The In-store analytics Market Size was valued at USD 3.0 billion in 2023 and is expected to reach USD 16.4 billion by 2031 and grow at a CAGR of 23.7 % over the forecast period 2024-2031.
The in-store analytics market is flourishing due to, Retailers leverage customer data to personalize the shopping experience, from targeted promotions to optimized layouts. Data-driven decisions based on real-time insights improve inventory management, staffing, and store design. Furthermore, analytics solutions can deter shoplifting and enhance security. Integration with AR allows for virtual try-on experiences and product visualization, boosting engagement and sales. Finally, cloud-based solutions democratize access to data, empowering smaller retailers to compete through data-driven strategies. This market offers exciting opportunities for shaping the future of retail through innovation and a focus on customer experience.
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KEY DRIVERS:
Inventory Management and Theft Prevention.
Enhanced Customer Experience drive the market growth.
Analytics helps retailers personalize shopping experiences. For instance, Macy's utilizes in-store Wi-Fi tracking to send targeted promotions to customers' phones based on their location within the store, leading to increased customer satisfaction and potentially higher sales.
RESTRAINTS:
Integrating in-store analytics systems with existing IT infrastructure can be complex, requiring technical expertise and potentially delaying implementation.
Cost of Implementation can be a barrier in market growth.
Advanced in-store analytics solutions can be expensive, especially for smaller retailers. The initial investment in hardware, software, and data security measures can be a significant hurdle.
OPPORTUNITIES:
Growth in Emerging Markets, presents a significant opportunity for solution providers to cater to this growing segment.
Convergence with Emerging Technologies.
The integration of in-store analytics with technologies like augmented reality (AR) can create a more interactive shopping experience. For example, retailers could offer AR product information overlays or virtual try-on experiences, potentially leading to increased engagement and sales.
CHALLENGES:
Cybersecurity threats are a growing concern as retailers collect and store customer data. Implementing strong security measures is critical to protecting sensitive customer data.
Evolving Consumer Behavior can be Challenging .
Consumer behavior is constantly evolving, requiring retailers to adapt their analytics strategies. Staying ahead of these trends and continuously refining data collection and analysis methods is a challenge.
Sanctions imposed on Russia and disruptions in global supply chains have led to a shortage of critical components like semiconductors, which are essential for manufacturing hardware used in in-store analytics solutions. This shortage, coupled with rising energy costs, can potentially lead to price hikes for these solutions, impacting both retailers' initial investment and ongoing operational costs. Consumer spending habits have shifted due to the war and rising inflation. There's a growing focus on essential goods, potentially leading to decreased foot traffic in stores selling discretionary items. This could impact the market for in-store analytics solutions in these sectors, as retailers might re-evaluate the return on investment for such technologies. The war could also create unforeseen opportunities. For instance, there might be a rise in demand for in-store analytics solutions that help retailers track inventory levels more effectively and manage potential stockouts of essential goods. Additionally, the focus on cost-efficiency could lead to a surge in demand for cloud-based analytics solutions offering subscription models as they are typically more affordable for retailers.
During Economic Slowdown, Consumers tighten their budget. which reduces retail sales. This could contribute to a 10-15% decline in the overall growth of the in-store analytics market as retailers may delay or reduce investments in non-essential technologies. Retailers may prefer short-term cost-cutting measures over long-term investments. This could lead to a 10% increase in demand for affordable cloud-based analytics solutions compared to more complex on-premise systems. Retailers are likely to demand a clearer return on investment (ROI) from in-store analytics solutions. This could lead to a more than 12 percent increase in demand for analytics platforms with features that directly lead to cost savings or sales improvements.
Eg. a large department store chain considering an advanced store analytics platform with an annual subscription fee of $1 million. During a economic slowdown, when sales are down and the focus is on reducing costs, a business might opt for a more basic cloud-based solution that costs $200,000 a year. This change reflects market dynamics that prioritize affordability in times of economic distress.
