The Retail Analytics Market was valued at USD 8.0 Billion in 2023 and is expected to reach USD 45.4 Billion by 2032, growing at a CAGR of 21.31% from 2024-2032.
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The retail analytics market has experienced remarkable growth in recent years as the need for data-driven insights to optimize operations and improve customer experiences continues to provide the impetus for rapid growth. With data from multiple retail channels such as online transactions, store activity, and social media interaction increasing rapidly, retailers are investing in new analytics solutions to process and make sense of all this big information. The data provides retailers with deeper insight into consumer behavior, purchasing patterns, and emerging trends, allowing them to create targeted marketing campaigns, strategically design product assortments, and drive customer loyalty. Knowing what consumers want is increasingly becoming a decisive force in not only sales but also building customer loyalty.
Retail analytics is also an essential part of retail inventory management as retailers are using more and more analytics tools and solutions to track their inventory levels, and sales velocity in real-time, as well as forecast demand. Such features help maintain sufficient stock, eliminating the possibility of over/ under stock, thereby minimizing operational expenditure and enhancing efficacy. With the increasing competition in the retail industry, brands are using analytics to better understand market trends, competitor performance, and consumer sentiment, thereby gaining their competitive edge. With these insights, retailers can make better decisions, discover new opportunities, and proactively adjust to changes in consumer demand.
Several trends have facilitated market adoption over the years, with the rocket of advanced techniques such as artificial intelligence, machine learning, and the Internet of Things being some of them to drive the retail analytics market even higher. Such technologies facilitate predictive analytics, real-time data processing, and automation, which considerably improves the functionalities of retail analytical platforms. The boom of e-commerce has been another key driver of market growth, especially within online retail, which generates massive quantities of data, all of which necessitate sophisticated analytics to track sales performance, customer behavior, and the online shopper journey.
Together with this, retail analytics enables the optimization of the supply chain through insights into supplier performance, logistics efficiency, and demand forecasting. Such enables retailers to optimize operations, reduce expenditure, and improve delivery time with the end goal of getting better customer satisfaction. Given the increasing significance of data privacy and security concerns, retailers are adopting analytics to help them meet regulatory requirements. They are useful in tracking data consumption, applying security processes, creating compliance reports, minimizing legal risks, and ensuring compliance with industry standards.
Drivers
Advanced technologies like AI and ML enable predictive analytics, enhancing the capabilities of retail analytics platforms.
AI and ML are revolutionizing the Retail Analytics Market through better predictions with analytics platforms. This goes beyond traditional methods of data analysis, but with the help of these kinds of technologies, retailers are equipped with tools that can detect patterns, trends, and insights that were once challenging to discover. Retailers can analyze vast amounts of data in real-time, allowing them to anticipate customer behavior, analyze demand, and effectively manage inventory with the help of AI and ML. Through AI-powered predictive analytics, previous sales information, seasonal trends, and customer preferences can all be analyzed to obtain accurate demand predictions. This enables retailers to make better, informed planning decisions, stocking the right products in the right quantities at the right time to minimize over-stocking and stockout risks. Machine learning algorithms learn from new data, improving the predictions rapidly over time, which empowers retailers to quickly adapt to changes in consumer habits and market trends.
Furthermore, AI and ML enable personalization recommendations and targeted marketing campaigns, improving customer experience and increasing sales. These technologies can provide better shopping experiences to customers and create loyalty by understanding individual customer behaviors and then recommending products that best suit individual shoppers. The adoption of AI and ML capabilities within retail analytics platforms empowers retailers with actionable insights, enabling data-driven decisions, operational optimization, and personalized experiences. And these technologies are bound to grow in importance in the future of the market of retail analytics.
The growing amount of data from online transactions, in-store activities, and social media interactions drives the demand for analytics solutions.
Retailers are leveraging analytics to create targeted marketing campaigns based on consumer behavior and preferences.
Restraints
There is a shortage of skilled professionals who can effectively interpret and utilize retail analytics data.
