Retail Analytics Market by Product Type, End-Users, and Geography (North America, Europe, Asia Pacific, Latin America, and the Middle East and Africa): Global Industry Analysis, Size, Share, Growth, Trends, and Forecast, 2023-2030

Description

Persistence Market Research has recently conducted an in-depth analysis of the Retail Analytics Market, providing a comprehensive report on the global landscape. This report offers key insights into market dynamics, trends, opportunities, and challenges, offering a detailed overview of the market structure. The research publication presents exclusive data and statistics, projecting the anticipated growth trajectory of the Retail Analytics Market from 2023 to 2030.

The retail analytics market is projected to grow steadily, with a compound annual growth rate (CAGR) of 10.9%. Starting from a value of US$17.4 billion in 2023, it is expected to reach US$36 billion by the conclusion of 2030.

Key Insights:

Retail Analytics Market Size (2023E): US$17.4 Bn

Projected Market Value (2030F): US$36.0 Bn

Global Market Growth Rate (CAGR 2023 to 2030): 10.9%

Historical Market Growth Rate (CAGR 2018 to 2022): 5.8%

Retail Analytics Market - Report Scope

Retail analytics involves systematically analyzing data generated within the retail sector to derive actionable insights that enhance decision-making quality. This process employs advanced analytics tools to analyze consumer behavior, refine inventory management, and boost operational efficiency. By leveraging data from various sources such as customer demographics, point-of-sale transactions, and online interactions, retailers gain a deeper understanding of market trends, consumer preferences, and performance metrics. Embracing a data-driven approach enables businesses to optimize decision-making, streamline workflows, and deliver personalized shopping experiences. The global retail analytics market is fueled by several factors. Firstly, the surge in e-commerce has resulted in vast data volumes, compelling retailers to leverage analytics for competitive advantage. Additionally, to meet the growing demand for tailored customer experiences, analytics tools are used to understand and anticipate consumer preferences. Furthermore, the necessity for efficient inventory management and supply chain optimization has driven the adoption of analytics solutions to cut costs and enhance overall efficiency. Retailers increasingly recognize the pivotal role of data-driven insights in gaining a competitive edge. As a result, the retail analytics market is poised for steady growth, driven by the pursuit of operational excellence and customer-centric strategies.

Market Growth Drivers

The rapid shift to e-commerce is driving the global retail analytics market forward, fueled by the immense volume of data generated within the digital retail landscape. As consumers increasingly turn to online shopping, retailers are inundated with diverse data from various digital touchpoints. This wealth of information, including browsing patterns, transaction histories, and engagement metrics, forms a valuable repository that, when effectively utilized, becomes a strategic asset for businesses. The surge in e-commerce transactions has led to widespread adoption of retail analytics tools, as merchants seek to extract meaningful insights from this data deluge. The retail landscape has been fundamentally reshaped by the exponential growth of e-commerce platforms, necessitating sophisticated approaches to data analysis for maintaining a competitive edge. Retailers are leveraging advanced analytics tools to interpret consumer behavior, preferences, and digital trends. By meticulously analyzing online interactions, shopping trends, and customer feedback, organizations can tailor their strategies to meet the evolving needs of their customers.

E-commerce analytics empower retailers to optimize their online platforms, enhance user experiences, and craft targeted marketing initiatives based on data-driven insights. This not only fosters customer loyalty but also enables agile responses to market changes. With the continual expansion of the digital retail sphere, analytics plays an increasingly vital role in unraveling the complexities of e-commerce. Consequently, analytics stands out as a pivotal factor driving the growth of the global retail analytics market.