KEY MARKET SEGMENTS:
By Component
Software
Service
Managed Service
Professional Service
Consulting
Support & Maintenance
Based on Component, Software segment hold a larger market size during the forecast period. It transcends the service segment and sees future growth due to increased adoption of software. Store analytics software allows stores to track sales to identify customer preferences and create business plans accordingly. By identifying trends and anomalies early, stores can also prevent risks such as shoplifting and OOS situations. In addition, new technologies such as AI and store analytics software integration capabilities have facilitated real-time forecasting of customer demand.
By Deployment Mode
On-Premise
Cloud
By Deployment Model, On-premises deployment segment is dominating.the On-Premise solution gives organizations complete control over the platform, applications, systems and data that can be processed and managed by the organization's own IT staff. the growth of the On-premise deployment model is primarily driven by flexibility, adapt the software according to the dynamic requirements of the organization. A store dealing with customer identity data would prefer an on-premises deployment model because the systems can be managed by the organization's own staff. Retail stores where data security and privacy are key concerns typically follow an on-premise deployment model.
By Application
Customer Management
Marketing Management
Merchandising Analysis
Store Operations Management
Risk and Compliance Management
Other
By Organization Size
Large Enterprises
Small & Medium Enterprises
North America has been at the forefront with high adoption of advanced In-Store Analytics solutions. Large retail chains are dominant players, driving demand for sophisticated systems like heat mapping, customer journey tracking, and AI-powered checkout optimization. While large retailers are major users, some SMEs are also adopting In-Store Analytics. Cloud-based solutions with affordable subscription models are making these tools more accessible. SMEs might focus on simpler analytics to optimize store layout, understand customer behavior, and improve staffing levels. A focus on enhancing customer experience, optimizing store operations, and increasing sales efficiency are key drivers for North American retailers. Additionally, data privacy regulations like CCPA (California Consumer Privacy Act) are shaping the market by requiring responsible data collection practices.
Asia Pacific region is experiencing rapid growth in In-Store Analytics. While large retailers are present, there's a significant number of SMEs with varying levels of technological adoption. Rising competition, growing disposable income leading to higher consumer expectations, and government support for retail modernization are key drivers in Asia Pacific. SMEs in Asia Pacific often utilize simpler, cost-effective solutions like basic traffic counting or basic heat mapping tools. Government initiatives and affordability are crucial factors in driving SME adoption. These solutions can help them understand customer behavior and improve product placement for better sales results.
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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
The major key players are SAP SE, Celect Inc., Capillary Technologies, Inpixon, Scanalytics Inc., Dor Technologies Inc., SEMSEYE, RETAILNEXT, INC., Mindtree Ltd, Happiest Minds & Other Players
In March 15, 2024, Retail Analytics Platform Integration.
IBM and Cisco announced a collaboration to integrate their respective retail analytics platforms, offering a more comprehensive solution for data collection and analysis.
In January 24, 2024, Integration of AR with In-Store Navigation.
Google introduced an update to its ARCore platform, enabling integration with in-store navigation apps. This allows for features like AR wayfinding and product information overlays.
| Report Attributes | Details |
|---|---|
| Market Size in 2023 | US$ 3.0 Billion |
| Market Size by 2031 | US$ 16.4 Billion |
| CAGR | CAGR of 23.7% From 2024 to 2031 |
| Base Year | 2023 |
| Forecast Period | 2024-2031 |
| Historical Data | 2020-2022 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • by Component (Software and Services) • by Deployment Mode (On-premise and Cloud) • by Organization Size (Large Enterprises and Small & Medium Enterprises) • by Application (Customer Management, Marketing Management, Merchandising Analysis, Store Operations Management, Risk and Compliance Management, and Other) |
| 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, Celect Inc., Capillary Technologies, Inpixon, Scanalytics Inc., Dor Technologies Inc., SEMSEYE, RETAILNEXT, INC., Mindtree Ltd, and Happiest Minds |
| Key Drivers | •New Advanced Technologies Raise Data Security and Privacy Concerns. •Inadequate Skilled Personnel. |
| RESTRAINTS | •Inadequate awareness and excessive service costs. •There are no comprehensive IT asset disposition procedures in place. |
Ans. The In-Store Analytics market size is forecasted to surpass USD 16.4 billion by 2031.