One of the key challenges that retailers face while adopting the advanced analytics solution is the limited skilled professionals in the retail analytics market. Retail analytics platforms produce more data than retailers can fathom; but without the talent who know how to read and convert that data into actionable insights, it becomes completely useless. However, there is a gap between the demand for data scientists and analysts and AI, ML, and data management professionals and the talent supply. This was further driven by the fact that the analytics talent was hard to find, especially among small and medium enterprises retailers, which in turn prevented them from optimizing their analytics platforms.
With improper knowledge and the lack of specialists, retailers will find it difficult to get meaningful insights out of the data, thus losing out on making improvements to operations, experience, and profitability. Professionals who are well-versed in data quality management, predictive modeling, and optimization ensure the analytics platforms deliver exactly what the retailer requires. They also serve as mentors who interpret complex data and make strategic recommendations based on trends and patterns. This also adds to the cost of recruitment of these analytics professionals and also takes time before these analytics solutions are implemented. Retailers either need to train employees with no experience or fight the job market where it can be hard to find professionals with experience. As the retail analytics demand rises, bridging this talent gap is vital for enterprises to stay ahead of the competition with data-enabled decisions. Therefore, along with the increase of the retail analytics market, it becomes a dire need of the hour to build up focused training programs and collaborations with institutes.
The initial investment in retail analytics tools and technologies can be expensive for small and medium-sized retailers.
Increasing concerns over data security and privacy regulations may limit the adoption of retail analytics solutions.
By Deployment
The cloud segment dominated the market and represented a significant revenue share of 59% in 2023, Growing preference for cloud-based solutions, providing scalability and cost-efficiency for faster deployment, has led to a sudden increase in the cloud-based deployment segment in the retail analytics market. Cloud enables retailers to store and analyze vast amounts of data with less capital depreciation in hardware. Digital transformation and increasing e-commerce demand have led to a proliferation of cloud-based retail analytics solutions. Also, cloud platforms allow for easier integration of other digital tools, including CRM and ERP systems, increasing overall operational efficiency. Deployment of the cloud is expected to continue thriving in the future growing number of retailers are opting for cloud-based solutions to improve data-driven decision-making as well as innovation.
The on-premise deployment segment is expected to grow at the fastest CAGR. On-premise solutions are also preferred by large enterprises as they provide greater control over data security, compliance, and customization. On-premise segment is driven by the capability to store sensitive customer and transactional data, which comes in handy, particularly in the industries that are governed by temperature-sensitive data privacy, security, and cyber regulations. Pre-existing solutions can also help speed up data processing and local infrastructure integration. With a growing emphasis on data privacy and the emergence of stricter regulatory requirements, the need for on-premise solutions is likely to increase especially for industries such as healthcare, finance, and governmental entities that need to keep their data secure.
By Retail Store Type
The retail chains dominated the market and accounted for a revenue share of more than 59% in 2023, which needs to optimize inventory management, increase operational efficiency, and enhance consumer engagement through advanced data analytics across their extensive operations. These chains are adapting to use analytics to gain more depth around consumer habits, hyper-personalize marketing and optimize their operations. Furthermore, the rising e-commerce space along with the increasing requirement for omnichannel strategy have notably driven the retail analytics demand in this segment. Battling against rising competition and changing customer expectations, retail chains are leveraging data-driven insights to stay ahead in this race. Retail chains can expect to witness a great future ahead in terms of the decision-making process, and they continue to invest the analytics solutions to enable informed decision-making, build an optimized supply chain, and offer a more personalized customer experience.
The Hypermarkets and Supermarkets are expected to register the fastest CAGR during the forecast period. As these retail types handle a huge number of transactions and an even larger number of inventories, analytics is crucial to helping optimize aspects such as inventory management, demand forecasting, and providing the customer with tailored promotions and recommendations. The growth of e-grocery and demand for interlinking physical stores with digital stores is also one of the key factors expected to drive the adoption of retail analytics for grocery in this segment. With changing customer preferences and increasing demand for convenience, hypermarkets and supermarkets are likely to further invest in analytics solutions to streamline operations and enhance overall customer experience.