Market Restraints

The global Retail Analytics Market faces significant challenges, including concerns surrounding data privacy and security. As the retail sector increasingly relies on data analytics to understand consumer preferences and behavior, safeguarding sensitive personal information becomes paramount. Following prominent data breaches and privacy incidents, consumers are becoming more vigilant about the confidentiality and protection of their data. This heightened awareness has prompted regulatory bodies to enact stringent data protection laws such as the GDPR in Europe, along with similar regulations in other regions. Another major hurdle is the complex integration process due to the diverse data sources within the retail ecosystem. Retailers gather data from various channels including supply chain operations, in-store transactions, online purchases, and social media interactions. However, harmonizing and integrating this disparate data into a cohesive format for analytics poses a significant challenge. Issues related to data sources, formats, and structures present formidable obstacles for retailers striving to derive meaningful insights.

Opportunities

The global retail analytics market is experiencing significant growth opportunities due to the emergence and integration of Artificial Intelligence (AI) and machine learning (ML) technologies. Combining AI and ML functionalities with retail analytics opens up a wide range of possibilities for retailers seeking to enhance their decision-making processes. These advanced technologies offer unparalleled capabilities for analyzing vast datasets in real-time, enabling retailers to gain deep insights into consumer behavior, market trends, and operational efficiency. The adoption of AI in retail analytics empowers organizations to accurately predict consumer preferences, leading to the development of tailored marketing strategies and personalized customer experiences. Machine learning algorithms allow retailers to forecast demand patterns, optimize pricing strategies, and dynamically adjust inventory levels. Moreover, AI facilitates understanding of individual consumer journeys, enabling targeted recommendations and promotions. This not only enhances customer satisfaction but also positively impacts sales performance and cultivates customer loyalty. The application of these technologies extends beyond the digital realm; AI-driven analytics can improve in-store experiences, optimize product placement, and streamline inventory management processes.

Key Questions Answered in Report::

What are the primary factors driving the growth of the retail analytics market?
What role do e-commerce and digital retail play in shaping the demand for retail analytics solutions?
How do concerns regarding data privacy and security impact the adoption of retail analytics?
What are the challenges associated with integrating diverse data sources for retail analytics purposes?
How are Artificial Intelligence (AI) and Machine Learning (ML) technologies transforming the retail analytics landscape?

Competitive Intelligence and Business Strategy

Market leaders in retail analytics, such as Salesforce.com, Inc., IBM Corporation, Oracle Corporation, SAP SE, and Microsoft Corporation, are implementing strategic initiatives on a global scale to maintain and expand their market share. Central to their strategy is a steadfast commitment to innovation and the development of cutting-edge analytics solutions. These companies dedicate substantial resources to research and development, ensuring that their analytics platforms incorporate advanced functionalities such as Machine Learning (ML) and Artificial Intelligence (AI). Moreover, these industry giants recognize the unique needs of the retail sector and tailor their solutions to effectively address the evolving challenges faced by retailers. This involves creating comprehensive analytics platforms that cover various retail operations including supply chain management, customer management, merchandising, store operations, and strategic planning. By offering integrated solutions, these competitors aim to position themselves as the go-to choice for retailers seeking comprehensive analytics tools.

Key Companies Profiled
Microsoft
IBM
AWS
Oracle
Salesforce
Qlik
HCL
Fujitsu
Oracle
SAS Institute

Retail Analytics Market Segmentation

By Solution:
Software
Services
Training & Consulting
Integration & Deployment
Managed Services
By Deployment Mode:
On-Premise
Cloud-Based
By Enterprise Size:

Small Offices (1-9 employees)

Small Enterprises (10-99 employees)

Medium-sized Enterprise (100-499 employees)

Large Enterprises (500-999 employees)

Very Large Enterprises (1,000+ employees)

By Function:
Customer Management
Merchandising
Store Operations
Supply Chain
Strategy & Planning
By Region:
North America
Europe
East Asia
South Asia & Oceania
Latin America
Middle East & Africa

Product Code: PMRREP33658

1. Executive Summary

1.1. Global Retail Analytics Market Snapshot, 2023 and 2030
1.2. Market Opportunity Assessment, 2023 - 2030, US$ Mn
1.3. Key Market Trends
1.4. Future Market Projections
1.5. Premium Market Insights
1.6. Industry Developments and Key Market Events
1.7. PMR Analysis and Recommendations

