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Retail Analytics Market Report by Function, Component, Deployment Mode, End User, and Region 2024-2032

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BJH 24.09.12

The global retail analytics market size reached US$ 8.8 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 40.0 Billion by 2032, exhibiting a growth rate (CAGR) of 17.8% during 2024-2032. The retail analytics market is experiencing significant growth driven by the expanding digitization in organizations, rising use of cloud-based retail analytics solutions, and growing online shopping habits of consumers looking to save time and money.

Retail Analytics Market Analysis:

Major Market Drivers: The retail analytics market outlook is primarily driven by the enhanced utilization of data analytics and machine learning in stock inventory control, supply chain optimization, and customer behavior analysis. Merchandises (retailers), with the aid of these technologies, come to know the tastes of consumers, organize collections appropriately, improve their operational processes, and eventually increase their sales and profits.

Key Market Trends: The major trend in the retail analytics industry is the emergence of a cloud-based analytics solution as a mainstream offering. These solutions give retailers scalability, flexibility, and real-time data access, which are the necessary tools to have a better generation and processing of large data volumes. With the help of cloud-based analytics, retailers collaborate and integrate available information over several channels and positions and act in one direction to give customers the choice of omnichannel shopping.

Geographical Trends: North America leads in market adoption, driven by advanced technology infrastructure and the strong presence of major retail players. In North America, a mature retail market with a high level of technology innovation, there is an environment fit for retailers to implement advanced analytics solutions to support their operations.

Competitive Landscape: Some of the major market players in the retail analytics industry include 1010data Inc. (Advance Publications Inc.), Adobe Inc., Altair Engineering Inc., Flir Systems Inc., Fujitsu Limited, International Business Machines Corporation, Information Builders Inc., Microsoft Corporation, Microstrategy Incorporated, Oracle Corporation, Qlik Technologies Inc. (Thoma Bravo LLC), SAP SE, SAS Institute Inc., Tableau Software LLC (Salesforce.com Inc.), Tibco Software Inc., among many others.

Challenges and Opportunities: The retail analytics market faces data privacy issues that concern the regulatory environment and the consumers' cautions related to data security and privacy. Nonetheless, the introduction of AI opens a lot of possibilities for personalized customer experiences, targeted marketing initiatives, and increased efficiency in operations. The retailers will be able to control the practical power of AI-driven analytics for predicting customer preferences, creating efficient price strategies as well as the overall competitiveness in the market.

Retail Analytics Market Trends:

Integration of Machine Learning and Artificial Intelligence

As per the retail analytics market statistics, artificial intelligence (AI) and machine learning (ML) are becoming essential as they offer profound enhancements in the operations efficiencies and capability of prediction. AI is being used from professional to personal level these days. According to Forbes Advisor, a staggering 97% of business owners believe that ChatGPT will benefit their businesses. With the help of this technology, merchants can now more precisely than ever predict customer behavior, manage inventory levels, and target marketing campaigns. Large datasets can be analyzed by AI-driven analytics systems to find patterns and trends, enabling real-time decision-making that may boost revenue and satisfy customers. With time, machine learning algorithms get better, continuously enhancing their projections and suggestions based on fresh data. Retailers are adopting a more consumer-centric and responsive approach to operations due to this trend, which is changing everything from supply chain management to customer engagement tactics.

Enhanced Customer Experience through Personalization

Due to the availability of big data and sophisticated analytical tools, personalization is a dominant trend in the retail analytics sector. Retailers may now provide clients with extremely customized shopping experiences by examining their preferences, purchasing patterns, and even social media activity. By customizing products and promotions to everyone's tastes, personalized marketing is made possible by this data-driven strategy, which dramatically raises conversion rates and fosters client loyalty, people want more of inclusivity and human treatment from the companies they buy from. For instance, as per the report published by Forbes Magazine, 84% of consumers say being treated like a person, not a number is very important to winning their business. Furthermore, personalization goes beyond marketing to include adjusting the actual purchasing experience, such as offering customized in-store services, dynamic pricing, and personalized recommendations. By matching supply with demand, this degree of customisation not only raises customer pleasure but also boosts retail operations efficiency.

