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Global Retail Analytics Market to reach USD 16.6 Billion by 2027.

Global Retail Analytics Market Size study, by Application (Merchandising analysis, Pricing analysis, Customer analytics, Promotional analysis and planning, Yield analysis, Inventory Analysis, Others), by Component (Services, Solutions), by Business function (Finance, Marketing and sales, Human resource, Operations), by organization size(Large enterprise, small and medium enterprises), by end user(Online and offline) and Regional Forecasts 2021-2027

Product Code: ICTBC-87798998
Publish Date: 12-10-2021
Page: 200

Global Retail Analytics Market is valued approximately at USD 4.3 billion in 2020 and is anticipated to grow with a healthy growth rate of more than 21.3% over the forecast period 2021-2027. Retail analytics is the process of providing analytical data on inventory levels, supply chain movement and more. Retail analytics provides detailed customer insights along with the insights of the business and its processes of the organization with the scope and detailed need for improvement. The global Retail Analytics market is being driven by growing digitalization to enhance to customer experience and retail operation, as well as rising adoption of disruptive technolog in forecasting the future market values trends in e-commerce platforms. Furthermore, growing adoption of cloud services in retail, will provide new opportunities for the global retail analytics industry. For instance, according to statista, there has been rise in rate of smartphone penetration globally, as in year 2019 the smartphone penetration rate reached to 46.44% which increased to 54.23% in year 2020 and it is expected to reach 95.81% by year 2040. As a result, increase in smartphone penetration rate across the world. will serve as a catalyst for the Retail Analytics industry in the future. However, lack of technology adoption by unorganized retail sector and legal concern and data privacy issue, may impede market growth over the forecast period of 2021-2027.

Asia Pacific, North America, Europe, Latin America, and Rest of the World are the key region considered for the regional analysis of global retail analytics market. An early adoption of technology, and large enterprises presence makes the North America significant region across the world in terms of market share. Whereas Asia Pacific is also anticipated to exhibit the highest growth rate over the forecast period 2021-2027, due to growth of retail stores and technology development in various regions.
Major market player included in this report are:

Microsoft
IBM
Oracle
Salesforce
SAP
AWS
SAS Institute
Qlik
Manthan
Bridgei2i

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Application:
Merchandising analysis
Pricing analysis
Customer analytics
Promotional analysis and planning
Yield analysis
Inventory Analysis
Others
By Component:
Services
Solutions
By Business function:
Finance
Marketing and sales
Human resource
Operations
By Organization size:
Large enterprise
small and medium enterprises
By end Use:
Online
Offline

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 the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019
Base year – 2020
Forecast period – 2021 to 2027.