2. Market Overview

2.1. Market Scope and Definition
2.2. Market Dynamics
- 2.2.1. Drivers
- 2.2.2. Restraints
- 2.2.3. Opportunity
- 2.2.4. Challenges
- 2.2.5. Key Trends
2.3. Solution Lifecycle Analysis
2.4. Retail Analytics Market: Value Chain
- 2.4.1. List of Raw Material Supplier
- 2.4.2. List of Manufacturers
- 2.4.3. List of Distributors
- 2.4.4. List of Applications
- 2.4.5. Profitability Analysis
2.5. Porter Five Force's Analysis
2.6. Geopolitical Tensions: Market Impact
2.7. Macro-Economic Factors
- 2.7.1. Global Sectorial Outlook
- 2.7.2. Global GDP Growth Outlook
- 2.7.3. Global Parent Market Overview
2.8. Forecast Factors - Relevance and Impact
2.9. Regulatory and Deployment Mode Landscape

3. Global Retail Analytics Market Outlook: Historical (2018 - 2022) and Forecast (2023 - 2030)

3.1. Key Highlights
- 3.1.1. Market Volume (Units) Projections
- 3.1.2. Market Size and Y-o-Y Growth
- 3.1.3. Absolute $ Opportunity
3.2. Market Size (US$ Mn) Analysis and Forecast
- 3.2.1. Historical Market Size Analysis, 2013-2016
- 3.2.2. Current Market Size Forecast, 2018-2026
3.3. Global Retail Analytics Market Outlook: Solution
- 3.3.1. Introduction / Key Findings
- 3.3.2. Historical Market Size (US$ Mn) and Volume (Units) Analysis By Solution, 2018 - 2022
- 3.3.3. Current Market Size (US$ Mn) and Volume (Units) Forecast By Solution, 2023 - 2030
  - 3.3.3.1. Software
  - 3.3.3.2. Enterprise Sizes
    - 3.3.3.2.1. Training & Consulting
    - 3.3.3.2.2. Integration & Deployment
    - 3.3.3.2.3. Managed Enterprise Sizes
3.4. Market Attractiveness Analysis: Solution
3.5. Global Retail Analytics Market Outlook: Deployment Mode
- 3.5.1. Introduction / Key Findings
- 3.5.2. Historical Market Size (US$ Mn) and Volume (Units) Analysis By Deployment Mode, 2018 - 2022
- 3.5.3. Current Market Size (US$ Mn) and Volume (Units) Forecast By Deployment Mode, 2023 - 2030
  - 3.5.3.1. On-Premise
  - 3.5.3.2. Cloud-Based
3.6. Market Attractiveness Analysis: Deployment Mode
3.7. Global Retail Analytics Market Outlook: Enterprise Size
- 3.7.1. Introduction / Key Findings
- 3.7.2. Historical Market Size (US$ Mn) and Volume (Units) Analysis By Enterprise Size, 2018 - 2022
- 3.7.3. Current Market Size (US$ Mn) and Volume (Units) Forecast By Enterprise Size, 2023 - 2030
  - 3.7.3.1. Small Offices (1-9 employees)
  - 3.7.3.2. Small Enterprises (10-99 employees)
  - 3.7.3.3. Medium-sized Enterprise (100-499 employees)
  - 3.7.3.4. Large Enterprises (500-999 employees)
  - 3.7.3.5. Very Large Enterprises (1,000+ employees)
3.8. Market Attractiveness Analysis: Enterprise Size
3.9. Global Retail Analytics Market Outlook: Function
- 3.9.1. Introduction / Key Findings
- 3.9.2. Historical Market Size (US$ Mn) and Volume (Units) Analysis By Function, 2018 - 2022
- 3.9.3. Current Market Size (US$ Mn) and Volume (Units) Forecast By Function, 2023 - 2030
  - 3.9.3.1. Customer Management
  - 3.9.3.2. Merchandising
  - 3.9.3.3. Store Operations
  - 3.9.3.4. Supply Chain
  - 3.9.3.5. Strategy & Planning
3.10. Market Attractiveness Analysis: Function

