Retail Analytics Market Size and Outlook 2031

Report Description

Forecast Period	2027-2031
Market Size (2025)	USD 8.73 Billion
CAGR (2026-2031)	19.82%
Fastest Growing Segment	Cloud
Largest Market	North America
Market Size (2031)	USD 25.83 Billion

Market Overview

The Global Retail Analytics Market will grow from USD 8.73 Billion in 2025 to USD 25.83 Billion by 2031 at a 19.82% CAGR. Retail analytics is defined as the systematic processing of inventory, supply chain, and consumer data to optimize pricing, merchandising, and marketing strategies. The market is primarily propelled by the urgent necessity for operational efficiency and the exponential increase in data volume generated through digital channels, which compels retailers to adopt advanced analytical tools for precise decision-making. This shifting landscape is evidenced by the rapid growth of digital commerce; according to the National Retail Federation in 2024, online and other non-store sales are projected to increase between 7% and 9% to a range of $1.47 trillion to $1.50 trillion. Such a surge in digital activity underscores the critical reliance on analytics to interpret complex consumer footprints.

One significant challenge impeding the expansion of the global retail analytics market is the increasing complexity of data privacy regulations and security compliance. Stringent legal frameworks regarding the collection and utilization of consumer information necessitate rigorous governance and transparency standards. These regulatory hurdles often create high implementation barriers and substantial compliance costs, effectively deterring smaller enterprises with limited resources from adopting comprehensive analytics solutions and limiting the scope of data utilization for larger organizations.

Key Market Drivers

The integration of Artificial Intelligence and Machine Learning for predictive analytics acts as a primary catalyst for the Global Retail Analytics Market, fundamentally reshaping decision-making processes. Retailers are increasingly deploying these technologies to synthesize vast datasets, enabling precise demand forecasting and dynamic pricing that directly enhance profitability. This operational shift is delivering measurable financial returns; according to NVIDIA, January 2025, in the 'State of AI in Retail and CPG' report, 87% of retailers indicated that AI had a positive impact on increasing annual revenue. Such quantifiable success is driving widespread adoption, as organizations seek to leverage predictive models for maintaining a competitive edge in a saturated market.

The imperative for supply chain optimization and real-time inventory management further propels market expansion, necessitating advanced analytics to mitigate disruptions and streamline logistics. As consumer expectations for speed and availability rise, retailers are compelled to automate complex operational workflows to ensure stock accuracy and efficiency. This strategic focus is evidenced by substantial investment plans; according to Honeywell, January 2025, in the 'AI in Retail Survey', more than 80% of retailers plan to increase the use of automation and artificial intelligence across their operations to adapt to changing consumer behaviors. The broader market trajectory reflects this prioritization of efficiency, where data-driven strategies are becoming standard practice. According to NVIDIA, in 2025, 94% of retailers reported that AI has helped reduce annual operational costs.

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Key Market Challenges

The increasing complexity of data privacy regulations and security compliance constitutes a primary obstacle restricting the expansion of the Global Retail Analytics Market. As governments worldwide enforce stringent legal frameworks regarding the collection and utilization of consumer information, retailers are compelled to establish rigorous governance and transparency standards. This regulatory pressure diverts critical financial and operational resources away from innovation and the adoption of advanced analytics tools, creating a defensive operational posture. These compliance demands effectively construct high barriers to entry, particularly for smaller enterprises that lack the capital to sustain extensive legal and technical safeguards, thereby reducing the total addressable market for analytics solutions.

The financial magnitude of this hurdle is significant. According to the International Association of Privacy Professionals, in 2024, the average annual privacy budget for organizations rose to approximately $1.75 million. This escalation in non-revenue-generating expenditure forces retailers to consolidate spending on compliance rather than expanding their analytical capabilities. Consequently, the high cost of adherence not only delays the implementation of analytics strategies but also limits the scope of data utilization for larger organizations, directly stalling overall market growth.