North America dominated the market and accounted for a revenue share of more than 39% due to its high infrastructure and plant capacity in terms of technology and equipment, and rapid adoption of a wide range of digital solutions by the leading players in the Retail market. With the increasing focus on data-based decision-making, customer-specific experiences, and operational effectiveness, retail analytics solutions are increasingly being embraced by the region. Moreover, the growth of e-commerce, omnichannel retailing, and the need for inventory optimization have increased the demand for analytics tools. The roadmap for North America still looks bright as the region is continuously investing in advanced analytics AI and machine learning-based technologies to strengthen operational strategy, enhance customer insights, and retain a competitive advantage in retail.
Asia Pacific is likely to be the fastest-growing region in the retail analytics market during the forecast period due to faster digitization, higher internet penetration, and a larger pool of consumer spending. Demand for data-driven solutions to improve inventory management, personalized marketing, and customer experiences is propelled by the growing retail sector in the region, especially in emerging markets such as China and India. This, coupled with the increasing shift towards e-commerce and mobile shopping, is also further driving the adoption of retail analytics in the region. With the evolution of retail and the predictive and analytical capabilities of technologies like AI, machine learning, and IoT, the adoption curve will further the size of the market. Asia Pacific continues to be an extremely positive, high-growth region from both traditional as well as online retail strategies.
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The major key players along with their products are
SAP SE - SAP Customer Activity Repository
Oracle Corporation - Oracle Retail Analytics
IBM Corporation - IBM Watson Retail Analytics
SAS Institute Inc. - SAS Retail Analytics
Microsoft Corporation - Microsoft Power BI
Qlik Technologies Inc. - Qlik Sense
Teradata Corporation - Teradata Vantage
Nielsen Holdings PLC - NielsenIQ
Tableau Software - Tableau Analytics Platform
Google LLC - Google Cloud Retail Analytics
Infor - Infor CloudSuite Retail
Manthan Systems - Manthan Retail Analytics Suite
TIBCO Software Inc. - TIBCO Spotfire for Retail Analytics
In January 2024, Walmart's CEO, John Furner, announced the use of 'digital twin' technology to optimize store layouts across over 1,700 locations, enhancing customer shopping experiences and store efficiency.
In November 2024, Walmart incorporated weather analysis into its AI software for inventory planning, adjusting product pricing strategies based on regional weather forecasts to enhance operational efficiency.
| Report Attributes | Details |
|---|---|
| Market Size in 2023 | USD 8.0 Billion |
| Market Size by 2032 | USD 45.4 Billion |
| CAGR | CAGR of 21.31% From 2024 to 2032 |
| Base Year | 2023 |
| Forecast Period | 2024-2032 |
| Historical Data | 2020-2022 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Deployment (On-Premise, Cloud) • By Retail Store Type (Hypermarkets and Supermarkets, Retail Chains) • By Function (Customer Management, Supply Chain, Merchandising, Strategy and Planning, In-Store Operations) |
| Regional Analysis/Coverage | North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia, Rest of Latin America) |
| Company Profiles | SAP SE, Oracle Corporation, IBM Corporation, SAS Institute Inc., Microsoft Corporation, Qlik Technologies Inc., Teradata Corporation, Nielsen Holdings PLC, Tableau Software, Google LLC, Infor, Manthan Systems, TIBCO Software Inc. |
| Key Drivers | • The growing amount of data from online transactions, in-store activities, and social media interactions drives the demand for analytics solutions. • Retailers are leveraging analytics to create targeted marketing campaigns based on consumer behavior and preferences. |
| RESTRAINTS | • The initial investment in retail analytics tools and technologies can be expensive for small and medium-sized retailers. • Increasing concerns over data security and privacy regulations may limit the adoption of retail analytics solutions. |
Ans- The Retail Analytics Market was valued at USD 8.0 Billion in 2023 and is expected to reach USD 45.4 Billion by 2032, growing at a CAGR of 21.31% from 2024-2032.
Ans- The CAGR of the Retail Analytics Market during the forecast period is 21.31% from 2024-2032.