4. Global Retail Analytics Market Outlook: Region

4.1. Key Highlights
4.2. Historical Market Size (US$ Mn) and Volume (Units) Analysis By Region, 2018 - 2022
4.3. Current Market Size (US$ Mn) and Volume (Units) Forecast By Region, 2023 - 2030
- 4.3.1. North America
- 4.3.2. Europe
- 4.3.3. East Asia
- 4.3.4. South Asia and Oceania
- 4.3.5. Latin America
- 4.3.6. Middle East & Africa (MEA)
4.4. Market Attractiveness Analysis: Region

5. North America Retail Analytics Market Outlook: Historical (2018 - 2022) and Forecast (2023 - 2030)

5.1. Key Highlights
5.2. Pricing Analysis
5.3. Historical Market Size (US$ Mn) and Volume (Units) Analysis By Market, 2018 - 2022
- 5.3.1. By Country
- 5.3.2. By Solution
- 5.3.3. By Deployment Mode
- 5.3.4. By Enterprise Size
- 5.3.5. By Function
5.4. Current Market Size (US$ Mn) and Volume (Units) Forecast By Country, 2023 - 2030
- 5.4.1. U.S.
- 5.4.2. Canada
5.5. Current Market Size (US$ Mn) and Volume (Units) Forecast By Solution, 2023 - 2030
- 5.5.1. Software
- 5.5.2. Services
  - 5.5.2.1. Training & Consulting
  - 5.5.2.2. Integration & Deployment
  - 5.5.2.3. Managed Services
5.6. Current Market Size (US$ Mn) and Volume (Units) Forecast By Deployment Mode, 2023 - 2030
- 5.6.1. On-Premise
- 5.6.2. Cloud-Based
5.7. Current Market Size (US$ Mn) and Volume (Units) Forecast By Enterprise Size, 2023 - 2030
- 5.7.1. Small Offices (1-9 employees)
- 5.7.2. Small Enterprises (10-99 employees)
- 5.7.3. Medium-sized Enterprise (100-499 employees)
- 5.7.4. Large Enterprises (500-999 employees)
- 5.7.5. Very Large Enterprises (1,000+ employees)
5.8. Current Market Size (US$ Mn) and Volume (Units) Forecast By Function, 2023 - 2030
- 5.8.1. Customer Management
- 5.8.2. Merchandising
- 5.8.3. Store Operations
- 5.8.4. Supply Chain
- 5.8.5. Strategy & Planning
5.9. Market Attractiveness Analysis

6. Europe Retail Analytics Market Outlook: Historical (2018 - 2022) and Forecast (2023 - 2030)

6.1. Key Highlights
6.2. Pricing Analysis
6.3. Historical Market Size (US$ Mn) and Volume (Units) Analysis By Market, 2018 - 2022
- 6.3.1. By Country
- 6.3.2. By Solution
- 6.3.3. By Deployment Mode
- 6.3.4. By Enterprise Size
- 6.3.5. By Function
6.4. Current Market Size (US$ Mn) and Volume (Units) Forecast By Country, 2023 - 2030
- 6.4.1. Germany
- 6.4.2. France
- 6.4.3. U.K.
- 6.4.4. Italy
- 6.4.5. Spain
- 6.4.6. Russia
- 6.4.7. Turkiye
- 6.4.8. Rest of Europe
6.5. Current Market Size (US$ Mn) and Volume (Units) Forecast By Solution, 2023 - 2030
- 6.5.1. Software
- 6.5.2. Services
  - 6.5.2.1. Training & Consulting
  - 6.5.2.2. Integration & Deployment
  - 6.5.2.3. Managed Services
6.6. Current Market Size (US$ Mn) and Volume (Units) Forecast By Deployment Mode, 2023 - 2030
- 6.6.1. On-Premise
- 6.6.2. Cloud-Based
6.7. Current Market Size (US$ Mn) and Volume (Units) Forecast By Enterprise Size, 2023 - 2030
- 6.7.1. Small Offices (1-9 employees)
- 6.7.2. Small Enterprises (10-99 employees)
- 6.7.3. Medium-sized Enterprise (100-499 employees)
- 6.7.4. Large Enterprises (500-999 employees)
- 6.7.5. Very Large Enterprises (1,000+ employees)
6.8. Current Market Size (US$ Mn) and Volume (Units) Forecast By Function, 2023 - 2030
- 6.8.1. Customer Management
- 6.8.2. Merchandising
- 6.8.3. Store Operations
- 6.8.4. Supply Chain
- 6.8.5. Strategy & Planning
6.9. Market Attractiveness Analysis