Adoption of Omnichannel Strategies

Retail analytics developments have made omnichannel commerce a crucial strategy for success in the digital age. This strategy creates a seamless consumer experience by integrating many shopping channels (online, mobile, and in-store). In order to create a cohesive picture of customer behaviour, retail analytics track and analyze consumer interactions across all platforms, which is a critical component to create business opportunities in the retail analytics market. According to Forbes, 70% of consumers say that a company understanding how they use products and services is very important to winning their business. This data is essential for improving customer service, streamlining the inventory process, and building a consistent brand experience. Using analytics to manage and improve these interactions is becoming an essential part of retail strategy as customers demand a smooth transition between online and in-store buying experience

Retail Analytics Market Segmentation:

IMARC Group provides an analysis of the key trends in each segment of the market, along with forecasts at the global, regional, and country levels for 2024-2032. Our report has categorized the market based on function, component, deployment mode, end user.

Breakup by Function:

Customer Management

In-store Operation

Strategy and Planning

Supply Chain Management

Marketing and Merchandizing

Others

Customer management accounts for the majority of the market share

The report has provided a detailed breakup and analysis of the market based on the function. This includes customer management, in-store operation, strategy and planning, supply chain management, marketing and merchandizing, and others. According to the report, customer management represented the largest segment.

Due to the growing demand for individualized customer experiences and the strategic significance of customer loyalty and retention in a cutthroat retail environment, customer management leads the retail analytics market by function. Retailers may deliver customized marketing, improve customer interactions, and expand their service offerings by using analytics to obtain deep insights into customer behaviors, preferences, and purchasing habits. For instance, the Census Bureau data shows significant insights into retail sales and e-commerce trends which are crucial for customer management in retail analytics. In addition, the Annual Retail Trade Survey provides detailed annual sales, e-commerce sales, and inventories across various retail sectors. This can help businesses understand consumer buying patterns and adapt their customer management strategies accordingly. This data-driven strategy aids in the identification of valuable clients, forecasting their future purchasing patterns and putting in place efficient loyalty schemes. Furthermore, by facilitating real-time decision-making and predictive analytics, the incorporation of technologies like artificial intelligence (AI) and machine learning further augments the efficacy of these techniques.

Breakup by Component:

Software

Services

Software holds the largest share of the industry

A detailed breakup and analysis of the market based on the component have also been provided in the report. This includes software and services. According to the report, software accounted for the largest market share.

Software dominates the retail analytics industry as it is crucial to turning massive volumes of data into insights that can be put into practice, which helps retailers make better decisions. The U.S. Census Bureau reports that in Q12021, e-commerce sales made up almost 13% of overall sales, highlighting the significance of analytics in maximizing online sales tactics. In today's data-driven market climate, retail analytics software offers extensive solutions for customer behavior monitoring, inventory management, and sales forecasting. The growing use of digital operations in retail, as noted by the Bureau of Labor Statistics, calls for advanced analytics solutions to manage the scope and intricacy of contemporary retail operations.

Breakup by Deployment Mode:

On-premises

Cloud-based

Cloud-based represents the leading market segment

The report has provided a detailed breakup and analysis of the market based on the deployment mode. This includes on-premises and cloud-based. According to the report, cloud-based represented the largest segment.

Due to their scalability, flexibility, and affordability-all of which are critical for managing the enormous volumes of data created by contemporary retail operations-cloud-based solutions provide a positive impact on the retail analytics industry outlook. Retailers are able to efficiently handle peak shopping periods because they have the flexibility to scale resources up or down as needed. A U.S. Small Business Administration survey states that as cloud computing can lower IT overhead expenses and increase operational efficiency, small and medium-sized firms are adopting it at an increasing rate. This change is particularly important for the retail industry, where real-time data processing and analytics are required due to changing market conditions. Cloud systems make this possible by offering data storage and sophisticated analysis capabilities without requiring a substantial initial outlay of funds.

Breakup by End User:

Small and Medium Enterprises

Large Enterprises

Large enterprises exhibit a clear dominance in the market

A detailed breakup and analysis of the market based on the end user have also been provided in the report. This includes small and medium enterprises and large enterprises. According to the report, large enterprises accounted for the largest market share.