Ans- Asia-Pacific is expected to register the fastest CAGR during the forecast period.
Ans- The growing amount of data from online transactions, in-store activities, and social media interactions drives the demand for analytics solutions.
Ans- Increasing concerns over data security and privacy regulations may limit the adoption of retail analytics solutions.
Table of Contents
1. Introduction
1.1 Market Definition
1.2 Scope (Inclusion and Exclusions)
1.3 Research Assumptions
2. Executive Summary
2.1 Market Overview
2.2 Regional Synopsis
2.3 Competitive Summary
3. Research Methodology
3.1 Top-Down Approach
3.2 Bottom-up Approach
3.3. Data Validation
3.4 Primary Interviews
4. Market Dynamics Impact Analysis
4.1 Market Driving Factors Analysis
4.1.1 Drivers
4.1.2 Restraints
4.2 PESTLE Analysis
4.3 Porter’s Five Forces Model
5. Statistical Insights and Trends Reporting
5.1 Adoption Rates of Emerging Technologies
5.2 Network Infrastructure Expansion, by Region
5.3 Cybersecurity Incidents, by Region (2020-2023)
5.4 Cloud Services Usage, by Region
6. Competitive Landscape
6.1 List of Major Companies, By Region
6.2 Market Share Analysis, By Region
6.3 Product Benchmarking
6.3.1 Product specifications and features
6.3.2 Pricing
6.4 Strategic Initiatives
6.4.1 Marketing and promotional activities
6.4.2 Distribution and supply chain strategies
6.4.3 Expansion plans and new product launches
6.4.4 Strategic partnerships and collaborations
6.5 Technological Advancements
6.6 Market Positioning and Branding
7. Retail Analytics Market Segmentation, By Deployment
7.1 Chapter Overview
7.2 On-Premise
7.2.1 On-Premise Market Trends Analysis (2020-2032)
7.2.2 On-Premise Market Size Estimates and Forecasts to 2032 (USD Billion)
7.3 Cloud
7.3.1 Cloud Market Trends Analysis (2020-2032)
7.3.2 Cloud Market Size Estimates and Forecasts to 2032 (USD Billion)
8. Retail Analytics Market Segmentation, by Retail Store Type
8.1 Chapter Overview
8.2 Hypermarkets and Supermarkets
8.2.1 Hypermarkets and Supermarkets Market Trends Analysis (2020-2032)
8.2.2 Hypermarkets and Supermarkets Market Size Estimates and Forecasts to 2032 (USD Billion)
8.3 Retail Chains
8.3.1 Retail Chains Market Trends Analysis (2020-2032)
8.3.2 Retail Chains Market Size Estimates and Forecasts to 2032 (USD Billion)
9. Retail Analytics Market Segmentation, by Function
9.1 Chapter Overview
9.2 Customer Management
9.2.1 Customer Management Market Trends Analysis (2020-2032)
9.2.2 Customer Management Market Size Estimates and Forecasts to 2032 (USD Billion)
9.3 Supply Chain
9.3.1 Supply Chain Market Trends Analysis (2020-2032)
9.3.2 Supply Chain Market Size Estimates and Forecasts to 2032 (USD Billion)
9.4 Merchandising
9.4.1 Merchandising Market Trends Analysis (2020-2032)
9.4.2 Merchandising Market Size Estimates and Forecasts to 2032 (USD Billion)
9.5 Strategy and Planning
9.5.1Strategy and Planning Market Trends Analysis (2020-2032)
9.5.2Strategy and Planning Market Size Estimates and Forecasts to 2032 (USD Billion)
9.6 In-Store Operations
9.6.1In-Store Operations Market Trends Analysis (2020-2032)
9.6.2In-Store Operations Market Size Estimates and Forecasts to 2032 (USD Billion)
10. Regional Analysis
10.1 Chapter Overview
10.2 North America
10.2.1 Trends Analysis
10.2.2 North America Retail Analytics Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
10.2.3 North America Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.2.4 North America Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.2.5 North America Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.2.6 USA
10.2.6.1 USA Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.2.6.2 USA Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.2.6.3 USA Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.2.7 Canada
10.2.7.1 Canada Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.2.7.2 Canada Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.2.7.3 Canada Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.2.8 Mexico
10.2.8.1 Mexico Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.2.8.2 Mexico Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.2.8.3 Mexico Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3 Europe
10.3.1 Eastern Europe
10.3.1.1 Trends Analysis
10.3.1.2 Eastern Europe Retail Analytics Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
10.3.1.3 Eastern Europe Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.1.4 Eastern Europe Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.1.5 Eastern Europe Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.1.6 Poland
10.3.1.6.1 Poland Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.1.6.2 Poland Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.1.6.3 Poland Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.1.7 Romania
10.3.1.7.1 Romania Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.1.7.2 Romania Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.1.7.3 Romania Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.1.8 Hungary
10.3.1.8.1 Hungary Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.1.8.2 Hungary Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.1.8.3 Hungary Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.1.9 Turkey