7. East Asia Retail Analytics Market Outlook: Historical (2018 - 2022) and Forecast (2023 - 2030)

7.1. Key Highlights
7.2. Pricing Analysis
7.3. Historical Market Size (US$ Mn) and Volume (Units) Analysis By Market, 2018 - 2022
- 7.3.1. By Country
- 7.3.2. By Solution
- 7.3.3. By Deployment Mode
- 7.3.4. By Enterprise Size
- 7.3.5. By Function
7.4. Current Market Size (US$ Mn) and Volume (Units) Forecast By Country, 2023 - 2030
- 7.4.1. China
- 7.4.2. Japan
- 7.4.3. South Korea
7.5. Current Market Size (US$ Mn) and Volume (Units) Forecast By Solution, 2023 - 2030
- 7.5.1. Software
- 7.5.2. Services
  - 7.5.2.1. Training & Consulting
  - 7.5.2.2. Integration & Deployment
  - 7.5.2.3. Managed Services
7.6. Current Market Size (US$ Mn) and Volume (Units) Forecast By Deployment Mode, 2023 - 2030
- 7.6.1. On-Premise
- 7.6.2. Cloud-Based
7.7. Current Market Size (US$ Mn) and Volume (Units) Forecast By Enterprise Size, 2023 - 2030
- 7.7.1. Small Offices (1-9 employees)
- 7.7.2. Small Enterprises (10-99 employees)
- 7.7.3. Medium-sized Enterprise (100-499 employees)
- 7.7.4. Large Enterprises (500-999 employees)
- 7.7.5. Very Large Enterprises (1,000+ employees)
7.8. Current Market Size (US$ Mn) and Volume (Units) Forecast By Function, 2023 - 2030
- 7.8.1. Customer Management
- 7.8.2. Merchandising
- 7.8.3. Store Operations
- 7.8.4. Supply Chain
- 7.8.5. Strategy & Planning
7.9. Market Attractiveness Analysis

8. South Asia & Oceania Retail Analytics Market Outlook: Historical (2018 - 2022) and Forecast (2023 - 2030)

8.1. Key Highlights
8.2. Pricing Analysis
8.3. Historical Market Size (US$ Mn) and Volume (Units) Analysis By Market, 2018 - 2022
- 8.3.1. By Country
- 8.3.2. By Solution
- 8.3.3. By Deployment Mode
- 8.3.4. By Enterprise Size
- 8.3.5. By Function
8.4. Current Market Size (US$ Mn) and Volume (Units) Forecast By Country, 2023 - 2030
- 8.4.1. India
- 8.4.2. Southeast Asia
- 8.4.3. ANZ
- 8.4.4. Rest of South Asia & Oceania
8.5. Current Market Size (US$ Mn) and Volume (Units) Forecast By Solution, 2023 - 2030
- 8.5.1. Software
- 8.5.2. Services
  - 8.5.2.1. Training & Consulting
  - 8.5.2.2. Integration & Deployment
  - 8.5.2.3. Managed Services
8.6. Current Market Size (US$ Mn) and Volume (Units) Forecast By Deployment Mode, 2023 - 2030
- 8.6.1. On-Premise
- 8.6.2. Cloud-Based
8.7. Current Market Size (US$ Mn) and Volume (Units) Forecast By Enterprise Size, 2023 - 2030
- 8.7.1. Small Offices (1-9 employees)
- 8.7.2. Small Enterprises (10-99 employees)
- 8.7.3. Medium-sized Enterprise (100-499 employees)
- 8.7.4. Large Enterprises (500-999 employees)
- 8.7.5. Very Large Enterprises (1,000+ employees)
8.8. Current Market Size (US$ Mn) and Volume (Units) Forecast By Function, 2023 - 2030
- 8.8.1. Customer Management
- 8.8.2. Merchandising
- 8.8.3. Store Operations
- 8.8.4. Supply Chain
- 8.8.5. Strategy & Planning
8.9. Market Attractiveness Analysis

