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The market is segmented by Product (Software, Service), Deployment (Cloud, On-Premise), Application (Supply Chain and Logistics, Product Optimization, In-Store Navigation, Payment and Pricing Analytics, Inventory Management, Customer Relationship Management), and Geography.
2018 - 2026
Fastest Growing Market:
The Artificial Intelligence in Retail Market was valued at USD 1.80 billion in 2020 and is expected to reach USD 10.90 billion by 2026, at a CAGR of 35% over the forecast period 2021 - 2026. AI will drive faster business decisions in marketing, e-commerce, product management, and other areas of the business by decreasing the gap from insights to action.
The application of artificial intelligence (AI), Big Data, and analytics will push the business access toward a data-driven model by expanding the types of data that can be analyzed and raise the level of sophistication of the resulting insight. Artificial intelligence in the retail market is being divided as software, services with different applications like supply chain and logistics, product optimization, in-store navigation, payment and pricing analytics, inventory management, customer relationship management. All these applications are being deployed either in the cloud or on-premise.
|Supply Chain and Logistics|
|Payment and Pricing Analytics|
|Customer Relationship Management (CRM)|
|Middle East & Africa|
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Artificial intelligence in the retail market is fragmented. The growing adoption of IoT, Big Data analytics, and e-commerce marketing provide lucrative opportunities for artificial intelligence in the retail market. Overall, the competitive rivalry among existing competitors is high. Moving forward, acquisitions and collaborations of large companies with startups are expected, which are focused toward innovation. Some of the key developments in the area are:
1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study
2. RESEARCH METHODOLOGY
3. EXECUTIVE SUMMARY
4. MARKET INSIGHT
4.1 Market Overview
4.2 Industry Attractiveness - Porter's Five Forces Analysis
4.2.1 Threat of New Entrants
4.2.2 Bargaining Power of Buyers/Consumers
4.2.3 Bargaining Power of Suppliers
4.2.4 Threat of Substitute Products
4.2.5 Intensity of Competitive Rivalry
4.3 Value Chain / Supply Chain Analysis
4.4 Industry Policies
4.5 Technology Snapshot
4.5.1 Machine Learning
4.5.2 Deep Learning
4.5.3 Neuro-Linguistic Programming
5. MARKET DYNAMICS
5.1 Introduction to Market Drivers and Restraints
5.2 Market Drivers
5.2.1 Rapid Adoption of Advances in Technology Across Retail Chain
5.2.2 Emerging Trend of Startups in the Retail Space
5.3 Market Restraints
5.3.1 Lack of Professionals as well as In-House Knowledge for Cultural Readiness
6. MARKET SEGMENTATION
6.1 By Product
6.2 By Deployment
6.3 By Application
6.3.1 Supply Chain and Logistics
6.3.2 Product Optimization
6.3.3 In-Store Navigation
6.3.4 Payment and Pricing Analytics
6.3.5 Inventory Management
6.3.6 Customer Relationship Management (CRM)
6.4.1 North America
6.4.4 Latin America
6.4.5 Middle East & Africa
7. COMPETITIVE LANDSCAPE
7.1 Company Profiles
7.1.1 Amazon Web Services Inc.
7.1.3 Google LLC
7.1.4 Daisy Intelligence
7.1.5 IBM Corporation
7.1.6 Microsoft Corporation
7.1.7 Plexure Ltd
7.1.8 Versium Analytics Inc.
7.1.9 Findmine Inc.
7.1.10 SAP SE
7.1.11 Salesforce.com Inc.
7.1.12 Conversica Inc.
7.1.13 BloomReach Inc.
7.1.14 Sentient Technologies Holdings Limited
7.1.15 Focal Systems Inc.
7.1.16 ViSenze Pte Ltd
8. INVESTMENT ANALYSIS
9. MARKET OPPORTUNITIES AND FUTURE TRENDS
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