AI in Retail and e-Commerce - Global Market Forecast to 2025
- May, 2019
- Domain: ICT - Verticals - Retail
Pages:
114
Tables:
29
Charts:
55
Regions/Countries:
4 / 0
Companies:
10
Enquiry Hours:
10
- Get Free 10% Customization in this Report
[114 Report Pages] Globally, the retail industry has become more competitive than ever as customers have plenty of choices while buying any product. The retail sector has become much more diverse because every customer has different and customized needs, which makes it tough for retailers to target a group. AI is now being used by retailers to get real-time and in-depth insights to attract diverse shoppers.
The revolution of AI is changing the customer shopping experience. AI in retail offers several opportunities in the retail space, as retailers have massive customer data available with them. Retailers can now understand their customers better and provide personalized recommendations, which help in retaining the customers and open new revenue streams for retailers. Brick and mortar retailers are spending in AI-based solutions to understand their customers better and enhance their shopping experience. The e-commerce industry is using AI to focus on applications such as product recommendations, search analysis, analyzing consumer sentiments, and promotions.
Market Analysis
According to Infoholic Research, the global AI in retail and e-commerce market is expected to grow at a CAGR of 42.8% during the forecast period 2019–2025 to reach revenue of $19.37 billion by 2025. Various retail and e-commerce companies are investing in digital technologies such as IoT, AI, and big data to stay ahead of the competition. AI-based solutions are being adopted by retail and e-commerce companies to enhance the performance and to achieve higher profits & business growth. These solutions are also used for critical decision making around sales and merchandising planning, pricing strategies, and product promotions.
Market Segmentation Analysis
The report provides in-depth qualitative insights and validated market forecast or projections based on certain assumptions and historical data. The projections and trends featured in the report have been derived using proven research methodologies and assumptions based on the vendors’ portfolio, blogs, whitepapers, and vendor presentations. Thus, the research report represents every side of the market and is segmented based on regional markets, providers, applications, and organization size.
Competitive Analysis
The report covers and analyzes the AI in retail and e-commerce market. Major vendors across different verticals are planning for high investments in this market, and as a result, the market is expected to grow at an impressive rate in the coming years. The key players are adopting various organic as well as inorganic growth strategies such as mergers & acquisitions, collaborations & partnerships, joint ventures, and few other strategies to be in the strong position in the market.
The report contains an in-depth analysis of the vendors, which includes financial health, business units, key business priorities, SWOT, strategies, and views. The prominent vendors covered in the report include IBM, SAP, Microsoft, AWS, SAS, JDA Software, Salesforce, Symphony RetailAI, Visenze, and Infinite Analytics among many others. The vendors have been identified based on the portfolio, geographical presence, marketing & distribution channels, revenue generation, and significant investments in R&D.
IBM, SAP, AWS, and Microsoft are the key players in the AI in retail and e-commerce market. In 2017, Godrej Interio, a leading furniture brand in India, collaborated with IBM and selected Watson Commerce for increasing customer engagement and experience. Kroger, one of the America’s largest grocery store chain, and Microsoft partnered in January 2019 for creating high-tech grocery stores. In February 2019, Sansibar Stores partnered with SAP and is using SAP Customer Checkout application for monitoring sales in real time, offering customized discounts, time-related prices, and many more.
The report also includes the complete insights of the industry and aims to provide an opportunity for the emerging and established players to understand the market trends, current scenario, initiatives taken by the government, and the latest technologies related to the market. In addition, it helps the venture capitalists in understanding the companies better and to take informed decisions.
Regional Analysis
Europe held the largest market share in 2018 and is projected to dominate the AI in retail and e-commerce market during the forecast period. Retailers in this region are focusing on loyalty programs to make emotional connections with their customers, by leveraging the power of AI. The growing number of retailers’ partnerships in this region for expanding their services is driving the growth of the market. For example, IKEA, a home goods giant, acquired TaskRabbit, an online platform that connects skilled taskers with customers. In 2018, Metro AG, a Germany-based bricks-and-mortar retailer, invested in a start-up offering AI-based visual recognition solutions for in-store insights.
Benefits
The report provides an in-depth analysis of the AI in retail and e-commerce market. Retailers can make the best use of the available data by deploying AI-based solutions for analyzing customer behavior, buying patterns, preferences so that personalized recommendations can be offered to them. With data-fueled customer insights, retailers can create unforgettable experiences for their customers and build long-term customer loyalty. Visual search is helping online as well as instore retailers to enhance revenue by being able to accurately suggest the product that the customers are looking for, ranging from apparels to household goods & accessories. The report discusses the market in terms of types, solutions, applications, and regions. Further, the report provides details about the major challenges impacting the market growth.