9. Latin America Retail Analytics Market Outlook: Historical (2018 - 2022) and Forecast (2023 - 2030)

9.1. Key Highlights
9.2. Pricing Analysis
9.3. Historical Market Size (US$ Mn) and Volume (Units) Analysis By Market, 2018 - 2022
- 9.3.1. By Country
- 9.3.2. By Solution
- 9.3.3. By Deployment Mode
- 9.3.4. By Enterprise Size
- 9.3.5. By Function
9.4. Current Market Size (US$ Mn) and Volume (Units) Forecast By Country, 2023 - 2030
- 9.4.1. Brazil
- 9.4.2. Mexico
- 9.4.3. Rest of Latin America
9.5. Current Market Size (US$ Mn) and Volume (Units) Forecast By Solution, 2023 - 2030
- 9.5.1. Software
- 9.5.2. Services
  - 9.5.2.1. Training & Consulting
  - 9.5.2.2. Integration & Deployment
  - 9.5.2.3. Managed Services
9.6. Current Market Size (US$ Mn) and Volume (Units) Forecast By Deployment Mode, 2023 - 2030
- 9.6.1. On-Premise
- 9.6.2. Cloud-Based
9.7. Current Market Size (US$ Mn) and Volume (Units) Forecast By Enterprise Size, 2023 - 2030
- 9.7.1. Small Offices (1-9 employees)
- 9.7.2. Small Enterprises (10-99 employees)
- 9.7.3. Medium-sized Enterprise (100-499 employees)
- 9.7.4. Large Enterprises (500-999 employees)
- 9.7.5. Very Large Enterprises (1,000+ employees)
9.8. Current Market Size (US$ Mn) and Volume (Units) Forecast By Function, 2023 - 2030
- 9.8.1. Customer Management
- 9.8.2. Merchandising
- 9.8.3. Store Operations
- 9.8.4. Supply Chain
- 9.8.5. Strategy & Planning
9.9. Market Attractiveness Analysis