Key Market Trends

The Expansion of Retail Media Network Analytics is fundamentally altering the revenue models of major retailers, transforming them into digital advertising publishers that require sophisticated measurement capabilities. As retailers monetize their first-party data, there is a critical need for granular analytics to provide advertisers with closed-loop attribution and verifiable return on ad spend, moving beyond simple sales metrics to deep audience insights. This trend is driving heavy investment in platforms that can track customer journeys across onsite and offsite channels to justify media budgets. The scale of this financial opportunity is rapidly increasing; according to the IAB, April 2025, in the 'Internet Advertising Revenue Report', retail media network advertising revenues rose 23.0% year-over-year to reach $53.7 billion in 2024.

Concurrently, the Integration of Generative AI for Dynamic Content Creation is enabling a shift from static segmented marketing to true real-time hyper-personalization. Unlike traditional predictive models that focus primarily on pricing or stock levels, generative AI allows for the instant creation of unique product descriptions, marketing copy, and visual assets tailored to individual shopper preferences. This capability allows retailers to enhance customer engagement by delivering highly relevant, context-aware interactions at scale, necessitating analytics solutions that can evaluate the performance of AI-generated assets. The widespread commitment to this technology is evident; according to Salesforce, March 2024, in a study conducted with the Retail AI Council, 93% of retailers indicated they are already utilizing generative AI for personalization tasks such as customized email copy and product recommendations.

Segmental Insights

The Cloud segment currently demonstrates the most rapid growth within the Global Retail Analytics Market due to its high scalability and cost efficiency. Retailers are increasingly adopting cloud solutions to avoid the substantial capital costs associated with physical servers and to facilitate instant access to data across multiple locations. This deployment mode supports the seamless consolidation of inventory and customer information, which allows for more agile business strategies. Additionally, cloud platforms provide the necessary flexibility to manage fluctuating data volumes during peak sales periods, ensuring consistent performance without heavy technical maintenance requirements.

Regional Insights

North America maintains a dominant position in the retail analytics market due to the extensive adoption of digital technologies by major enterprises. The United States leads this expansion as retailers increasingly integrate artificial intelligence and cloud computing to optimize supply chains and inventory levels. Additionally, the region benefits from a high concentration of established solution providers that facilitate accessible analytics implementation. This strong infrastructure, combined with a mature e-commerce landscape, encourages businesses to utilize analytics for improved operational efficiency and customer engagement, thereby solidifying North America’s leadership in the global market.

Recent Developments

In September 2024, Salesforce launched Agentforce, a new suite of autonomous AI agents designed to augment employee capabilities across various business functions, including retail service and marketing. Announced at the annual Dreamforce conference of the company, Agentforce allows retailers to deploy agentic AI that can independently analyze data, make decisions, and execute tasks such as resolving customer inquiries or optimizing marketing campaigns. This platform represents a shift from traditional chatbots to more advanced AI that can reason and take action. The launch emphasizes the commitment of Salesforce to integrating deep data analytics with actionable AI to drive efficiency and personalize customer experiences at scale.
In August 2024, Blue Yonder completed the acquisition of One Network Enterprises for an enterprise value of approximately $839 million. This significant move was designed to create a unified, multi-enterprise supply chain ecosystem that facilitates real-time data sharing and collaboration across all trading partners. By integrating the Digital Supply Chain Network from One Network with its own platform, Blue Yonder enhanced its capabilities in providing end-to-end visibility and control. The collaboration enables retailers and manufacturers to mitigate disruptions more effectively through AI-powered predictive analytics and control tower solutions, ensuring greater agility and resilience in their global supply chain operations.
In May 2024, SPS Commerce expanded its portfolio of supply chain solutions by acquiring Traverse Systems, a SaaS platform provider, for approximately $29 million. This strategic acquisition was aimed at enhancing supply chain visibility and collaboration for retailers and suppliers. Traverse Systems specializes in providing unified views of supply chain performance, which complements the existing retail network of SPS Commerce by adding capabilities for scorecarding and vendor performance management. The integration of this technology allows the company to offer more comprehensive data analytics and operational insights, helping trading partners optimize their supply chain efficiency and improve on-time and in-full delivery rates.
In January 2024, Google Cloud unveiled new generative AI and modern analytics capabilities designed to assist retailers in personalizing online shopping and streamlining operations. The technology giant introduced a conversational commerce solution that enables retailers to embed generative AI-powered virtual agents into their websites and mobile applications. These agents can converse with shoppers in natural language and provide tailored product recommendations based on individual preferences. Additionally, Google Cloud launched a new large language model feature for its Vertex AI Search for retail, aimed at improving the relevance and accuracy of product search results for consumers.

