Retail Intelligence: Innovations in Retail Analytics Technology Manufacturers and Global Industry Analysis by 2031 | Cisco Systems Inc., MicroStrategy, Inc.

Retail Analytics helps retailers to analyze customer behavior and purchasing patterns by tracking their website visits and browsing history. It enables retailers to offer personalized recommendations and promotions.

Market Dynamics:

Rising need for personalized customer experience is a major factor driving growth of the retail analytics market. Retail analytics helps retailers to gain deep customer insights which help them provide a customized experience. It allows retailers to target customers with tailored recommendations, personalized discounts, and customized content. Additionally, increasing adoption of advanced technologies such as AI, machine learning and predictive analytics is also fueling market growth. These technologies help retailers to make accurate demand forecasts, optimize pricing decisions, enhance supply chain efficiencies and devise effective marketing strategies.

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Major Market Drivers for Retail Analytics Market

Increased Focus on Customer Retention and Personalization

With the increased competition in the retail industry, retailers are focusing more on customer retention by providing personalized shopping experience. Retail analytics helps retailers understand customer purchasing patterns, preferences and predict future purchases. This helps retailers provide better recommendations, targeted promotions and a customized shopping experience. By having insights into customer behavior, retailers can develop strong customer loyalty and improve retention rates.

Key Company Profiles:

he key players operating in the global retail analytics market include IBM Corporation, Microsoft Corporation, Oracle Corporation, SAP SE, Adobe Systems Incorporated, SAS Institute Inc., HCL Technologies Ltd., Cisco Systems Inc., MicroStrategy, Inc., and Tableau Software, Inc. The major players of the market such as IBM Corporation, Microsoft, and Oracle Corporation are adopting strategies such as mergers and acquisitions for product development, in order to retain the position in the market. For instance, in December 2014, Oracle Corporation introduced the Oracle Retail Merchandising Analytics 14.1 version, which helps the retailers to improve their business performance by leveraging the real data collected from the consumers.

Market segmentation:

On the basis of component type, the global retail analytics market is segmented into:

Software
Services
On the basis of deployment model, the global retail analytics market is segmented into:

On-Premises
On-Demand
On the basis of organization size, the global retail analytics market is segmented into:

SMEs (Small and Medium Enterprises)
Large Enterprises
On the basis of application, the global retail analytics market is segmented into:

Merchandising Analysis
Customer Analysis
Performance Analysis
Inventory Analysis
Others
Key Region/Countries are Classified as Follows:

» North America (U.S., Canada, Mexico)
» Europe (Germany, U.K., France, Italy, Russia, Spain, Rest of Europe)
» Asia-Pacific (China, India, Japan, Singapore, Australia, New Zealand, Rest of APAC)
» South America (Brazil, Argentina, Rest of SA)
» Middle East & Africa (Turkey, Saudi Arabia, Iran, UAE, Africa, Rest of MEA)



Growing Emphasis on Omnichannel Retailing

Customers now research products online and make purchases both in-store and online. This has increased the need for omnichannel retailing where retailers provide a seamless shopping experience across all channels. Retail analytics assists retailers in gaining a unified view of customer transactions and behavior across channels. It helps track customers as they move from online to offline and vice-versa. This allows retailers to provide consistent personalized experiences, manage inventory across all channels and optimize supply chain.

Major Market Restrain for Retail Analytics Market

Data Privacy and Security Concerns

With a massive amount of customer data being collected and analyzed, data privacy has become a major concern. Customers are worried about how their personal data is being stored, shared and used. Any data breach can damage customer trust and brand reputation. Retailers need to ensure high-level security for customer data and be transparent about data usage. Difficulty in accessing and integrating data from various sources within the organization due to platform constraints or legacy systems is another challenge. Retailers have to overcome these barriers to gain customer acceptance for retail analytics programs.

Major Market Opportunity for Retail Analytics Market

Adoption of AI and Machine Learning Technologies

Artificial Intelligence (AI) and Machine Learning (ML) are increasingly being used in retail analytics to gain deeper consumer insights. Technologies like neural networks, computer vision and predictive analytics help retailers make data-driven decisions. AI assists in automating repetitive tasks, identifying patterns, making predictions and personalized recommendations. It also helps optimize pricing strategies. As AI/ML solutions advance further, their adoption in retail analytics is expected to accelerate in the coming years. This will open up new opportunities for analytics vendors as well as help retailers maximize ROI from analytics investments.

Major Market Trend for Retail Analytics Market

Emergence of Edge Computing and IoT

Edge computing is a trend where processing of data is moved closer to the data source i.e. at the edge of the network rather than in a centralized data center. This reduces response times and bandwidth usage. In retail, edge devices such as sensors, cameras, POS systems and digital signages generate huge volumes of data in stores. Edge analytics processes this data locally to gain insights for applications like predictive maintenance, inventory management, planogram compliance etc. Combined with IoT, edge analytics helps optimize in-store operations and customer engagement. This trend is allowing retailers to unlock value from store-level data in real-time.



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Some of the Major Points of TOC cover:

Chapter 1: Techniques & Scope

1.1Definition and forecast parameters
1.2Methodology and forecast parameters
1.3 Information Sources

Chapter 2: Latest Trends Summary

2.1 Regional trends
2.2 Product trends
2.3 End-use trends
2.4 Business trends

Chapter 3: Industry Insights

3.1 Industry fragmentation
3.2 Industry landscape
3.3 Vendor matrix
3.4 Technological and Innovative Landscape

Chapter 4: Retail Analytics Market , By Region

Chapter 5: Company Profiles

5.1 Overview of the Company

5.2 Economic components

5.3 Product Overview

5.4 Analysis of Strengths and Weaknesses

5.5 Methodical Outlook

Chapter 6: Assumptions and Acronyms

Chapter 7: Research Methodology

Chapter 8: Contact (Continue . . .)

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