. Asia-Pacific expected to witness highest CAGR during the forecast period 2024-2032. This is due to its adoption of cloud-enabled big data analytics in retail software witnessing significant growth. Factors such as fast internet connectivity, the proliferation of smartphones, the rise of e-commerce, changing customer purchase patterns, and growing competition among retail vendors contribute to the market expansion in this region. Furthermore, many retail analytics vendors from North America are expanding their presence in Asia-Pacific, creating lucrative opportunities for the market.

Major market players included in this report are:

Adobe
IBM Corporation
Microsoft Corporation
Oracle Corporation
SAP SE
SAS Institute Inc.
Salesforce.com, Inc.
Teradata Corporation
Qlik Technologies Inc.
TIBCO Software Inc.

The detailed segments and sub-segment of the market are explained below:

By Component

Software
Services

By Deployment

On-Premise
Cloud

By Organization Size

Large Enterprise
Small & Medium Enterprise

By Application

Sales & Marketing Analytics
Supply Chain Operations Management
Merchandising Analytics
Customer Analytics
Others

By Region:

North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of Latin America
Middle East & Africa
Saudi Arabia
South Africa
RoMEA

Years considered for the study are as follows:

Historical year - 2022
Base year - 2023
Forecast period - 2024 to 2032

Key Takeaways:

Market Estimates & Forecast for 10 years from 2022 to 2032.
Annualized revenues and regional level analysis for each market segment.
Detailed analysis of geographical landscape with Country level analysis of major regions.
Competitive landscape with information on major players in the market.
Analysis of key business strategies and recommendations on future market approach.
Analysis of competitive structure of the market.
Demand side and supply side analysis of the market.

Chapter 1. Global Big Data Analytics in Retail Market Executive Summary

1.1. Global Big Data Analytics in Retail Market Size & Forecast (2022-2032)
1.2. Regional Summary
1.3. Segmental Summary
- 1.3.1. By Component
- 1.3.2. By Deployment
- 1.3.3. By Organization Size
- 1.3.4. By Application
1.4. Key Trends
1.5. Recession Impact
1.6. Analyst Recommendation & Conclusion

Chapter 2. Global Big Data Analytics in Retail Market Definition and Research Assumptions

2.1. Research Objective
2.2. Market Definition
2.3. Research Assumptions
- 2.3.1. Inclusion & Exclusion
- 2.3.2. Limitations
- 2.3.3. Supply Side Analysis
  - 2.3.3.1. Availability
  - 2.3.3.2. Infrastructure
  - 2.3.3.3. Regulatory Environment
  - 2.3.3.4. Market Competition
  - 2.3.3.5. Economic Viability (Consumer's Perspective)
- 2.3.4. Demand Side Analysis
  - 2.3.4.1. Regulatory frameworks
  - 2.3.4.2. Technological Advancements
  - 2.3.4.3. Environmental Considerations
  - 2.3.4.4. Consumer Awareness & Acceptance
2.4. Estimation Methodology
2.5. Years Considered for the Study
2.6. Currency Conversion Rates

Chapter 3. Global Big Data Analytics in Retail Market Dynamics

3.1. Market Drivers
- 3.1.1. Increase in spending on big data analytics tools
- 3.1.2. Growth of e-commerce sector
- 3.1.3. Rise in demand for high-quality content
3.2. Market Challenges
- 3.2.1. Issues in collecting and collating data from disparate systems
- 3.2.2. Presence of free & open-source VFX software
3.3. Market Opportunities
- 3.3.1. Integration of advanced technologies such as VR & AI
- 3.3.2. Increased spending on VFX in emerging markets

Chapter 4. Global Big Data Analytics in Retail Market Industry Analysis

4.1. Porter's 5 Force Model
- 4.1.1. Bargaining Power of Suppliers
- 4.1.2. Bargaining Power of Buyers
- 4.1.3. Threat of New Entrants
- 4.1.4. Threat of Substitutes
- 4.1.5. Competitive Rivalry
- 4.1.6. Futuristic Approach to Porter's 5 Force Model
- 4.1.7. Porter's 5 Force Impact Analysis
4.2. PESTEL Analysis
- 4.2.1. Political
- 4.2.2. Economical
- 4.2.3. Social
- 4.2.4. Technological
- 4.2.5. Environmental
- 4.2.6. Legal
4.3. Top Investment Opportunity
4.4. Top Winning Strategies
4.5. Disruptive Trends
4.6. Industry Expert Perspective
4.7. Analyst Recommendation & Conclusion

Chapter 5. Global Big Data Analytics in Retail Market Size & Forecasts by Component 2022-2032