Key Market Players

IBM Corporation
SAP SE
Microsoft Corporation
Adobe Inc.
Oracle Corporation
SAS Institute Inc.
Qlik Technologies Inc.
Salesforce Company
Teradata Corporation
MicroStrategy Incorporated
HCL Technologies Limited
Domo Inc.
Information Builders Inc.

By Component	By Deployment Mode	By Application	By Region
Software Vs. Service	Cloud Vs. On-Premises	Merchandising Analytics & Others	North America Europe Asia Pacific South America Middle East & Africa

Report Scope:

In this report, the Global Retail Analytics Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Retail Analytics Market, By Component:

Software Vs. Service

Retail Analytics Market, By Deployment Mode:

Cloud Vs. On-Premises

Retail Analytics Market, By Application:

Merchandising Analytics & Others

Retail Analytics Market, By Region:

North America

United States
Canada
Mexico

Europe

France
United Kingdom
Italy
Germany
Spain

Asia Pacific

China
India
Japan
Australia
South Korea

South America

Brazil
Argentina
Colombia

Middle East & Africa

South Africa
Saudi Arabia
UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Retail Analytics Market.

Available Customizations:

Global Retail Analytics Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

Detailed analysis and profiling of additional market players (up to five).

Global Retail Analytics Market is an upcoming report to be released soon. If you wish an early delivery of this report or want to confirm the date of release, please contact us at [email protected]