Ans: - Ecommerce Players' Increased Competition and Improved Customer Service and Shopping Experience.
Ans: - The segments covered in the In-Store Analytics Market report for study are on the basis of Component, Deployment Mode, Organization Size, and Application.
Ans. The primary growth tactics of In-Store Analytics market participants include merger and acquisition, business expansion, and product launch.
Ans: - Manufacturers, Research Institutes, university libraries, suppliers, and distributors of the product.
TABLE OF CONTENTS
1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions
2. Industry Flowchart
3. Research Methodology
4. Market Dynamics
4.1 Drivers
4.2 Restraints
4.3 Opportunities
4.4 Challenges
5. Impact Analysis
5.1 Impact of Russia-Ukraine Crisis
5.2 Impact of Economic Slowdown on Major Countries
5.2.1 Introduction
5.2.2 United States
5.2.3 Canada
5.2.4 Germany
5.2.5 France
5.2.6 UK
5.2.7 China
5.2.8 Japan
5.2.9 South Korea
5.2.10 India
6. Value Chain Analysis
7. Porter’s 5 Forces Model
8. Pest Analysis
9. In-Store Analytics Market, By Component
9.1 Introduction
9.2 Trend Analysis
9.3 Software
9.4 Service
9.4.1 Managed Service
9.4.2 Professional Service
9.4.3 Consulting
9.4.4 Support & Maintenance
10. In-Store Analytics Market, By Deployment Mode
10.1 Introduction
10.2 Trend Analysis
10.3 On-Premise
10.4 Cloud
11. In-Store Analytics Market, By Application
11.1 Introduction
11.2 Trend Analysis
11.3 Customer Management
11.4 Marketing Management
11.5 Merchandising Analysis
11.6 Store Operations Management
11.7 Risk and Compliance Management
11.8 Other
12. In-Store Analytics Market, By Organization Size
12.1 Introduction
12.2 Trend Analysis
12.3 Large Enterprises
12.4 Small & Medium Enterprises
13. Regional Analysis
13.1 Introduction
13.2 North America
13.2.1 Trend Analysis
13.2.2 North America In-Store Analytics Market, by Country
13.2.3 North America In-Store Analytics Market, By Component
13.2.4 North America In-Store Analytics Market, By Deployment Mode
13.2.5 North America In-Store Analytics Market, By Application
13.2.6 North America In-Store Analytics Market, By Organization Size
13.2.7 USA
13.2.7.1 USA In-Store Analytics Market, By Component
13.2.7.2 USA In-Store Analytics Market, By Deployment Mode
13.2.7.3 USA In-Store Analytics Market, By Application
13.2.7.4 USA In-Store Analytics Market, By Organization Size
13.2.8 Canada
13.2.8.1 Canada In-Store Analytics Market, By Component
13.2.8.2 Canada In-Store Analytics Market, By Deployment Mode
13.2.8.3 Canada In-Store Analytics Market, By Application
13.2.8.4 Canada In-Store Analytics Market, By Organization Size
13.2.9 Mexico
13.2.9.1 Mexico In-Store Analytics Market, By Component
13.2.9.2 Mexico In-Store Analytics Market, By Deployment Mode
13.2.9.3 Mexico In-Store Analytics Market, By Application
13.2.9.4 Mexico In-Store Analytics Market, By Organization Size
13.3 Europe
13.3.1 Trend Analysis
13.3.2 Eastern Europe
13.3.2.1 Eastern Europe In-Store Analytics Market, by Country
13.3.2.2 Eastern Europe In-Store Analytics Market, By Component
13.3.2.3 Eastern Europe In-Store Analytics Market, By Deployment Mode
13.3.2.4 Eastern Europe In-Store Analytics Market, By Application
13.3.2.5 Eastern Europe In-Store Analytics Market, By Organization Size
