Retail Analytics Market by Component, Business Function, Deployment Model, Retail Store Type, Application, End User

List of Tables

[189 Pages Report] The Retail Analytics Market size was estimated at USD 8.01 billion in 2023 and expected to reach USD 9.37 billion in 2024, at a CAGR 17.69% to reach USD 25.06 billion by 2030.

Retail analytics involves the process of providing analytical data on inventory levels, supply chain movement, consumer demand, and sales, which is crucial for making critical decisions within the retail sector. It uses a mix of statistical analysis, predictive modeling, and data-mining tools to understand and enhance retail operations significantly, aiming to maximize sales and minimize costs. Increased E-commerce adoption with the surge in online shopping that produces vast amounts of data is creating a platform for the retail analytics market. The blending of online and offline sales channels necessitates a more integrated approach to data analysis to ensure consistent and effective customer engagement across all platforms. Data privacy and security concerns with the usage of retail analytics solutions hampers the market growth. The integration of advanced analytics, AI, and machine learning technologies that enable more sophisticated data analysis and provide deeper insights for retailers are expected to create opportunities for market growth.

KEY MARKET STATISTICS
Base Year [2023]	USD 8.01 billion
Estimated Year [2024]	USD 9.37 billion
Forecast Year [2030]	USD 25.06 billion
CAGR (%)	17.69%

Component: Rising usage of retail analytics that enables the collection, processing, and analysis of data generated in the retail sector

In the retail analytics, services pertain to various support and activities provided by firms to retailers, aiming to enhance their data analysis capabilities. These services are crucial for retailers to make informed decisions, optimize operations, and improve customer satisfaction. Managed services is the outsourcing of certain tasks or operations related to retail analytics. Providers of managed services take on the responsibility of monitoring, managing, and analyzing data on behalf of the retailer. This option is suitable for retailers that focuses on their vital business activities while leaving the complex data management tasks to specialized companies. Professional services include specialized support such as consultation, implementation, and training related to retail analytics solutions. These services are offered by experts who guide retailers on how to effectively utilize analytics tools, interpret data, and apply insights to achieve business goals. Whether it's integrating new software or optimizing existing analytics strategies, professional services play a key role in enhancing a retailer's analytical capabilities. In retail analytics, software enables the processing, collection, and analysis of huge amounts of data generated in the retail sector. This software provides insights into customer behavior, sales performance, inventory management, and more. It ranges from simple dashboard tools for data visualization to complex machine learning algorithms for predictive analytics. The right software can transform raw data into actionable insights, helping retailers to make smarter decisions, forecast trends, and tailor their offerings to meet customer needs effectively.

Deployment Model: High potential for on-cloud deployment due to its flexibility, scalability, and ease of access

On-cloud, also known as cloud-based deployment, means that the retail analytics software and data are hosted on the service provider's remote servers. Users access these services over the Internet. This model is known for its flexibility, scalability, and ease of access. Notably, it allows retail businesses of all sizes to leverage powerful analytics tools without the need for substantial hardware investments or an extensive IT staff. The data management, software updates, and infrastructure maintenance are handled by the service provider, ensuring that the system is always up-to-date and secure. The on-premises deployment model involves installing the retail analytics software directly on the company's own servers and computers. This approach gives businesses complete control over their data and analytics tools, allowing for customized security measures and integration with existing systems. On-premises deployment is often chosen by organizations that have strict data security requirements or those that prefer to manage all aspects of their IT infrastructure. While offering higher levels of control and potentially enhanced security, this model requires significant upfront investment in hardware, software licenses, and an IT team capable of managing and maintaining the system. Additionally, updates and scaling require additional resources and time.

Regional Insights

In the Americas, retail analytics solutions have a significant adoption with a strong emphasis on enhancing customer experience, streamlining operations, and employing advanced technologies, including AI and ML, to understand consumer behavior better. Retailers in these countries are investing in analytics tools to forecast trends, manage inventory more effectively, and personalize marketing strategies. South America, with countries including Brazil and Mexico, is increasingly leveraging these solutions and is propelled by digital transformation initiatives. The APAC region is witnessing rapid growth in retail analytics, fueled by its vast population and the rising middle class, especially in countries such as China, India, and Southeast Asia. The surge in online shopping, mobile penetration, and digital payments pushes retailers to adopt analytics solutions to optimize their online and offline strategies. The focus here is on understanding consumer patterns, optimizing supply chains, and enhancing customer engagement through data. The diversity of the APAC market, with its varied consumer preferences and behaviors, makes analytics an essential tool for retailers operating in this region. In Europe, there's a strong focus on compliance and data protection and the need to enhance customer satisfaction and operational efficiency. Retailers are leveraging analytics to gain insights into customer preferences and streamline their operations, aligning with GDPR (General Data Protection Regulation) guidelines. The Middle East is witnessing a digital transformation, with countries including the UAE and Saudi Arabia leading the adoption of retail analytics to enhance customer experiences and integrate online and offline retail channels. Africa shows promise, particularly in South Africa and Nigeria, driven by increasing internet and smartphone penetration.