1 Executive Summary
1.1 AI Used Cases Emerging Across Subsector
1.2 Segments expected to dominate during the forecasted period
2 Industry Outlook
2.1 Industry Overview
2.2 Industry Trends
3 Market Snapshot
3.1 Total Addressable Market
3.2 Segment Addressable Market
3.2.1 PEST Analysis
3.2.2 Porter’s Five Force Analysis
3.3 Related Markets
4 Market Characteristics
4.1 Ecosystem
4.2 Market Trends and Impact
4.3 Value Chain Analysis
4.4 Market Segmentation
4.5 Market Dynamics
4.5.1 Drivers
4.5.1.1 Necessity to retain customers and enhance customer experience
4.5.1.2 Growing demand for enhancing revenue and improving productivity
4.5.1.3 Need to control fraud and Shrinkages
4.5.2 Restraints
4.5.2.1 Shortage of AI developers with required skills
4.5.2.2 High investment cost and variability of AI algorithms
4.5.3 Opportunities
4.5.3.1 Increasing penetration of smartphones
4.5.3.2 Rising shift towards Omnichann
4.5.4 DRO – Impact Analysis
5 AI in Retail and E-Commerce Market, By Type
5.1 Overview
5.2 Brick & Mortar
5.3 E-Commerce
6 AI in Retail and E-commerce Market, By Solutions
6.1 Overview
6.2 Customer Insights and Relationship Management
6.3 Personalized Product Recommendation
6.4 Price Optimization
6.5 Supply Chain Management and Demand Planning
6.6 Intelligent Virtual Assistant
6.7 Visual Search
6.8 Payments
6.9 Others
7 AI in Retail and E-Commerce Market, By Applications
7.1 Overview
7.2 Sales and Merchandise Planning
7.3 Reduced fraud and shrinkage
7.4 Logistics and Delivery
7.5 Trade Promotions Management
7.6 Others
8 AI in Retail and E-Commerce Market, By Region
8.1 Overview
8.2 North America
8.2.1 Market Size and Analysis
8.3 Europe
8.3.1 Market Size and Analysis
8.4 Asia Pacific
8.4.1 Market Size and Analysis
8.5 RoW
8.5.1 Market Size and Analysis
9 Competitive Landscape
9.1 Competitor Analysis
9.2 Product/Offerings Portfolio Analysis
9.3 Market Developments
9.3.1 Partnerships and Collaborations
9.3.2 Product Launches & Exhibitions
10 Vendor Profiles
10.1 IBM Corporation
10.1.1 Overview
10.1.2 Business Units
10.1.3 Geographic Revenue
10.1.4 Recent Developments
10.1.5 SWOT Analysis
10.1.6 Business Focus and Strategies
10.2 SAP
10.2.1 Overview
10.2.2 Business Units
10.2.3 Geographic Revenue
10.2.4 Recent Developments
10.2.5 SWOT Analysis
10.2.6 Business Focus and Strategies
10.3 Microsoft
10.3.1 Overview
10.3.2 Business Units
10.3.3 Geographic Revenue
10.3.4 Recent Developments
10.3.5 SWOT Analysis
10.3.6 Business Focus and Strategies
10.4 Amazon (AWS)
10.4.1 Overview
10.4.2 Business Units
10.4.3 Recent Developments
10.4.4 SWOT Analysis
10.4.5 Business Focus and Strategies
10.5 SAS
10.5.1 Overview
10.5.2 Recent Developments
10.5.3 SWOT Analysis
10.5.4 Business Focus and Strategies
11 Companies to Watch for
11.1 JDA Software
11.1.1 Overview
11.1.2 Product Profile
11.1.3 Analyst Opinion
11.2 Salesforce
11.2.1 Overview
11.2.2 Product Profile
11.2.3 Analyst Opinion
11.3 Symphony RetailAI
11.3.1 Overview
11.3.2 Product Profile
11.3.3 Analyst Opinion
11.4 Visenze
11.4.1 Overview
11.4.2 Product Profile
11.4.3 Analyst Opinion
11.5 Infinite Analytics
11.5.1 Overview
11.5.2 Product Profile
11.5.3 Analyst Opinion
12 Annexure
12.1 Report Scope
12.2 Market Definition
12.3 Research Methodology
