Worldwide Retail Analytics Industry to 2025 - Players include Microsoft, IBM and Oracle among others
DUBLIN, Dec. 11, 2020 /PRNewswire/ -- The "Retail Analytics Market by Application (Merchandising Analysis, Customer Analytics, and Promotional Analysis and Planning), Business Function (Finance and Operations), Component, Organization Size, End User, and Region - Global Forecast to 2025" report has been added to ResearchAndMarkets.com's offering.
The global retail analytics market size to grow from USD 4.3 billion in 2020 to USD 11.1 billion by 2025, at a CAGR of 21.2% during the forecast period.
Major factors contributing to the growth of the retail analytics market are the rising demand for dashboards for data visualization, growing adoption of cloud, and continuous increase in data generation. The objective of the report is to define, describe, and forecast the retail analytics market size based on component, business function, application, organization size, end-user, and region.
The COVID-19 has impacted all elements of the technology sector. It has slowed down the growth of IT infrastructure owing to disruptions in the hardware supply chain and reduced manufacturing activities. This health crisis has had an unprecedented impact on businesses across industries; while some are struggling, others are thriving. Rising support from governments and several data analytics companies can help in the fight against this highly contagious disease. Businesses providing retail analytics solutions and services are also expected to witness a decline in their growth for a short span of time. However, the adoption of collaborative applications, IoT, analytics, security solutions, and AI is set to increase in the remaining part of 2020.
The service segment to grow at a higher CAGR during the forecast period
The services segment is expected to grow at the highest CAGR during the forecast period. The growing concern of organizations to gain visibility for diagnosing and troubleshooting problems before they impact operations or end-user experiences will drive the adoption of retail analytics solutions and services.
The operation business function segment to grow at the highest CAGR during the forecast period
The operations segment is projected to grow at the highest CAGR during the forecast period. The growth can be attributed to the rising need of retailers to generate deeper insights across the entire value chain of retail operations, including procurement, supply chain, sales and marketing, store operations, and customer management.
The inventory analysis segment to grow at the highest CAGR during the forecast period
The retail analytics market is segmented into various applications, such as merchandising analysis, pricing analysis, customer analytics, promotional analysis and planning, yield analysis, inventory analysis, and others (order management, transportation management, assortment and cluster planning, and real-estate planning). The inventory analysis segment is projected to register a higher CAGR during the forecast period due to the growing need to enhance business processes by keeping track of stocked goods and ensure surplus inventory.
Among regions, Asia Pacific (APAC) to grow at the highest CAGR during the forecast period
APAC is expected to record the highest CAGR during the forecast period, as it is home to many developed and emerging economies, which offer major opportunities for the growth of retail stores and technology development. China, India, and Japan in particular are focusing on the management of data to enable data-based business decisions and enhance business processes in the retail market.
Key Topics Covered: 1 Introduction 2 Research Methodology 3 Executive Summary 4 Premium Insights 4.1 Attractive Opportunities in Retail Analytics Market 4.2 Market: Top Three Applications 4.3 Market, by Region 4.4 Market, by Business Function and Application 5 Market Overview and Industry Trends 5.1 Introduction 5.2 Retail Analytics: Evolution 5.3 Retail Analytics: Ecosystem 5.4 Market Dynamics 5.4.1 Drivers 220.127.116.11 Digitalizing to Enhance Customer Experience and Retail Operations 18.104.22.168 Rising Adoption of Disruptive Technologies to Forecast Future Market Trends 22.214.171.124 Growing Number of Smartphones, and Increasing Use of M-Commerce 5.4.2 Restraints 