FPNV Positioning Matrix

The FPNV Positioning Matrix is pivotal in evaluating the Retail Analytics Market. It offers a comprehensive assessment of vendors, examining key metrics related to Business Strategy and Product Satisfaction. This in-depth analysis empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital (V).

Market Share Analysis

The Market Share Analysis is a comprehensive tool that provides an insightful and in-depth examination of the current state of vendors in the Retail Analytics Market. By meticulously comparing and analyzing vendor contributions in terms of overall revenue, customer base, and other key metrics, we can offer companies a greater understanding of their performance and the challenges they face when competing for market share. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With this expanded level of detail, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.

Key Company Profiles

The report delves into recent significant developments in the Retail Analytics Market, highlighting leading vendors and their innovative profiles. These include 1010data, Inc. by SymphonyAI LLC, Amazon Web Services, Inc., Amazon.com, Inc., Analytics8, LLC, CARTO, DataWeave Software Private Limited, Domo, Inc., Fractal Analytics Inc., Fujitsu Limited, Google, LLC by Alphabet Inc., HCL Technologies Ltd., Intelligence Node, International Business Machines Corporation, LatentView Analytics, Microsoft Corporation, MicroStrategy Incorporated, Oracle Corporation, QlikTech International AB, RetailNext Inc., Salesforce, Inc., SAP SE, Sisense Ltd., Standard Cognition, Corp., Teledyne FLIR LLC, and Teradata Corporation.

Market Segmentation & Coverage

This research report categorizes the Retail Analytics Market to forecast the revenues and analyze trends in each of the following sub-markets:

Component
- Services
  - Managed Services
  - Professional Services

Software

Business Function
- Finance
- Human Resources
- Marketing & Sales
- Operations

Deployment Model
- On-Cloud
- On-Premise

Retail Store Type
- Convenience Stores
- Department Stores
- Supermarkets & Grocery Stores

Application
- Customer Management
- Inventory Analysis
- Merchandising Analysis
- Performance Analysis
- Pricing Analysis
- Promotional Analysis & Planning

End User
- Offline
- Online

Region
- Americas
  - Argentina
  - Brazil
  - Canada
  - Mexico
  - United States
    - California
    - Florida
    - Illinois
    - New York
    - Ohio
    - Pennsylvania
    - Texas
- Asia-Pacific
  - Australia
  - China
  - India
  - Indonesia
  - Japan
  - Malaysia
  - Philippines
  - Singapore
  - South Korea
  - Taiwan
  - Thailand
  - Vietnam

Europe, Middle East & Africa
- Denmark
- Egypt
- Finland
- France
- Germany
- Israel
- Italy
- Netherlands
- Nigeria
- Norway
- Poland
- Qatar
- Russia
- Saudi Arabia
- South Africa
- Spain
- Sweden
- Switzerland
- Turkey
- United Arab Emirates
- United Kingdom

The report offers valuable insights on the following aspects:

1. Market Penetration: It presents comprehensive information on the market provided by key players.

2. Market Development: It delves deep into lucrative emerging markets and analyzes the penetration across mature market segments.

3. Market Diversification: It provides detailed information on new product launches, untapped geographic regions, recent developments, and investments.

4. Competitive Assessment & Intelligence: It conducts an exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players.

5. Product Development & Innovation: It offers intelligent insights on future technologies, R&D activities, and breakthrough product developments.

The report addresses key questions such as:

1. What is the market size and forecast of the Retail Analytics Market?

2. Which products, segments, applications, and areas should one consider investing in over the forecast period in the Retail Analytics Market?