Table of content

1. Product Overview

1.1. Market Definition

1.2. Scope of the Market

1.2.1. Markets Covered

1.2.2. Years Considered for Study

1.2.3. Key Market Segmentations

2. Research Methodology

2.1. Objective of the Study

2.2. Baseline Methodology

2.3. Key Industry Partners

2.4. Major Association and Secondary Sources

2.5. Forecasting Methodology

2.6. Data Triangulation & Validation

2.7. Assumptions and Limitations

3. Executive Summary

3.1. Overview of the Market

3.2. Overview of Key Market Segmentations

3.3. Overview of Key Market Players

3.4. Overview of Key Regions/Countries

3.5. Overview of Market Drivers, Challenges, Trends

4. Voice of Customer

5. Global Retail Analytics Market Outlook

5.1. Market Size & Forecast

5.1.1. By Value

5.2. Market Share & Forecast

5.2.1. By Component (Software Vs. Service)

5.2.2. By Deployment Mode (Cloud Vs. On-Premises)

5.2.3. By Application (Merchandising Analytics & Others)

5.2.4. By Region

5.2.5. By Company (2025)

5.3. Market Map

6. North America Retail Analytics Market Outlook

6.1. Market Size & Forecast

6.1.1. By Value

6.2. Market Share & Forecast

6.2.1. By Component

6.2.2. By Deployment Mode

6.2.3. By Application

6.2.4. By Country

6.3. North America: Country Analysis

6.3.1. United States Retail Analytics Market Outlook

6.3.1.1. Market Size & Forecast

6.3.1.1.1. By Value

6.3.1.2. Market Share & Forecast

6.3.1.2.1. By Component

6.3.1.2.2. By Deployment Mode

6.3.1.2.3. By Application

6.3.2. Canada Retail Analytics Market Outlook

6.3.2.1. Market Size & Forecast

6.3.2.1.1. By Value

6.3.2.2. Market Share & Forecast

6.3.2.2.1. By Component

6.3.2.2.2. By Deployment Mode

6.3.2.2.3. By Application

6.3.3. Mexico Retail Analytics Market Outlook

6.3.3.1. Market Size & Forecast

6.3.3.1.1. By Value

6.3.3.2. Market Share & Forecast

6.3.3.2.1. By Component

6.3.3.2.2. By Deployment Mode

6.3.3.2.3. By Application

7. Europe Retail Analytics Market Outlook

7.1. Market Size & Forecast

7.1.1. By Value

7.2. Market Share & Forecast

7.2.1. By Component

7.2.2. By Deployment Mode

7.2.3. By Application

7.2.4. By Country

7.3. Europe: Country Analysis

7.3.1. Germany Retail Analytics Market Outlook

7.3.1.1. Market Size & Forecast

7.3.1.1.1. By Value

7.3.1.2. Market Share & Forecast

7.3.1.2.1. By Component

7.3.1.2.2. By Deployment Mode

7.3.1.2.3. By Application

7.3.2. France Retail Analytics Market Outlook

7.3.2.1. Market Size & Forecast

7.3.2.1.1. By Value

7.3.2.2. Market Share & Forecast

7.3.2.2.1. By Component

7.3.2.2.2. By Deployment Mode

7.3.2.2.3. By Application

7.3.3. United Kingdom Retail Analytics Market Outlook

7.3.3.1. Market Size & Forecast

7.3.3.1.1. By Value

7.3.3.2. Market Share & Forecast

7.3.3.2.1. By Component

7.3.3.2.2. By Deployment Mode

7.3.3.2.3. By Application

7.3.4. Italy Retail Analytics Market Outlook

7.3.4.1. Market Size & Forecast

7.3.4.1.1. By Value

7.3.4.2. Market Share & Forecast

7.3.4.2.1. By Component

7.3.4.2.2. By Deployment Mode

7.3.4.2.3. By Application

7.3.5. Spain Retail Analytics Market Outlook

7.3.5.1. Market Size & Forecast

7.3.5.1.1. By Value

7.3.5.2. Market Share & Forecast

7.3.5.2.1. By Component

7.3.5.2.2. By Deployment Mode

7.3.5.2.3. By Application

8. Asia Pacific Retail Analytics Market Outlook

8.1. Market Size & Forecast

8.1.1. By Value

8.2. Market Share & Forecast

8.2.1. By Component

8.2.2. By Deployment Mode

8.2.3. By Application

8.2.4. By Country

8.3. Asia Pacific: Country Analysis

8.3.1. China Retail Analytics Market Outlook

8.3.1.1. Market Size & Forecast

8.3.1.1.1. By Value

8.3.1.2. Market Share & Forecast

8.3.1.2.1. By Component

8.3.1.2.2. By Deployment Mode

8.3.1.2.3. By Application

8.3.2. India Retail Analytics Market Outlook

8.3.2.1. Market Size & Forecast