Due to their vast operational scope and the intricate data environments, they oversee, large organizations hold a dominant position in the end-user retail analytics market. These companies possess the infrastructure and financial means to invest in cutting-edge retail analytics solutions, which are essential for managing the enormous volumes of data produced across numerous channels and regions. Large businesses may learn a great deal about market trends, supply chain efficiency, and consumer behavior by integrating and analyzing this data. Strategic planning, competitiveness in international markets, and operational optimization all depend on this degree of analytics. Large businesses can also frequently use more advanced analytics, such as AI-driven tools and predictive modeling, to spur innovation and enhance consumer experiences.

Breakup By Region:

North America

United States

Canada

Asia Pacific

China

Japan

India

South Korea

Australia

Indonesia

Others

Europe

Germany

France

United Kingdom

Italy

Spain

Russia

Others

Latin America

Brazil

Mexico

Others

Middle East and Africa

North America leads the market, accounting for the largest retail analytics market share

The report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America represented the largest market for retail analytics.

North America dominates the retail analytics market due to its sophisticated technological infrastructure, there has been a widespread use of big data solutions, and large investments in artificial intelligence (AI) and machine learning. The U.S. Department of Commerce reports that North American retail e-commerce sales increased 32.4% in 2019 compared to 2020, indicating the sector's rapid expansion and the growing demand for advanced analytics. Large digital organizations and startups that specialize in retail analytics solutions to improve customer experiences and operational efficiency call this region home. According to the U.S. Bureau of Economic Analysis, the demand for analytics to comprehend consumer behavior, manage inventory, and improve supply chains is driven by the digital transformation in retail. This is further catalyzing the retail analytics market growth.

Competitive Landscape:

The retail analytics market research report has also provided a comprehensive analysis of the competitive landscape in the market. Detailed profiles of all major companies have also been provided. Some of the major market players in the retail analytics industry include 1010data Inc. (Advance Publications Inc.), Adobe Inc., Altair Engineering Inc., Flir Systems Inc., Fujitsu Limited, International Business Machines Corporation, Information Builders Inc., Microsoft Corporation, Microstrategy Incorporated, Oracle Corporation, Qlik Technologies Inc. (Thoma Bravo LLC), SAP SE, SAS Institute Inc., Tableau Software LLC (Salesforce.com Inc.), Tibco Software Inc, etc.

(Please note that this is only a partial list of the key players, and the complete list is provided in the report.)

Some of the leading companies in the retail analytics space, such as Microsoft Corporation, Fujitsu Limited, Flir Systems Inc., Altair Engineering Inc., Adobe Inc., and 1010data Inc., are constantly improving their products to increase the retail analytics market value. 1010data Inc. is a cloud-based analytics provider with a strong emphasis on retail operations optimization. Adobe Inc. provides customized digital marketing solutions through its advanced Adobe Analytics platform. Retailers can enhance supply chain and inventory management with the assistance of Altair Engineering Inc., which incorporates analytics into product design. Flir Systems Inc. uses cutting-edge thermal imaging technology to gain insights into customer behavior and security. Complete retail solutions, such as data-driven point-of-sale systems, are provided by Fujitsu Limited. Microsoft Corporation, is advancing the personalization of shopping experiences by leveraging cutting-edge AI and cloud-based technologies to improve customer engagement. Collectively, these businesses are paving the way for sophisticated, data-driven retail strategy. For instance, Adobe Experience Platform delivered new tools such as customer journey analytics with which retailers can now leverage AI to detect broken experiences (or to uncover new opportunities). This update takes anomaly detection beyond the website - where it has been predominantly used - and allows brands to see where issues arise as shoppers move between channels.

Retail Analytics Market News:

Feb 2024: Kroger partnered with Intelligence Node to enhance marketplace listings and provide clearer product guides for third-party vendors.

Jan 2024: Microsoft announced the launch of new GenAI tools specifically designed for the retail industry, aiming to personalize shopping experiences and assist frontline workers in real time.

Key Questions Answered in This Report

  • 1. What was the size of the global retail analytics market in 2023?
  • 2. What is the expected growth rate of the global retail analytics market during 2024-2032?
  • 3. What are the key factors driving the global retail analytics market?
  • 4. What has been the impact of COVID-19 on the global retail analytics market?
  • 5. What is the breakup of the global retail analytics market based on the function?
  • 6. What is the breakup of the global retail analytics market based on the component?
  • 7. What is the breakup of the global retail analytics market based on the deployment mode?
  • 8. What is the breakup of the global retail analytics market based on the end user?
  • 9. What are the key regions in the global retail analytics market?
  • 10. Who are the key players/companies in the global retail analytics market?

