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Global In-Store Analytics Market to reach USD 7.36 billion by 2027.

Global In-Store Analytics Market Size study, by Components (Software, Services) by Application (Marketing Management, Customer Management, Merchandising Analysis, Store Operations Management, Risk and Compliance Management) by Deployment Model (On-premises, Cloud) by Organization Size (SME’s, Large Enterprises) and Regional Forecasts 2021-2027

Product Code: ICTICTS-88568783
Publish Date: 15-08-2021
Page: 200

Global In-Store Analytics Market is valued approximately USD 1.68 billion in 2020 and is anticipated to grow with a healthy growth rate of more than 23.5% over the forecast period 2021-2027. In-Store Analytics refers to the process of gaining meaningful insights of data from the customers’ behavioral attributes. This data gives the information ranging from demographics to age to gender of the customer. This information, after being processed, helps provide the consumers, retailers and buyers an enhanced shopping experience and optimized store layout for the same. Increasing need towards better customer service and increasing shopping experience and maintenance of huge data volumes are factors contributing to the market growth. For instance, according to the U.S Census Bureau, the United States’ retail sales went up by 0.3% in January 2020, thus, with an increase in the sales in the retail store there was an increase in the data volume to be recorded systematically. Thus in order to have a free flow of customer’s database there leads an increasing demand of the Analytics. However, lack of skilled professionals impedes the growth of the market over the forecast period of 2021-2027. Also, increasing awareness towards optimizing store performance is likely to increase the growth of the market in the forecasting period.

The regional analysis of global In-Store Analytics market when considering for the key regions such as Asia Pacific, North America, Europe, Latin America and Rest of the World has led to the analysis that North America is a significant region across the world in terms of market share owing to rapid adoption of in-store analytics solutions coupled with established developed countries in the region Whereas, Europe is anticipated to exhibit the highest growth rate over the forecast period 2021-2027. Factors such as increased technological improvements coupled with research and development initiatives by the firms would create lucrative growth prospects for the In-Store Analytics market across Asia-Pacific region.

Major market player included in this report are:
Retail Solutions
Think inside
Happiest Minds
Capillary Technologies
Scan Analytics

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 Components:
By Application:
Marketing Management
Customer Management
Merchandising Analysis
Store Operations Management
Risk and Compliance Management

By Deployment Model:

By Organization Size:
Large Enterprises

By Region:
North America

Asia Pacific
South Korea
Latin America
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 In-Store 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

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2027 (USD Billion)
1.2.1. In-Store Analytics Market, by Region, 2019-2027 (USD Billion)
1.2.2. In-Store Analytics Market, by Components, 2019-2027 (USD Billion)
1.2.3. In-Store Analytics Market, by Application, 2019-2027 (USD Billion)
1.2.4. In-Store Analytics Market, by Deployment Model, 2019-2027 (USD Billion)
1.2.5. In-Store Analytics Market, by Organization Size 2019-2027 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global In-Store 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 In-Store Analytics Market Dynamics
3.1. In-Store Analytics Market Impact Analysis (2019-2027)
3.1.1. Market Drivers Increasing need towards better customer service Rising need to maintain huge data volumes
3.1.2. Market Challenges Lack of skilled professionals
3.1.3. Market Opportunities Increasing awareness towards optimizing store performance
Chapter 4. Global In-Store 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 In-Store Analytics Market, by Components
5.1. Market Snapshot
5.2. Global In-Store Analytics Market by Components, Performance – Potential Analysis
5.3. Global In-Store Analytics Market Estimates & Forecasts by Components2018-2027 (USD Billion)
5.4. In-Store Analytics Market, Sub Segment Analysis
5.4.1. Software
5.4.2. Services
Chapter 6. Global In-Store Analytics Market, by Application
6.1. Market Snapshot
6.2. Global In-Store Analytics Market by Application, Performance – Potential Analysis
6.3. Global In-Store Analytics Market Estimates & Forecasts by Application 2018-2027 (USD Billion)
6.4. In-Store Analytics Market, Sub Segment Analysis
6.4.1. Marketing Management
6.4.2. Customer Management
6.4.3. Merchandising Analysis
6.4.4. Store Operations Management
6.4.5. Risk and Compliance Management
Chapter 7. Global In-Store Analytics Market, by Deployment Model
7.1. Market Snapshot
7.2. Global In-Store Analytics Market by Deployment Model Performance – Potential Analysis
7.3. Global In-Store Analytics Market Estimates & Forecasts by Deployment Model 2018-2027 (USD Billion)
7.4. In-Store Analytics Market, Sub Segment Analysis
7.4.1. On-premises
7.4.2. Cloud
Chapter 8. Global In-Store Analytics Market, by Organization Size
8.1. Market Snapshot
8.2. Global In-Store Analytics Market by Organization Size, Performance – Potential Analysis
8.3. Global In-Store Analytics Market Estimates & Forecasts by Organization Size 2018-2027 (USD Billion)
8.4. In-Store Analytics Market, Sub Segment Analysis
8.4.1. SME’s
8.4.2. Large Enterprises
Chapter 9. Global In-Store Analytics Market, Regional Analysis
9.1. In-Store Analytics Market, Regional Market Snapshot
9.2. North America In-Store Analytics Market
9.2.1. U.S. In-Store Analytics Market Component breakdown estimates & forecasts, 2018-2027 Application breakdown estimates & forecasts, 2018-2027 Deployment Model breakdown estimates & forecasts, 2018-2027 Organization Size breakdown estimates & forecasts, 2018-2027
9.2.2. Canada In-Store Analytics Market
9.3. Europe In-Store Analytics Market Snapshot
9.3.1. U.K. In-Store Analytics Market
9.3.2. Germany In-Store Analytics Market
9.3.3. France In-Store Analytics Market
9.3.4. Spain In-Store Analytics Market
9.3.5. Italy In-Store Analytics Market
9.3.6. Rest of Europe In-Store Analytics Market
9.4. Asia-Pacific In-Store Analytics Market Snapshot
9.4.1. China In-Store Analytics Market
9.4.2. India In-Store Analytics Market
9.4.3. Japan In-Store Analytics Market
9.4.4. Australia In-Store Analytics Market
9.4.5. South Korea In-Store Analytics Market
9.4.6. Rest of Asia Pacific In-Store Analytics Market
9.5. Latin America In-Store Analytics Market Snapshot
9.5.1. Brazil In-Store Analytics Market
9.5.2. Mexico In-Store Analytics Market
9.6. Rest of The World In-Store Analytics Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. Retail Solutions Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
10.2.2. RetailNext
10.2.3. SAP
10.2.4. Think inside
10.2.5. Mindtree
10.2.6. Happiest Minds
10.2.7. CELECT
10.2.8. Capillary Technologies
10.2.9. Scan Analytics
10.2.10. INPIXON
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

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Data Collection:
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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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