Retail Analytics Market to USD 45.4 Billion by 2032| SNS Insider
The Retail Analytics Market, valued at USD 8.0 Bn in 2023, is projected to reach USD 45.4 Bn by 2032, growing at a 21.31% CAGR from 2024-2032 (SNS Insider).
AUSTIN, TX, UNITED STATES, February 11, 2025 /EINPresswire.com/ -- The SNS Insider report indicates that the Retail Analytics Market size was valued at USD 8.0 billion in 2023 and is expected to grow to USD 45.4 billion by 2032, expanding at a CAGR of 21.31% over the forecast period of 2024-2032. The growing need for real-time data analytics, personalized shopping experiences, and efficient supply chain management has fueled the market’s expansion.Get Sample Copy of Report: https://www.snsinsider.com/sample-request/2913
Some of Major Keyplayers:
- 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
By Deployment: Cloud Dominates, On-Premise Registers Fastest CAGR
The cloud segment dominated the market and accounted for a significant revenue share in 2023, owing to the scalability, affordability, and real-time accessibility to data provided by it. To enable easy integration with existing business processes, retailers are increasingly resorting to cloud-based solutions. In addition, the use of cloud analytics also provides AI-based insights and predictive modeling which helps businesses to keep up with the trends in consumer behaviors.
The on-premise segment is expected to register the fastest CAGR during the forecast period. Although-retailers at every level have embraced the cloud, larger enterprises still gravitate toward on-premise solutions because they offer more control over data as well as security and compliance with rigid regulatory standards. Due to the growing attention of analysts, the requirement for on-premise analytics is likely to increase, with a focus on data privacy along with localized storage.
By Retail Store Type: Retail Chains Lead, Hypermarkets and Supermarkets Grow Fastest
The retail chains segment led the market due to the wide scale implementation of advanced analytics solutions for customer engagement, inventory management, and marketing optimization. The large retail chains benefit from using AI-based analytics to study what consumers are doing, coming up with better pricing, and optimizing supply chain dynamics.
The hypermarkets and supermarkets segment is expected to grow at the fastest rate in terms of terms of the CAGR on account of the rising need for accurate and real-time information that includes inventory tracking, demand forecasting, and personalized recommendations of choices made by customers As smart checkout systems and AI-driven shopping assistants grow in popularity, supermarkets are leveraging analytics to boost efficiency in operations.
By Function: Customer Management Leads, In-Store Operations Sees Fastest Growth
Customer management dominated the market and accounted for significant revenue share in 2023, being pushed by the retailers to achieve excellence in customer experience and engagement through personalized interactions. By utilizing AI–driven analytics, retailers gain insight into customer preferences and purchasing patterns, enabling them to offer targeted promotions and ultimately drive customer retention and more sales.
The in-store operations segment is expected to register the fastest CAGR, Driven by Automation, IoT-enabled retail solutions, and AI-based workforce management. With real-time data analytics, retailers have employed their analytics to discover the best store layouts and foot traffic as well as customer interactions to optimize flow, which has made the usage of capital significantly better.
Retail Analytics Market Segmentation:
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
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North America Leads the Retail Analytics Market while Asia-Pacific Registers the Fastest Growth
North America dominated the market and accounted for the largest market share of around 39% in 2023, early adoption of AI-driven analytics solutions, the presence of the largest retail giants, and a large emphasis on customer experience are some of the major contributing factors that to the region maintains its lead. This has also boosted the demand for real-time analytics due to the well-established retail infrastructure and deep e-commerce penetration in the region.
The Asia-Pacific region is projected to see the fastest CAGR during the forecast period, The rising e-commerce sector, and growing smartphone penetration alongside continuous retail transformation through digitalization. Through AI-powered analytics, retailers are adopting data-driven insight in emerging regions like China, India, and Japan to engage with consumers better and manage their inventories efficiently. An increasing proportion of the middle-class population with higher disposable income further adds fuel to the demand for data-driven retail solutions in the region.
Recent Developments in the Retail Analytics Market
- January 2024: Oracle launched an upgraded version of its Retail AI and Data Analytics Platform, enhancing predictive capabilities for retailers.
- February 2024: Microsoft partnered with a leading global retail chain to integrate AI-driven analytics into its supply chain and customer management operations.
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Table of Content:
1. Introduction
2. Executive Summary
3. Research Methodology
4. Market Dynamics Impact Analysis
5. Statistical Insights and Trends Reporting
6. Competitive Landscape
7. Retail Analytics Market Segmentation, By Deployment
8. Retail Analytics Market Segmentation, by Retail Store Type
9. Retail Analytics Market Segmentation, by Function
10. Regional Analysis
11. Company Profiles
12. Use Cases and Best Practices
13. Conclusion
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