Table of Contents

1 Preface

2 Scope and Methodology

  • 2.1 Objectives of the Study
  • 2.2 Stakeholders
  • 2.3 Data Sources
    • 2.3.1 Primary Sources
    • 2.3.2 Secondary Sources
  • 2.4 Market Estimation
    • 2.4.1 Bottom-Up Approach
    • 2.4.2 Top-Down Approach
  • 2.5 Forecasting Methodology

3 Executive Summary

4 Introduction

  • 4.1 Overview
  • 4.2 Key Industry Trends

5 Global Retail Analytics Market

  • 5.1 Market Overview
  • 5.2 Market Performance
  • 5.3 Impact of COVID-19
  • 5.4 Market Forecast

6 Market Breakup by Function

  • 6.1 Customer Management
    • 6.1.1 Market Trends
    • 6.1.2 Market Forecast
  • 6.2 In-store Operation
    • 6.2.1 Market Trends
    • 6.2.2 Market Forecast
  • 6.3 Strategy and Planning
    • 6.3.1 Market Trends
    • 6.3.2 Market Forecast
  • 6.4 Supply Chain Management
    • 6.4.1 Market Trends
    • 6.4.2 Market Forecast
  • 6.5 Marketing and Merchandizing
    • 6.5.1 Market Trends
    • 6.5.2 Market Forecast
  • 6.6 Others
    • 6.6.1 Market Trends
    • 6.6.2 Market Forecast

7 Market Breakup by Component

  • 7.1 Software
    • 7.1.1 Market Trends
    • 7.1.2 Market Forecast
  • 7.2 Services
    • 7.2.1 Market Trends
    • 7.2.2 Market Forecast

8 Market Breakup by Deployment Mode

  • 8.1 On-premises
    • 8.1.1 Market Trends
    • 8.1.2 Market Forecast
  • 8.2 Cloud-based
    • 8.2.1 Market Trends
    • 8.2.2 Market Forecast

9 Market Breakup by End User

  • 9.1 Small and Medium Enterprises
    • 9.1.1 Market Trends
    • 9.1.2 Market Forecast
  • 9.2 Large Enterprises
    • 9.2.1 Market Trends
    • 9.2.2 Market Forecast

10 Market Breakup by Region

  • 10.1 North America
    • 10.1.1 United States
      • 10.1.1.1 Market Trends
      • 10.1.1.2 Market Forecast
    • 10.1.2 Canada
      • 10.1.2.1 Market Trends
      • 10.1.2.2 Market Forecast
  • 10.2 Asia Pacific
    • 10.2.1 China
      • 10.2.1.1 Market Trends
      • 10.2.1.2 Market Forecast
    • 10.2.2 Japan
      • 10.2.2.1 Market Trends
      • 10.2.2.2 Market Forecast
    • 10.2.3 India
      • 10.2.3.1 Market Trends
      • 10.2.3.2 Market Forecast
    • 10.2.4 South Korea
      • 10.2.4.1 Market Trends
      • 10.2.4.2 Market Forecast
    • 10.2.5 Australia
      • 10.2.5.1 Market Trends
      • 10.2.5.2 Market Forecast
    • 10.2.6 Indonesia
      • 10.2.6.1 Market Trends
      • 10.2.6.2 Market Forecast
    • 10.2.7 Others
      • 10.2.7.1 Market Trends
      • 10.2.7.2 Market Forecast
  • 10.3 Europe
    • 10.3.1 Germany
      • 10.3.1.1 Market Trends
      • 10.3.1.2 Market Forecast
    • 10.3.2 France
      • 10.3.2.1 Market Trends
      • 10.3.2.2 Market Forecast
    • 10.3.3 United Kingdom
      • 10.3.3.1 Market Trends
      • 10.3.3.2 Market Forecast
    • 10.3.4 Italy
      • 10.3.4.1 Market Trends
      • 10.3.4.2 Market Forecast
    • 10.3.5 Spain
      • 10.3.5.1 Market Trends
      • 10.3.5.2 Market Forecast
    • 10.3.6 Russia
      • 10.3.6.1 Market Trends
      • 10.3.6.2 Market Forecast
    • 10.3.7 Others
      • 10.3.7.1 Market Trends
      • 10.3.7.2 Market Forecast
  • 10.4 Latin America
    • 10.4.1 Brazil
      • 10.4.1.1 Market Trends
      • 10.4.1.2 Market Forecast
    • 10.4.2 Mexico
      • 10.4.2.1 Market Trends
      • 10.4.2.2 Market Forecast
    • 10.4.3 Others
      • 10.4.3.1 Market Trends
      • 10.4.3.2 Market Forecast
  • 10.5 Middle East and Africa
    • 10.5.1 Market Trends
    • 10.5.2 Market Breakup by Country
    • 10.5.3 Market Forecast