13.3.2.6 Poland
13.3.2.6.1 Poland In-Store Analytics Market, By Component
13.3.2.6.2 Poland In-Store Analytics Market, By Deployment Mode
13.3.2.6.3 Poland In-Store Analytics Market, By Application
13.3.2.6.4 Poland In-Store Analytics Market, By Organization Size
13.3.2.7 Romania
13.3.2.7.1 Romania In-Store Analytics Market, By Component
13.3.2.7.2 Romania In-Store Analytics Market, By Deployment Mode
13.3.2.7.3 Romania In-Store Analytics Market, By Application
13.3.2.7.4 Romania In-Store Analytics Market, By Organization Size
13.3.2.8 Hungary
13.3.2.8.1 Hungary In-Store Analytics Market, By Component
13.3.2.8.2 Hungary In-Store Analytics Market, By Deployment Mode
13.3.2.8.3 Hungary In-Store Analytics Market, By Application
13.3.2.8.4 Hungary In-Store Analytics Market, By Organization Size
13.3.2.9 Turkey
13.3.2.9.1 Turkey In-Store Analytics Market, By Component
13.3.2.9.2 Turkey In-Store Analytics Market, By Deployment Mode
13.3.2.9.3 Turkey In-Store Analytics Market, By Application
13.3.2.9.4 Turkey In-Store Analytics Market, By Organization Size
13.3.2.10 Rest of Eastern Europe
13.3.2.10.1 Rest of Eastern Europe In-Store Analytics Market, By Component
13.3.2.10.2 Rest of Eastern Europe In-Store Analytics Market, By Deployment Mode
13.3.2.10.3 Rest of Eastern Europe In-Store Analytics Market, By Application
13.3.2.10.4 Rest of Eastern Europe In-Store Analytics Market, By Organization Size
13.3.3 Western Europe
13.3.3.1 Western Europe In-Store Analytics Market, by Country
13.3.3.2 Western Europe In-Store Analytics Market, By Component
13.3.3.3 Western Europe In-Store Analytics Market, By Deployment Mode
13.3.3.4 Western Europe In-Store Analytics Market, By Application
13.3.3.5 Western Europe In-Store Analytics Market, By Organization Size
13.3.3.6 Germany
13.3.3.6.1 Germany In-Store Analytics Market, By Component
13.3.3.6.2 Germany In-Store Analytics Market, By Deployment Mode
13.3.3.6.3 Germany In-Store Analytics Market, By Application
13.3.3.6.4 Germany In-Store Analytics Market, By Organization Size
13.3.3.7 France
13.3.3.7.1 France In-Store Analytics Market, By Component
13.3.3.7.2 France In-Store Analytics Market, By Deployment Mode
13.3.3.7.3 France In-Store Analytics Market, By Application
13.3.3.7.4 France In-Store Analytics Market, By Organization Size
13.3.3.8 UK
13.3.3.8.1 UK In-Store Analytics Market, By Component
13.3.3.8.2 UK In-Store Analytics Market, By Deployment Mode
13.3.3.8.3 UK In-Store Analytics Market, By Application
13.3.3.8.4 UK In-Store Analytics Market, By Organization Size
13.3.3.9 Italy
13.3.3.9.1 Italy In-Store Analytics Market, By Component
13.3.3.9.2 Italy In-Store Analytics Market, By Deployment Mode
13.3.3.9.3 Italy In-Store Analytics Market, By Application
13.3.3.9.4 Italy In-Store Analytics Market, By Organization Size
13.3.3.10 Spain
13.3.3.10.1 Spain In-Store Analytics Market, By Component
13.3.3.10.2 Spain In-Store Analytics Market, By Deployment Mode
13.3.3.10.3 Spain In-Store Analytics Market, By Application
13.3.3.10.4 Spain In-Store Analytics Market, By Organization Size
13.3.3.11 Netherlands
13.3.3.11.1 Netherlands In-Store Analytics Market, By Component
13.3.3.11.2 Netherlands In-Store Analytics Market, By Deployment Mode