10.3.1.9.1 Turkey Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.1.9.2 Turkey Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.1.9.3 Turkey Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.1.10 Rest of Eastern Europe
10.3.1.10.1 Rest of Eastern Europe Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.1.10.2 Rest of Eastern Europe Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.1.10.3 Rest of Eastern Europe Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.2 Western Europe
10.3.2.1 Trends Analysis
10.3.2.2 Western Europe Retail Analytics Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
10.3.2.3 Western Europe Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.2.4 Western Europe Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.2.5 Western Europe Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.2.6 Germany
10.3.2.6.1 Germany Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.2.6.2 Germany Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.2.6.3 Germany Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.2.7 France
10.3.2.7.1 France Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.2.7.2 France Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.2.7.3 France Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.2.8 UK
10.3.2.8.1 UK Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.2.8.2 UK Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.2.8.3 UK Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.2.9 Italy
10.3.2.9.1 Italy Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.2.9.2 Italy Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.2.9.3 Italy Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.2.10 Spain
10.3.2.10.1 Spain Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.2.10.2 Spain Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.2.10.3 Spain Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.2.11 Netherlands
10.3.2.11.1 Netherlands Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.2.11.2 Netherlands Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.2.11.3 Netherlands Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.2.12 Switzerland
10.3.2.12.1 Switzerland Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.2.12.2 Switzerland Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.2.12.3 Switzerland Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.2.13 Austria
10.3.2.13.1 Austria Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.2.13.2 Austria Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.2.13.3 Austria Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.3.2.14 Rest of Western Europe
10.3.2.14.1 Rest of Western Europe Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.3.2.14.2 Rest of Western Europe Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.3.2.14.3 Rest of Western Europe Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.4 Asia Pacific
10.4.1 Trends Analysis
10.4.2 Asia Pacific Retail Analytics Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
10.4.3 Asia Pacific Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.4.4 Asia Pacific Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.4.5 Asia Pacific Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.4.6 China
10.4.6.1 China Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.4.6.2 China Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.4.6.3 China Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.4.7 India
10.4.7.1 India Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.4.7.2 India Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.4.7.3 India Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.4.8 Japan
10.4.8.1 Japan Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.4.8.2 Japan Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.4.8.3 Japan Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.4.9 South Korea
10.4.9.1 South Korea Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.4.9.2 South Korea Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.4.9.3 South Korea Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.4.10 Vietnam
10.4.10.1 Vietnam Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.4.10.2 Vietnam Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.4.10.3 Vietnam Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.4.11 Singapore
10.4.11.1 Singapore Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.4.11.2 Singapore Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.4.11.3 Singapore Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.4.12 Australia
10.4.12.1 Australia Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.4.12.2 Australia Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.4.12.3 Australia Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.4.13 Rest of Asia Pacific
10.4.13.1 Rest of Asia Pacific Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.4.13.2 Rest of Asia Pacific Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.4.13.3 Rest of Asia Pacific Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.5 Middle East and Africa
10.5.1 Middle East
10.5.1.1 Trends Analysis