8.3.2.1.1. By Value

8.3.2.2. Market Share & Forecast

8.3.2.2.1. By Component

8.3.2.2.2. By Deployment Mode

8.3.2.2.3. By Application

8.3.3. Japan Retail Analytics Market Outlook

8.3.3.1. Market Size & Forecast

8.3.3.1.1. By Value

8.3.3.2. Market Share & Forecast

8.3.3.2.1. By Component

8.3.3.2.2. By Deployment Mode

8.3.3.2.3. By Application

8.3.4. South Korea Retail Analytics Market Outlook

8.3.4.1. Market Size & Forecast

8.3.4.1.1. By Value

8.3.4.2. Market Share & Forecast

8.3.4.2.1. By Component

8.3.4.2.2. By Deployment Mode

8.3.4.2.3. By Application

8.3.5. Australia Retail Analytics Market Outlook

8.3.5.1. Market Size & Forecast

8.3.5.1.1. By Value

8.3.5.2. Market Share & Forecast

8.3.5.2.1. By Component

8.3.5.2.2. By Deployment Mode

8.3.5.2.3. By Application

9. Middle East & Africa Retail Analytics Market Outlook

9.1. Market Size & Forecast

9.1.1. By Value

9.2. Market Share & Forecast

9.2.1. By Component

9.2.2. By Deployment Mode

9.2.3. By Application

9.2.4. By Country

9.3. Middle East & Africa: Country Analysis

9.3.1. Saudi Arabia Retail Analytics Market Outlook

9.3.1.1. Market Size & Forecast

9.3.1.1.1. By Value

9.3.1.2. Market Share & Forecast

9.3.1.2.1. By Component

9.3.1.2.2. By Deployment Mode

9.3.1.2.3. By Application

9.3.2. UAE Retail Analytics Market Outlook

9.3.2.1. Market Size & Forecast

9.3.2.1.1. By Value

9.3.2.2. Market Share & Forecast

9.3.2.2.1. By Component

9.3.2.2.2. By Deployment Mode

9.3.2.2.3. By Application

9.3.3. South Africa Retail Analytics Market Outlook

9.3.3.1. Market Size & Forecast

9.3.3.1.1. By Value

9.3.3.2. Market Share & Forecast

9.3.3.2.1. By Component

9.3.3.2.2. By Deployment Mode

9.3.3.2.3. By Application

10. South America Retail Analytics Market Outlook

10.1. Market Size & Forecast

10.1.1. By Value

10.2. Market Share & Forecast

10.2.1. By Component

10.2.2. By Deployment Mode

10.2.3. By Application

10.2.4. By Country

10.3. South America: Country Analysis

10.3.1. Brazil Retail Analytics Market Outlook

10.3.1.1. Market Size & Forecast

10.3.1.1.1. By Value

10.3.1.2. Market Share & Forecast

10.3.1.2.1. By Component

10.3.1.2.2. By Deployment Mode

10.3.1.2.3. By Application

10.3.2. Colombia Retail Analytics Market Outlook

10.3.2.1. Market Size & Forecast

10.3.2.1.1. By Value

10.3.2.2. Market Share & Forecast

10.3.2.2.1. By Component

10.3.2.2.2. By Deployment Mode

10.3.2.2.3. By Application

10.3.3. Argentina Retail Analytics Market Outlook

10.3.3.1. Market Size & Forecast

10.3.3.1.1. By Value

10.3.3.2. Market Share & Forecast

10.3.3.2.1. By Component

10.3.3.2.2. By Deployment Mode

10.3.3.2.3. By Application

11. Market Dynamics

11.1. Drivers

11.2. Challenges

12. Market Trends & Developments

12.1. Merger & Acquisition (If Any)

12.2. Product Launches (If Any)

12.3. Recent Developments

13. Global Retail Analytics Market: SWOT Analysis

14. Porter's Five Forces Analysis

14.1. Competition in the Industry

14.2. Potential of New Entrants

14.3. Power of Suppliers

14.4. Power of Customers

14.5. Threat of Substitute Products

15. Competitive Landscape

15.1. IBM Corporation

15.1.1. Business Overview

15.1.2. Products & Services

15.1.3. Recent Developments

15.1.4. Key Personnel

15.1.5. SWOT Analysis

15.2. SAP SE

15.3. Microsoft Corporation

15.4. Adobe Inc.

15.5. Oracle Corporation

15.6. SAS Institute Inc.

15.7. Qlik Technologies Inc.

15.8. Salesforce Company

15.9. Teradata Corporation

15.10. MicroStrategy Incorporated

15.11. HCL Technologies Limited

15.12. Domo Inc.

15.13. Information Builders Inc.

16. Strategic Recommendations

17. About Us & Disclaimer

Report Description

Table of content

Figures and Tables

Frequently asked questions

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