13.3.3.11.3 Netherlands In-Store Analytics Market, By Application
13.3.3.11.4 Netherlands In-Store Analytics Market, By Organization Size
13.3.3.12 Switzerland
13.3.3.12.1 Switzerland In-Store Analytics Market, By Component
13.3.3.12.2 Switzerland In-Store Analytics Market, By Deployment Mode
13.3.3.12.3 Switzerland In-Store Analytics Market, By Application
13.3.3.12.4 Switzerland In-Store Analytics Market, By Organization Size
13.3.3.13 Austria
13.3.3.13.1 Austria In-Store Analytics Market, By Component
13.3.3.13.2 Austria In-Store Analytics Market, By Deployment Mode
13.3.3.13.3 Austria In-Store Analytics Market, By Application
13.3.3.13.4 Austria In-Store Analytics Market, By Organization Size
13.3.3.14 Rest of Western Europe
13.3.3.14.1 Rest of Western Europe In-Store Analytics Market, By Component
13.3.3.14.2 Rest of Western Europe In-Store Analytics Market, By Deployment Mode
13.3.3.14.3 Rest of Western Europe In-Store Analytics Market, By Application
13.3.3.14.4 Rest of Western Europe In-Store Analytics Market, By Organization Size
13.4 Asia-Pacific
13.4.1 Trend Analysis
13.4.2 Asia-Pacific In-Store Analytics Market, by Country
13.4.3 Asia-Pacific In-Store Analytics Market, By Component
13.4.4 Asia-Pacific In-Store Analytics Market, By Deployment Mode
13.4.5 Asia-Pacific In-Store Analytics Market, By Application
13.4.6 Asia-Pacific In-Store Analytics Market, By Organization Size
13.4.7 China
13.4.7.1 China In-Store Analytics Market, By Component
13.4.7.2 China In-Store Analytics Market, By Deployment Mode
13.4.7.3 China In-Store Analytics Market, By Application
13.4.7.4 China In-Store Analytics Market, By Organization Size
13.4.8 India
13.4.8.1 India In-Store Analytics Market, By Component
13.4.8.2 India In-Store Analytics Market, By Deployment Mode
13.4.8.3 India In-Store Analytics Market, By Application
13.4.8.4 India In-Store Analytics Market, By Organization Size
13.4.9 Japan
13.4.9.1 Japan In-Store Analytics Market, By Component
13.4.9.2 Japan In-Store Analytics Market, By Deployment Mode
13.4.9.3 Japan In-Store Analytics Market, By Application
13.4.9.4 Japan In-Store Analytics Market, By Organization Size
13.4.10 South Korea
13.4.10.1 South Korea In-Store Analytics Market, By Component
13.4.10.2 South Korea In-Store Analytics Market, By Deployment Mode
13.4.10.3 South Korea In-Store Analytics Market, By Application
13.4.10.4 South Korea In-Store Analytics Market, By Organization Size
13.4.11 Vietnam
13.4.11.1 Vietnam In-Store Analytics Market, By Component
13.4.11.2 Vietnam In-Store Analytics Market, By Deployment Mode
13.4.11.3 Vietnam In-Store Analytics Market, By Application
13.4.11.4 Vietnam In-Store Analytics Market, By Organization Size
13.4.12 Singapore
13.4.12.1 Singapore In-Store Analytics Market, By Component
13.4.12.2 Singapore In-Store Analytics Market, By Deployment Mode
13.4.12.3 Singapore In-Store Analytics Market, By Application
13.4.12.4 Singapore In-Store Analytics Market, By Organization Size
13.4.13 Australia
13.4.13.1 Australia In-Store Analytics Market, By Component
13.4.13.2 Australia In-Store Analytics Market, By Deployment Mode
13.4.13.3 Australia In-Store Analytics Market, By Application
13.4.13.4 Australia In-Store Analytics Market, By Organization Size
13.4.14 Rest of Asia-Pacific