10.5.1.2 Middle East Retail Analytics Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
10.5.1.3 Middle East Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.5.1.4 Middle East Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.5.1.5 Middle East Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.5.1.6 UAE
10.5.1.6.1 UAE Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.5.1.6.2 UAE Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.5.1.6.3 UAE Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.5.1.7 Egypt
10.5.1.7.1 Egypt Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.5.1.7.2 Egypt Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.5.1.7.3 Egypt Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.5.1.8 Saudi Arabia
10.5.1.8.1 Saudi Arabia Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.5.1.8.2 Saudi Arabia Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.5.1.8.3 Saudi Arabia Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.5.1.9 Qatar
10.5.1.9.1 Qatar Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.5.1.9.2 Qatar Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.5.1.9.3 Qatar Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.5.1.10 Rest of Middle East
10.5.1.10.1 Rest of Middle East Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.5.1.10.2 Rest of Middle East Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.5.1.10.3 Rest of Middle East Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.5.2 Africa
10.5.2.1 Trends Analysis
10.5.2.2 Africa Retail Analytics Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
10.5.2.3 Africa Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.5.2.4 Africa Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.5.2.5 Africa Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.5.2.6 South Africa
10.5.2.6.1 South Africa Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.5.2.6.2 South Africa Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.5.2.6.3 South Africa Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.5.2.7 Nigeria
10.5.2.7.1 Nigeria Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.5.2.7.2 Nigeria Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.5.2.7.3 Nigeria Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.5.2.8 Rest of Africa
10.5.2.8.1 Rest of Africa Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.5.2.8.2 Rest of Africa Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.5.2.8.3 Rest of Africa Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.6 Latin America
10.6.1 Trends Analysis
10.6.2 Latin America Retail Analytics Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
10.6.3 Latin America Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.6.4 Latin America Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.6.5 Latin America Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.6.6 Brazil
10.6.6.1 Brazil Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.6.6.2 Brazil Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.6.6.3 Brazil Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.6.7 Argentina
10.6.7.1 Argentina Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.6.7.2 Argentina Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.6.7.3 Argentina Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.6.8 Colombia
10.6.8.1 Colombia Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.6.8.2 Colombia Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.6.8.3 Colombia Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
10.6.9 Rest of Latin America
10.6.9.1 Rest of Latin America Retail Analytics Market Estimates and Forecasts, By Deployment (2020-2032) (USD Billion)
10.6.9.2 Rest of Latin America Retail Analytics Market Estimates and Forecasts, by Retail Store Type (2020-2032) (USD Billion)
10.6.9.3 Rest of Latin America Retail Analytics Market Estimates and Forecasts, by Function (2020-2032) (USD Billion)
11. Company Profiles
11.1 SAP SE
11.1.1 Company Overview
11.1.2 Financial
11.1.3 Products/ Services Offered
11.1.4 SWOT Analysis
11.2 Oracle Corporation
11.2.1 Company Overview
11.2.2 Financial
11.2.3 Products/ Services Offered
11.2.4 SWOT Analysis
11.3 IBM Corporation
11.3.1 Company Overview
11.3.2 Financial
11.3.3 Products/ Services Offered
11.3.4 SWOT Analysis
11.4 SAS Institute Inc.
11.4.1 Company Overview
11.4.2 Financial
11.4.3 Products/ Services Offered
11.4.4 SWOT Analysis
11.5 Microsoft Corporation
11.5.1 Company Overview
11.5.2 Financial
11.5.3 Products/ Services Offered
11.5.4 SWOT Analysis
11.6 Qlik Technologies Inc
11.6.1 Company Overview
11.6.2 Financial
11.6.3 Products/ Services Offered
11.6.4 SWOT Analysis
11.7 Teradata Corporation
11.7.1 Company Overview
11.7.2 Financial
11.7.3 Products/ Services Offered
11.7.4 SWOT Analysis
11.8 Nielsen Holdings PLC
11.8.1 Company Overview
11.8.2 Financial
11.8.3 Products/ Services Offered
11.8.4 SWOT Analysis
11.9 Tableau Software
11.9.1 Company Overview
11.9.2 Financial
11.9.3 Products/ Services Offered
11.9.4 SWOT Analysis
11.10 Google LLC
11.10.1 Company Overview
11.10.2 Financial
11.10.3 Products/ Services Offered
11.10.4 SWOT Analysis
12. Use Cases and Best Practices
13. Conclusion
An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.