11 SWOT Analysis

  • 11.1 Overview
  • 11.2 Strengths
  • 11.3 Weaknesses
  • 11.4 Opportunities
  • 11.5 Threats

12 Value Chain Analysis

13 Porters Five Forces Analysis

  • 13.1 Overview
  • 13.2 Bargaining Power of Buyers
  • 13.3 Bargaining Power of Suppliers
  • 13.4 Degree of Competition
  • 13.5 Threat of New Entrants
  • 13.6 Threat of Substitutes

14 Price Analysis

15 Competitive Landscape

  • 15.1 Market Structure
  • 15.2 Key Players
  • 15.3 Profiles of Key Players
    • 15.3.1 1010data Inc. (Advance Publications Inc.)
      • 15.3.1.1 Company Overview
      • 15.3.1.2 Product Portfolio
    • 15.3.2 Adobe Inc.
      • 15.3.2.1 Company Overview
      • 15.3.2.2 Product Portfolio
      • 15.3.2.3 Financials
      • 15.3.2.4 SWOT Analysis
    • 15.3.3 Altair Engineering Inc.
      • 15.3.3.1 Company Overview
      • 15.3.3.2 Product Portfolio
      • 15.3.3.3 Financials
    • 15.3.4 Flir Systems Inc.
      • 15.3.4.1 Company Overview
      • 15.3.4.2 Product Portfolio
      • 15.3.4.3 Financials
      • 15.3.4.4 SWOT Analysis
    • 15.3.5 Fujitsu Limited
      • 15.3.5.1 Company Overview
      • 15.3.5.2 Product Portfolio
      • 15.3.5.3 Financials
      • 15.3.5.4 SWOT Analysis
    • 15.3.6 International Business Machines Corporation
      • 15.3.6.1 Company Overview
      • 15.3.6.2 Product Portfolio
      • 15.3.6.3 Financials
      • 15.3.6.4 SWOT Analysis
    • 15.3.7 Information Builders Inc.
      • 15.3.7.1 Company Overview
      • 15.3.7.2 Product Portfolio
    • 15.3.8 Microsoft Corporation
      • 15.3.8.1 Company Overview
      • 15.3.8.2 Product Portfolio
      • 15.3.8.3 Financials
      • 15.3.8.4 SWOT Analysis
    • 15.3.9 Microstrategy Incorporated
      • 15.3.9.1 Company Overview
      • 15.3.9.2 Product Portfolio
      • 15.3.9.3 Financials
      • 15.3.9.4 SWOT Analysis
    • 15.3.10 Oracle Corporation
      • 15.3.10.1 Company Overview
      • 15.3.10.2 Product Portfolio
      • 15.3.10.3 Financials
      • 15.3.10.4 SWOT Analysis
    • 15.3.11 Qlik Technologies Inc. (Thoma Bravo LLC)
      • 15.3.11.1 Company Overview
      • 15.3.11.2 Product Portfolio
    • 15.3.12 SAP SE
      • 15.3.12.1 Company Overview
      • 15.3.12.2 Product Portfolio
      • 15.3.12.3 Financials
      • 15.3.12.4 SWOT Analysis
    • 15.3.13 SAS Institute Inc.
      • 15.3.13.1 Company Overview
      • 15.3.13.2 Product Portfolio
      • 15.3.13.3 SWOT Analysis
    • 15.3.14 Tableau Software LLC (Salesforce.com Inc.)
      • 15.3.14.1 Company Overview
      • 15.3.14.2 Product Portfolio
    • 15.3.15 Tibco Software Inc.
      • 15.3.15.1 Company Overview
      • 15.3.15.2 Product Portfolio
      • 15.3.15.3 SWOT Analysis
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