13.4.14.1 Rest of Asia-Pacific In-Store Analytics Market, By Component
13.4.14.2 Rest of Asia-Pacific In-Store Analytics Market, By Deployment Mode
13.4.14.3 Rest of Asia-Pacific In-Store Analytics Market, By Application
13.4.14.4 Rest of Asia-Pacific In-Store Analytics Market, By Organization Size
13.5 Middle East & Africa
13.5.1 Trend Analysis
13.5.2 Middle East
13.5.2.1 Middle East In-Store Analytics Market, by Country
13.5.2.2 Middle East In-Store Analytics Market, By Component
13.5.2.3 Middle East In-Store Analytics Market, By Deployment Mode
13.5.2.4 Middle East In-Store Analytics Market, By Application
13.5.2.5 Middle East In-Store Analytics Market, By Organization Size
13.5.2.6 UAE
13.5.2.6.1 UAE In-Store Analytics Market, By Component
13.5.2.6.2 UAE In-Store Analytics Market, By Deployment Mode
13.5.2.6.3 UAE In-Store Analytics Market, By Application
13.5.2.6.4 UAE In-Store Analytics Market, By Organization Size
13.5.2.7 Egypt
13.5.2.7.1 Egypt In-Store Analytics Market, By Component
13.5.2.7.2 Egypt In-Store Analytics Market, By Deployment Mode
13.5.2.7.3 Egypt In-Store Analytics Market, By Application
13.5.2.7.4 Egypt In-Store Analytics Market, By Organization Size
13.5.2.8 Saudi Arabia
13.5.2.8.1 Saudi Arabia In-Store Analytics Market, By Component
13.5.2.8.2 Saudi Arabia In-Store Analytics Market, By Deployment Mode
13.5.2.8.3 Saudi Arabia In-Store Analytics Market, By Application
13.5.2.8.4 Saudi Arabia In-Store Analytics Market, By Organization Size
13.5.2.9 Qatar
13.5.2.9.1 Qatar In-Store Analytics Market, By Component
13.5.2.9.2 Qatar In-Store Analytics Market, By Deployment Mode
13.5.2.9.3 Qatar In-Store Analytics Market, By Application
13.5.2.9.4 Qatar In-Store Analytics Market, By Organization Size
13.5.2.10 Rest of Middle East
13.5.2.10.1 Rest of Middle East In-Store Analytics Market, By Component
13.5.2.10.2 Rest of Middle East In-Store Analytics Market, By Deployment Mode
13.5.2.10.3 Rest of Middle East In-Store Analytics Market, By Application
13.5.2.10.4 Rest of Middle East In-Store Analytics Market, By Organization Size
13.5.3 Africa
13.5.3.1 Africa In-Store Analytics Market, by Country
13.5.3.2 Africa In-Store Analytics Market, By Component
13.5.3.3 Africa In-Store Analytics Market, By Deployment Mode
13.5.3.4 Africa In-Store Analytics Market, By Application
13.5.3.5 Africa In-Store Analytics Market, By Organization Size
13.5.3.6 Nigeria
13.5.3.6.1 Nigeria In-Store Analytics Market, By Component
13.5.3.6.2 Nigeria In-Store Analytics Market, By Deployment Mode
13.5.3.6.3 Nigeria In-Store Analytics Market, By Application
13.5.3.6.4 Nigeria In-Store Analytics Market, By Organization Size
13.5.3.7 South Africa
13.5.3.7.1 South Africa In-Store Analytics Market, By Component
13.5.3.7.2 South Africa In-Store Analytics Market, By Deployment Mode
13.5.3.7.3 South Africa In-Store Analytics Market, By Application
13.5.3.7.4 South Africa In-Store Analytics Market, By Organization Size
13.5.3.8 Rest of Africa
13.5.3.8.1 Rest of Africa In-Store Analytics Market, By Component
13.5.3.8.2 Rest of Africa In-Store Analytics Market, By Deployment Mode
13.5.3.8.3 Rest of Africa In-Store Analytics Market, By Application
13.5.3.8.4 Rest of Africa In-Store Analytics Market, By Organization Size