10. Middle East & Africa Retail Analytics Market Outlook: Historical (2018 - 2022) and Forecast (2023 - 2030)

10.1. Key Highlights
10.2. Pricing Analysis
10.3. Historical Market Size (US$ Mn) and Volume (Units) Analysis By Market, 2018 - 2022
- 10.3.1. By Country
- 10.3.2. By Solution
- 10.3.3. By Deployment Mode
- 10.3.4. By Enterprise Size
- 10.3.5. By Function
10.4. Current Market Size (US$ Mn) and Volume (Units) Forecast By Country, 2023 - 2030
- 10.4.1. GCC
- 10.4.2. Egypt
- 10.4.3. South Africa
- 10.4.4. Northern Africa
- 10.4.5. Rest of Middle East & Africa
10.5. Current Market Size (US$ Mn) and Volume (Units) Forecast By Solution, 2023 - 2030
- 10.5.1. Software
- 10.5.2. Services
  - 10.5.2.1. Training & Consulting
  - 10.5.2.2. Integration & Deployment
  - 10.5.2.3. Managed Services
10.6. Current Market Size (US$ Mn) and Volume (Units) Forecast By Deployment Mode, 2023 - 2030
- 10.6.1. On-Premise
- 10.6.2. Cloud-Based
10.7. Current Market Size (US$ Mn) and Volume (Units) Forecast By Enterprise Size, 2023 - 2030
- 10.7.1. Small Offices (1-9 employees)
- 10.7.2. Small Enterprises (10-99 employees)
- 10.7.3. Medium-sized Enterprise (100-499 employees)
- 10.7.4. Large Enterprises (500-999 employees)
- 10.7.5. Very Large Enterprises (1,000+ employees)
10.8. Current Market Size (US$ Mn) and Volume (Units) Forecast By Function, 2023 - 2030
- 10.8.1. Customer Management
- 10.8.2. Merchandising
- 10.8.3. Store Operations
- 10.8.4. Supply Chain
- 10.8.5. Strategy & Planning
10.9. Market Attractiveness Analysis

11. Competition Landscape

11.1. Market Share Analysis, 2022
11.2. Market Structure
- 11.2.1. Competition Intensity Mapping By Market
- 11.2.2. Competition Dashboard
- 11.2.3. Apparent Product Capacity
11.3. Company Profiles (Details - Overview, Financials, Strategy, Recent Developments)
- 11.3.1. Microsoft
  - 11.3.1.1. Overview
  - 11.3.1.2. Segments and Product
  - 11.3.1.3. Key Financials
  - 11.3.1.4. Market Developments
  - 11.3.1.5. Market Strategy
- 11.3.2. IBM
  - 11.3.2.1. Overview
  - 11.3.2.2. Segments and Product
  - 11.3.2.3. Key Financials
  - 11.3.2.4. Market Developments
  - 11.3.2.5. Market Strategy
- 11.3.3. AWS
  - 11.3.3.1. Overview
  - 11.3.3.2. Segments and Product
  - 11.3.3.3. Key Financials
  - 11.3.3.4. Market Developments
  - 11.3.3.5. Market Strategy
- 11.3.4. Oracle
  - 11.3.4.1. Overview
  - 11.3.4.2. Segments and Product
  - 11.3.4.3. Key Financials
  - 11.3.4.4. Market Developments
  - 11.3.4.5. Market Strategy
- 11.3.5. Salesforce
  - 11.3.5.1. Overview
  - 11.3.5.2. Segments and Product
  - 11.3.5.3. Key Financials
  - 11.3.5.4. Market Developments
  - 11.3.5.5. Market Strategy
- 11.3.6. Qlik
  - 11.3.6.1. Overview
  - 11.3.6.2. Segments and Product
  - 11.3.6.3. Key Financials
  - 11.3.6.4. Market Developments
  - 11.3.6.5. Market Strategy
- 11.3.7. HCL
  - 11.3.7.1. Overview
  - 11.3.7.2. Segments and Product
  - 11.3.7.3. Key Financials
  - 11.3.7.4. Market Developments
  - 11.3.7.5. Market Strategy
- 11.3.8. Fujitsu
  - 11.3.8.1. Overview
  - 11.3.8.2. Segments and Product
  - 11.3.8.3. Key Financials
  - 11.3.8.4. Market Developments
  - 11.3.8.5. Market Strategy
- 11.3.9. Oracle
  - 11.3.9.1. Overview
  - 11.3.9.2. Segments and Product
  - 11.3.9.3. Key Financials
  - 11.3.9.4. Market Developments
  - 11.3.9.5. Market Strategy
- 11.3.10. SAS Institute
  - 11.3.10.1. Overview
  - 11.3.10.2. Segments and Product
  - 11.3.10.3. Key Financials
  - 11.3.10.4. Market Developments
  - 11.3.10.5. Market Strategy

12. Appendix

12.1. Research Methodology
12.2. Research Assumptions
12.3. Acronyms and Abbreviations