Each report that we prepare takes a timeframe of 350-400 business hours for production. Starting from the selection of titles through a couple of in-depth brain storming session to the final QC process before uploading our titles on our website we dedicate around 350 working hours. The titles are selected based on their current market cap and the foreseen CAGR and growth.
The 5 steps process:
Step 1: Secondary Research:
Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.
Step 2: Primary Research
When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data. This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.
We at SNS Insider have divided Primary Research into 2 parts.
Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.
This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.
Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.
Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.
Step 3: Data Bank Validation
Once all the information is collected via primary and secondary sources, we run that information for data validation. At our intelligence centre our research heads track a lot of information related to the market which includes the quarterly reports, the daily stock prices, and other relevant information. Our data bank server gets updated every fortnight and that is how the information which we collected using our primary and secondary information is revalidated in real time.
Step 4: QA/QC Process
After all the data collection and validation our team does a final level of quality check and quality assurance to get rid of any unwanted or undesired mistakes. This might include but not limited to getting rid of the any typos, duplication of numbers or missing of any important information. The people involved in this process include technical content writers, research heads and graphics people. Once this process is completed the title gets uploader on our platform for our clients to read it.
Step 5: Final QC/QA Process:
This is the last process and comes when the client has ordered the study. In this process a final QA/QC is done before the study is emailed to the client. Since we believe in giving our clients a good experience of our research studies, therefore, to make sure that we do not lack at our end in any way humanly possible we do a final round of quality check and then dispatch the study to the client.
Key Segments:
By Deployment
On-Premise
Cloud
By Retail Store Type
Hypermarkets and Supermarkets
Retail Chains
By Function
Customer Management
Supply Chain
Merchandising
Strategy and Planning
In-Store Operations
Request for Segment Customization as per your Business Requirement: Segment Customization Request
REGIONAL COVERAGE:
North America
US
Canada
Mexico
Europe
Eastern Europe
Poland
Romania
Hungary
Turkey
Rest of Eastern Europe
Western Europe
Germany
France
UK
Italy
Spain
Netherlands
Switzerland
Austria
Rest of Western Europe
Asia Pacific
China
India
Japan
South Korea
Vietnam
Singapore
Australia
Rest of Asia Pacific
Middle East & Africa
Middle East
UAE
Egypt
Saudi Arabia
Qatar
Rest of the Middle East
Africa
Nigeria
South Africa
Rest of Africa
Latin America
Brazil
Argentina
Colombia
Rest of Latin America
Request for Country Level Research Report: Country Level Customization Request
Available Customization
With the given market data, SNS Insider offers customization as per the company’s specific needs. The following customization options are available for the report:
Product Analysis
Criss-Cross segment analysis (e.g. Product X Application)
Product Matrix which gives a detailed comparison of product portfolio of each company
Geographic Analysis
Additional countries in any of the regions
Company Information
Detailed analysis and profiling of additional market players (Up to five)
The Data Center Liquid Cooling Market was valued at USD 2.99 Billion in 2023 and will reach USD 17.28 Billion by 2032, growing at a CAGR of 21.54% by 2032.
The Healthcare Cloud Computing Market size was valued at USD 48.88 Billion in 2023 and will reach USD 199.21 Billion by 2032 with a growing CAGR of 16.90% by2032.
The Open Source Services Market was valued at USD 28.6 billion in 2023 and will reach to USD 114.8 Billion by 2032, growing at a CAGR of 16.70% by 2032.
The Network Automation Market Size was valued at USD 4.7 Billion in 2023 and is expected to reach USD 32.1 Billion by 2032, growing at a CAGR of 23.8% by 2032.
The Digital Badges Market size was USD 208.05 Million in 2023 and is expected to reach USD 921.78 Mn by 2032 and grow at a CAGR of 18.01% by 2024-2032.
Progressive Web Apps Market size was USD 1.4 Billion in 2023 and will reach to USD 13.3 Billion by 2032 and grow at a CAGR of 28.6% by 2024-2032.
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