13.6 Latin America
13.6.1 Trend Analysis
13.6.2 Latin America In-Store Analytics Market, by country
13.6.3 Latin America In-Store Analytics Market, By Component
13.6.4 Latin America In-Store Analytics Market, By Deployment Mode
13.6.5 Latin America In-Store Analytics Market, By Application
13.6.6 Latin America In-Store Analytics Market, By Organization Size
13.6.7 Brazil
13.6.7.1 Brazil In-Store Analytics Market, By Component
13.6.7.2 Brazil In-Store Analytics Market, By Deployment Mode
13.6.7.3 Brazil In-Store Analytics Market, By Application
13.6.7.4 Brazil In-Store Analytics Market, By Organization Size
13.6.8 Argentina
13.6.8.1 Argentina In-Store Analytics Market, By Component
13.6.8.2 Argentina In-Store Analytics Market, By Deployment Mode
13.6.8.3 Argentina In-Store Analytics Market, By Application
13.6.8.4 Argentina In-Store Analytics Market, By Organization Size
13.6.9 Colombia
13.6.9.1 Colombia In-Store Analytics Market, By Component
13.6.9.2 Colombia In-Store Analytics Market, By Deployment Mode
13.6.9.3 Colombia In-Store Analytics Market, By Application
13.6.9.4 Colombia In-Store Analytics Market, By Organization Size
13.6.10 Rest of Latin America
13.6.10.1 Rest of Latin America In-Store Analytics Market, By Component
13.6.10.2 Rest of Latin America In-Store Analytics Market, By Deployment Mode
13.6.10.3 Rest of Latin America In-Store Analytics Market, By Application
13.6.10.4 Rest of Latin America In-Store Analytics Market, By Organization Size
14. Company Profiles
14.1 Happiest Minds
14.1.1 Company Overview
14.1.2 Financial
14.1.3 Products/ Services Offered
14.1.4 SWOT Analysis
14.1.5 The SNS View
14.2 SAP SE
14.2.1 Company Overview
14.2.2 Financial
14.2.3 Products/ Services Offered
14.2.4 SWOT Analysis
14.2.5 The SNS View
14.3 RETAILNEXT, INC.
14.3.1 Company Overview
14.3.2 Financial
14.3.3 Products/ Services Offered
14.3.4 SWOT Analysis
14.3.5 The SNS View
14.4 Capillary Technologies
14.4.1 Company Overview
14.4.2 Financial
14.4.3 Products/ Services Offered
14.4.4 SWOT Analysis
14.4.5 The SNS View
14.5 Scanalytics Inc.
14.5.1 Company Overview
14.5.2 Financial
14.5.3 Products/ Services Offered
14.5.4 SWOT Analysis
14.5.5 The SNS View
14.6 Celect Inc.
14.6.1 Company Overview
14.6.2 Financial
14.6.3 Products/ Services Offered
14.6.4 SWOT Analysis
14.6.5 The SNS View
14.7 Dor Technologies Inc.
14.7.1 Company Overview
14.7.2 Financial
14.7.3 Products/ Services Offered
14.7.4 SWOT Analysis
14.7.5 The SNS View
14.8 SEMSEYE
14.8.1 Company Overview
14.8.2 Financial
14.8.3 Products/ Services Offered
14.8.4 SWOT Analysis
14.8.5 The SNS View
14.9 Inpixon
14.9.1 Company Overview
14.9.2 Financial
14.9.3 Products/ Services Offered
14.9.4 SWOT Analysis
14.9.5 The SNS View
14.10 Mindtree Ltd.
14.10.1 Company Overview
14.10.2 Financial
14.10.3 Products/ Services Offered
14.10.4 SWOT Analysis
14.10.5 The SNS View
15. Competitive Landscape
15.1 Competitive Benchmarking
15.2 Market Share Analysis
15.3 Recent Developments
15.3.1 Industry News
15.3.2 Company News
15.3.3 Mergers & Acquisitions
16. Use Case and Best Practices
17. Conclusion
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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.
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