Target Audience of the Global Retail Analytics Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2027 (USD Billion)
1.2.1. Retail Analytics Market , by Region, 2019-2027 (USD Billion)
1.2.2. Retail Analytics Market , by Application, 2019-2027 (USD Billion)
1.2.3. Retail Analytics Market , by Component, 2019-2027 (USD Billion)
1.2.4. Retail Analytics Market, by business function, 2019-2027 (USD billion)
1.2.5. Retail Analytics Market, by organizational size, 2019-2027 (USD billion)
1.2.6. Retail Analytics Market, by end user, 2019-2027 (USD billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Retail Analytics Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Retail Analytics Market Dynamics
3.1. Retail Analytics Market Impact Analysis (2019-2027)
3.1.1. Market Drivers
3.1.1.1. Digitalizing to enhance customer experience and retail operations
3.1.1.2. Rising adoption of disruptive technologies to forecast future market trends
3.1.1.3. Growing number of smartphones, and increasing use of m-commerce
3.1.2. Market Restraint
3.1.2.1. Lack of technology adoption by unorganized retail sector
3.1.2.2. Legal concern and data privacy issues
3.1.3. Market Opportunities
3.1.3.1. Growing adoption of cloud services in retail
3.1.3.2. Proliferation of data analytics to understand customer data during COVID-19
Chapter 4. Global Retail Analytics 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 (2018-2027)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
Chapter 5. Global Retail Analytics Market , by Application
5.1. Market Snapshot
5.2. Global Retail Analytics Market by Application, Performance – Potential Analysis
5.3. Global Retail Analytics Market Estimates & Forecasts by Application 2018-2027 (USD Billion)
5.4. Retail Analytics Market , Sub Segment Analysis
5.4.1. Merchandising analysis
5.4.2. Pricing analysis
5.4.3. Customer analytics
5.4.4. Promotional analysis and planning
5.4.5. Yield analysis
5.4.6. Inventory Analysis
5.4.7. Others
Chapter 6. Global Retail Analytics Market , by Component
a. Market Snapshot
6.1. Global Retail Analytics Market by Component, Performance – Potential Analysis
6.2. Global Retail Analytics Market Estimates & Forecasts by Component2018-2027 (USD Billion)
6.3. Retail Analytics Market , Sub Segment Analysis
6.3.1. Services
6.3.2. Solution
Chapter 7. Global Retail Analytics Market , by Business functions
b. Market Snapshot
7.1. Global Retail Analytics Market by Business functions, Performance – Potential Analysis
7.2. Global Retail Analytics Market Estimates & Forecasts by Business function 2018-2027 (USD Billion)
7.3. Retail Analytics Market , Sub Segment Analysis
7.3.1. Finance
7.3.2. Marketing and sales
7.3.3. Human resources
7.3.4. Operations
Chapter 8. Global Retail Analytics Market , by organization size
c. Market Snapshot
8.1. Global Retail Analytics Market by Organization size, Performance – Potential Analysis
8.2. Global Retail Analytics Market Estimates & Forecasts by Organization Size 2018-2027 (USD Billion)
8.3. Retail Analytics Market , Sub Segment Analysis
8.3.1. Large enterprises
8.3.2. Small and medium enterprises
Chapter 9. Global Retail Analytics Market , by end use
d. Market Snapshot
9.1. Global Retail Analytics Market by End Use, Performance – Potential Analysis
9.2. Global Retail Analytics Market Estimates & Forecasts by End use 2018-2027 (USD Billion)
9.3. Retail Analytics Market , Sub Segment Analysis
9.3.1. Offline
9.3.2. Online
Chapter 10. Global Retail Analytics Market , Regional Analysis
10.1. Retail Analytics Market , Regional Market Snapshot
10.2. North America Retail Analytics Market
10.2.1. U.S. Retail Analytics Market
10.2.1.1. Application breakdown estimates & forecasts, 2018-2027
10.2.1.2. Component breakdown estimates & forecasts, 2018-2027
10.2.1.3. Business function breakdown estimates & forecasts, 2018-2027
10.2.1.4. Organizational size breakdown estimates & forecasts , 2018-2027
10.2.1.5. End use breakdown estimates & forecasts, 2018-2027
10.2.2. Canada Retail Analytics Market
10.3. Europe Retail Analytics Market Snapshot
10.3.1. U.K. Retail Analytics Market
10.3.2. Germany Retail Analytics Market
10.3.3. France Retail Analytics Market
10.3.4. Spain Retail Analytics Market
10.3.5. Italy Retail Analytics Market
10.3.6. Rest of Europe Retail Analytics Market
10.4. Asia-Pacific Retail Analytics Market Snapshot
10.4.1. China Retail Analytics Market
10.4.2. India Retail Analytics Market
10.4.3. Japan Retail Analytics Market
10.4.4. Australia Retail Analytics Market
10.4.5. South Korea Retail Analytics Market
10.4.6. Rest of Asia Pacific Retail Analytics Market
10.5. Latin America Retail Analytics Market Snapshot
10.5.1. Brazil Retail Analytics Market
10.5.2. Mexico Retail Analytics Market
10.6. Rest of The World Retail Analytics Market
Chapter 11. Competitive Intelligence
11.1. Top Market Strategies
11.2. Company Profiles
11.2.1. Microsoft
11.2.1.1. Key Information
11.2.1.2. Overview
11.2.1.3. Financial (Subject to Data Availability)
11.2.1.4. Product Summary
11.2.1.5. Recent Developments
11.2.2. IBM
11.2.3. Oracle
11.2.4. Salesforce
11.2.5. SAP
11.2.6. AWS
11.2.7. SAS Institute
11.2.8. Qlik
11.2.9. Manthan
11.2.10. Bridgei2i

Chapter 12. Research Process
12.1. Research Process
12.1.1. Data Mining
12.1.2. Analysis
12.1.3. Market Estimation
12.1.4. Validation
12.1.5. Publishing
12.2. Research Attributes
12.3. Research Assumption

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Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
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Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
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To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
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Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
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