12.3.1 Data Collation & In-house Estimation
12.3.2 Market Triangulation
12.3.3 Forecasting
12.4 Study Declarations
12.5 Report Assumptions
12.6 Abbreviations
TABLE 1 GLOBAL AI IN RETAIL AND E-COMMERCE MARKET REVENUE, BY TYPE, 2018–2025 ($BILLION)
TABLE 2 GLOBAL AI IN RETAIL AND E-COMMERCE MARKET REVENUE, BY SOLUTIONS, 2018–2025 ($BILLION)
TABLE 3 GLOBAL AI IN RETAIL AND E-COMMERCE MARKET REVENUE, BY APPLICATIONS 2018–2025 ($BILLION)
TABLE 4 GLOBAL AI IN RETAIL AND E-COMMERCE MARKET REVENUE BY REGIONS, 2018–2025 ($BILLION)
TABLE 5 NORTH AMERICA AI IN RETAIL AND E-COMMERCE MARKET REVENUE, BY TYPE, 2018–2025 ($BILLION)
TABLE 6 NORTH AMERICA AI IN RETAIL AND E-COMMERCE MARKET REVENUE, BY SOLUTIONS, 2018–2025 ($BILLION)
TABLE 7 NORTH AMERICA AI IN RETAIL AND E-COMMERCE MARKET REVENUE, BY APPLICATIONS, 20182025 ($BILLION)
TABLE 8 EUROPE AI IN RETAIL AND E-COMMERECE MARKET REVENUE, BY TYPE, 2018–2025 ($BILLION
TABLE 9 EUROPE AI IN RETAIL AND E-COMMERCE MARKET REVENUE, BY SOLUTIONS, 2018–2025 ($BILLION)
TABLE 10 EUROPE AI IN RETAIL AND E-COMMERCE MARKET REVENUE, BY APPLICATIONS, 2018–2025 ($BILLION)
TABLE 11 APAC AI IN RETAIL AND E-COMMERCE MARKET REVENUE, BY TYPE, 2018–2025 ($BILLION)
TABLE 12 APAC AI IN RETAIL AND E-COMMERCE MARKET REVENUE BY SOLUTIONS, 2018–2025 ($BILLION)
TABLE 13 APAC AI IN RETAIL AND E-COMMERCE MARKET REVENUE, BY APPLICATIONS, 2018–2025 ($BILLION)
TABLE 14 ROW AI IN RETAIL AND E-COMMERCE MARKET REVENUE, BY TYPE, 2018–2025 ($BILLION)
TABLE 15 ROW AI IN RETAIL AND E-COMMERCE MARKET REVENUE BY SOLUTIONS, 2018–2025 ($BILLION)
TABLE 16 ROW AI IN RETAIL AND E-COMMERCE MARKET REVENUE, BY APPLICATIONS, 2018–2025 ($BILLION)
TABLE 17 PRODUCT/OFFERINGS PORTFOLIO ANALYSIS: AI IN RETAIL AND E-COMMERCE MARKET
TABLE 18 MERGER & ACQUISITION, PARTNERSHIPS
TABLE 19 PRODUCT LAUNCHES & EXHIBITIONS, 2017–2018
TABLE 20 IBM CORPORTAION: RECENT DEVELOPMENTS
TABLE 21 SAP: RECENT DEVELOPMENTS
TABLE 22 MICROSOFT: RECENT DEVELOPMENTS
TABLE 23 AMAZON: RECENT DEVELOPMENTS
TABLE 24 HUAWEI: RECENT DEVELOPMENTS
TABLE 25 JDA SOFTWARE: PRODUCT PROFILE
TABLE 26 SALESFORCE: PRODUCT PROFILE
TABLE 27 SYMPHONY RETAIL: PRODUCT PROFILE
TABLE 28 VISENZE: PRODUCT PROFILE
TABLE 29 INFINITE ANALYTICS: PRODUCT PROFILE
Research Framework
Infoholic Research works on a holistic 360° approach in order to deliver high quality, validated and reliable information in our market reports. The Market estimation and forecasting involves following steps:
- Data Collation (Primary & Secondary)
- In-house Estimation (Based on proprietary data bases and Models)
- Market Triangulation
- Forecasting
Market related information is congregated from both primary and secondary sources.
Primary sources
Involved participants from all global stakeholders such as Solution providers, service providers, Industry associations, thought leaders etc. across levels such as CXOs, VPs and managers. Plus, our in-house industry experts having decades of industry experience contribute their consulting and advisory services.
Secondary sources
Include public sources such as regulatory frameworks, government IT spending, government demographic indicators, industry association statistics, and company publications along with paid sources such as Factiva, OneSource, Bloomberg among others.