5.1. Segment Dashboard
5.2. Global Big Data Analytics in Retail Market: Component Revenue Trend Analysis, 2022 & 2032 (USD Billion)
- 5.2.1. Software
- 5.2.2. Services

Chapter 6. Global Big Data Analytics in Retail Market Size & Forecasts by Deployment 2022-2032

6.1. Segment Dashboard
6.2. Global Big Data Analytics in Retail Market: Deployment Revenue Trend Analysis, 2022 & 2032 (USD Billion)
- 6.2.1. On-Premise
- 6.2.2. Cloud

Chapter 7. Global Big Data Analytics in Retail Market Size & Forecasts by Organization Size 2022-2032

7.1. Segment Dashboard
7.2. Global Big Data Analytics in Retail Market: Organization Size Revenue Trend Analysis, 2022 & 2032 (USD Billion)
- 7.2.1. Large Enterprise
- 7.2.2. Small & Medium Enterprise

Chapter 8. Global Big Data Analytics in Retail Market Size & Forecasts by Application 2022-2032

8.1. Segment Dashboard
8.2. Global Big Data Analytics in Retail Market: Application Revenue Trend Analysis, 2022 & 2032 (USD Billion)
- 8.2.1. Sales & Marketing Analytics
- 8.2.2. Supply Chain Operations Management
- 8.2.3. Merchandising Analytics
- 8.2.4. Customer Analytics
- 8.2.5. Others

Chapter 9. Global Big Data Analytics in Retail Market Size & Forecasts by Region 2022-2032

9.1. North America Big Data Analytics in Retail Market
- 9.1.1. U.S. Big Data Analytics in Retail Market
  - 9.1.1.1. Component breakdown size & forecasts, 2022-2032
  - 9.1.1.2. Deployment breakdown size & forecasts, 2022-2032
  - 9.1.1.3. Organization Size breakdown size & forecasts, 2022-2032
  - 9.1.1.4. Application breakdown size & forecasts, 2022-2032
- 9.1.2. Canada Big Data Analytics in Retail Market
9.2. Europe Big Data Analytics in Retail Market
- 9.2.1. U.K. Big Data Analytics in Retail Market
- 9.2.2. Germany Big Data Analytics in Retail Market
- 9.2.3. France Big Data Analytics in Retail Market
- 9.2.4. Spain Big Data Analytics in Retail Market
- 9.2.5. Italy Big Data Analytics in Retail Market
- 9.2.6. Rest of Europe Big Data Analytics in Retail Market
9.3. Asia-Pacific Big Data Analytics in Retail Market
- 9.3.1. China Big Data Analytics in Retail Market
- 9.3.2. India Big Data Analytics in Retail Market
- 9.3.3. Japan Big Data Analytics in Retail Market
- 9.3.4. Australia Big Data Analytics in Retail Market
- 9.3.5. South Korea Big Data Analytics in Retail Market
- 9.3.6. Rest of Asia Pacific Big Data Analytics in Retail Market
9.4. Latin America Big Data Analytics in Retail Market
- 9.4.1. Brazil Big Data Analytics in Retail Market
- 9.4.2. Mexico Big Data Analytics in Retail Market
- 9.4.3. Rest of Latin America Big Data Analytics in Retail Market
9.5. Middle East & Africa Big Data Analytics in Retail Market
- 9.5.1. Saudi Arabia Big Data Analytics in Retail Market
- 9.5.2. South Africa Big Data Analytics in Retail Market
- 9.5.3. Rest of Middle East & Africa Big Data Analytics in Retail Market

Chapter 10. Competitive Intelligence

10.1. Key Company SWOT Analysis
10.2. Top Market Strategies
10.3. Company Profiles
- 10.3.1. Oracle Corporation
  - 10.3.1.1. Key Information
  - 10.3.1.2. Overview
  - 10.3.1.3. Financial (Subject to Data Availability)
  - 10.3.1.4. Product Summary
  - 10.3.1.5. Market Strategies
- 10.3.2. SAP SE
- 10.3.3. Salesforce.com, Inc.
- 10.3.4. Teradata Corporation
- 10.3.5. Qlik Technologies Inc.
- 10.3.6. TIBCO Software Inc.
- 10.3.7. Adobe
- 10.3.8. IBM Corporation
- 10.3.9. Microsoft Corporation
- 10.3.10. SAS Institute Inc.

Chapter 11. Research Process

11.1. Research Process
- 11.1.1. Data Mining
- 11.1.2. Analysis
- 11.1.3. Market Estimation
- 11.1.4. Validation
- 11.1.5. Publishing
11.2. Research Attributes