3. What are the technology trends and regulatory frameworks in the Retail Analytics Market?

4. What is the market share of the leading vendors in the Retail Analytics Market?

5. Which modes and strategic moves are suitable for entering the Retail Analytics Market?

Product Code: MRR-035AB9C0DADC

1. Preface

1.1. Objectives of the Study
1.2. Market Segmentation & Coverage
1.3. Years Considered for the Study
1.4. Currency & Pricing
1.5. Language
1.6. Stakeholders

2. Research Methodology

2.1. Define: Research Objective
2.2. Determine: Research Design
2.3. Prepare: Research Instrument
2.4. Collect: Data Source
2.5. Analyze: Data Interpretation
2.6. Formulate: Data Verification
2.7. Publish: Research Report
2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

5.1. Market Dynamics
- 5.1.1. Drivers
  - 5.1.1.1. Growing consumer demand for quick and streamlined retail services
  - 5.1.1.2. Government initiatives to digitize retail infrastructure across the world
  - 5.1.1.3. Increasing eCommerce adoption among retailers
- 5.1.2. Restraints
  - 5.1.2.1. Complexities of integration of retail analytics technologies and performance issues
- 5.1.3. Opportunities
  - 5.1.3.1. Ongoing advancements to improve the functionality and efficiency of retail analytics technologies
  - 5.1.3.2. Rising investments to expand smart city and smart store operations
- 5.1.4. Challenges
  - 5.1.4.1. Data privacy and cybersecurity issues with retail analytics
5.2. Market Segmentation Analysis
- 5.2.1. Component: Rising usage of retail analytics that enables the collection, processing, and analysis of data generated in the retail sector
- 5.2.2. Deployment Model: High potential for on-cloud deployment due to its flexibility, scalability, and ease of access
5.3. Market Disruption Analysis
5.4. Porter's Five Forces Analysis
- 5.4.1. Threat of New Entrants
- 5.4.2. Threat of Substitutes
- 5.4.3. Bargaining Power of Customers
- 5.4.4. Bargaining Power of Suppliers
- 5.4.5. Industry Rivalry
5.5. Value Chain & Critical Path Analysis
5.6. Pricing Analysis
5.7. Technology Analysis
5.8. Patent Analysis
5.9. Trade Analysis
5.10. Regulatory Framework Analysis

6. Retail Analytics Market, by Component

6.1. Introduction
6.2. Services
6.3. Software

7. Retail Analytics Market, by Business Function

7.1. Introduction
7.2. Finance
7.3. Human Resources
7.4. Marketing & Sales
7.5. Operations

8. Retail Analytics Market, by Deployment Model

8.1. Introduction
8.2. On-Cloud
8.3. On-Premise

9. Retail Analytics Market, by Retail Store Type

9.1. Introduction
9.2. Convenience Stores
9.3. Department Stores
9.4. Supermarkets & Grocery Stores

10. Retail Analytics Market, by Application

10.1. Introduction
10.2. Customer Management
10.3. Inventory Analysis
10.4. Merchandising Analysis
10.5. Performance Analysis
10.6. Pricing Analysis
10.7. Promotional Analysis & Planning

11. Retail Analytics Market, by End User

11.1. Introduction
11.2. Offline
11.3. Online

12. Americas Retail Analytics Market

12.1. Introduction
12.2. Argentina
12.3. Brazil
12.4. Canada
12.5. Mexico
12.6. United States

13. Asia-Pacific Retail Analytics Market

13.1. Introduction
13.2. Australia
13.3. China
13.4. India
13.5. Indonesia
13.6. Japan
13.7. Malaysia
13.8. Philippines
13.9. Singapore
13.10. South Korea
13.11. Taiwan
13.12. Thailand
13.13. Vietnam

14. Europe, Middle East & Africa Retail Analytics Market

14.1. Introduction
14.2. Denmark
14.3. Egypt
14.4. Finland
14.5. France
14.6. Germany
14.7. Israel
14.8. Italy
14.9. Netherlands
14.10. Nigeria
14.11. Norway
14.12. Poland
14.13. Qatar
14.14. Russia
14.15. Saudi Arabia
14.16. South Africa
14.17. Spain
14.18. Sweden
14.19. Switzerland
14.20. Turkey
14.21. United Arab Emirates
14.22. United Kingdom

15. Competitive Landscape

15.1. Market Share Analysis, 2023
15.2. FPNV Positioning Matrix, 2023
15.3. Competitive Scenario Analysis
- 15.3.1. Standard AI Elevates Retail with Vision Analytics and Strategic Leadership Transition
- 15.3.2. RetailNext's Strategic Innovations in In-Store Analytics
- 15.3.3. Intelligence Node's Partnership with Kroger Marketplace
15.4. Strategy Analysis & Recommendation

16. Competitive Portfolio

16.1. Key Company Profiles
16.2. Key Product Portfolio