126.96.36.199 Lack of Technology Adoption by Unorganized Retail Sector 188.8.131.52 Legal Concerns and Data Privacy Issues 5.4.3 Opportunities 184.108.40.206 Growing Adoption of Cloud Services in Retail 220.127.116.11 Proliferation of Data Analytics to Understand Customer Data During COVID-19 5.4.4 Challenges 18.104.22.168 Retailers Face a Data Deficit in the Wake of the COVID-19 Pandemic 5.4.5 Cumulative Growth Analysis 5.5 Retail Analytics Market: COVID-19 Impact 5.6 Case Study Analysis 5.6.1 a Global Retail Chain Used Advanced Analytics & Machine Learning to Forecast New Store Locations and Revenues 5.6.2 a Fortune 500 Retailer Used Customer Genome to Deliver Personalized Interaction to Customers and Drive More Revenue 5.6.3 a Global Retailer Leveraged Manthan's Smart Analytics Solution to Take Data-Driven Business Decisions 5.6.4 The Retailer Used Bridgei2I to Deliver an Enhanced Customer Experience 5.6.5 The Client Adopted Sas Analytics to Understand Customer Needs 5.6.6 Groupo Merza Leveraged Sap Solutions for Market Basket Analysis 5.6.7 Peter England Adopted Capillary's Customer Acquisition Platform to Analyze Customer Footfall 5.6.8 a Global It Company Increased Customer Base and Improved Loyalty 5.6.9 a Home Improvement Retailer Enhanced Sales and Workforce Optimization 5.7 Patent Analysis 5.7.1 Patents Filed: Retail Analytics, by Application, 2019-2020 5.8 Value Chain Analysis 5.9 Technology Analysis 5.9.1 Voice Search 5.9.2 In-Store Digital Display 5.9.3 Social Shopping 5.9.4 Geo-Location Services 5.9.5 Visual Search 5.9.6 Smart Fitting Room 5.9.7 Ai and Ml in Retail 5.9.8 IoT in Retail 5.9.9 Big Data in Retail 5.1 Pricing Analysis 5.11 Retail Analytics, Key Performance Indicators (KPIs) 6 Retail Analytics Market, by Component 6.1 Introduction 6.1.1 Components: COVID-19 Impact 6.2 Solutions 6.2.1 Solutions: Market Drivers 6.3 Services 6.3.1 Services: Retail Analytics Market Drivers 6.3.2 Professional Services 22.214.171.124 Training and Support 126.96.36.199 Implementation and Consulting 6.3.3 Managed Services 7 Retail Analytics Market, by Business Function 7.1 Introduction 7.1.1 Business Functions: COVID-19 Impact 7.1.2 Business Functions: Market Drivers 7.2 Finance 7.3 Marketing and Sales 7.4 Human Resources 7.5 Operations 8 Retail Analytics Market, by Application 8.1 Introduction 8.1.1 Applications: COVID-19 Impact 8.1.2 Applications: Market Drivers 8.2 Merchandising Analysis 8.3 Pricing Analysis 8.4 Customer Analytics 8.5 Promotional Analysis and Planning 8.6 Yeild Analysis 8.7 Inventory Analysis 8.8 Others 9 Retail Analytics Market, by Organization Size 9.1 Introduction 9.1.1 Organization Size: COVID-19 Impact 9.1.2 Organization Size: Market Drivers 9.2 Large Enterprises 9.3 Small and Medium-Sized Enterprises 10 Retail Analytics Market, by End-user 10.1 Introduction 10.1.1 End-user: COVID-19 Impact 10.1.2 End-user: Market Drivers 10.2 Offline 10.3 Online 11 Retail Analytics Market, by Region 11.1 Introduction 11.2 North America 11.3 Europe 11.4 Asia-Pacific 11.5 Middle East & Africa 11.6 Latin America 12 Competitive Landscape 12.1 Overview 12.2 Market Evaluation Framework 12.3 Market Share, 2019 12.4 Historic Revenue Analysis of Key Market Players 12.5 Key Market Developments 12.5.1 New Product Launches and Product Enhancements 12.5.2 Business Expansions 12.5.3 Mergers and Acquisitions 12.5.4 Partnerships, Agreements, Contracts, and Collaborations 12.6 Company Evaluation Matrix, 2020 12.6.1 Star 12.6.2 Emerging Leader 12.6.3 Pervasive 12.6.4 Participant 12.7 Startup/SME Evaluation Matrix, 2020 12.7.1 Progressive Companies 12.7.2 Responsive Companies 12.7.3 Dynamic Companies 12.7.4 Starting Blocks 12.8 Market Ranking Analysis, by Company 13 Company Profiles 13.1 Introduction 13.2 Microsoft 13.3 IBM 13.4 Oracle 13.5 Salesforce 13.6 SAP 13.7 AWS 13.8 SAS Institute 13.9 Qlik 13.10 Manthan 13.11 Bridgei2I 13.12 Microstrategy 13.13 Teradata 13.14 HCL 13.15 Fujitsu 13.16 Domo 13.17 Google 13.18 Flir Systems 13.19 Information Builders 13.20 1010Data 13.21 Capillary 13.22 Retailnext 13.23 WNS 13.24 True Fit 13.25 Vend 13.26 Fit Analytics 13.27 Edited 13.28 Decision6 13.29 Cubelizer 13.30 Thinkinside 13.31 DOR Technologies 13.32 Glimpse Analytics 13.33 Pygmalios 13.34 Orenda Software Solutions 14 Appendix
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