In response to this rapidly changing environment, firms have turned to strategies that enable them consolidate or expand their market shares within the application of Artificial Intelligence (AI) on Retail & E-Commerce Marketplaces. One way to approach it is through focus on technological innovation to develop and offer advanced capable solutions that are customized according to requirements of retail (shopping) outlets and e-shopping sectors. Therefore, using latest technologies in machine learning, natural language processing (NLP), computer vision help brands reach out personalized responses when seeking for efficient inventory management options or customer engagement tools used in online marketing campaigns.
The pricing strategy plays a significant role when positioning oneself within the market share space in Applied AI in Retail & E-commerce Market. Some businesses adopt cost leadership strategy aiming at offering lower priced artificial intelligent solutions compared to their competitors targeting price sensitive retailers and e-markets ensuring competitive prices so that they obtain large market share nevertheless others position themselves as premium providers emphasizing features such as advanced recommendation engines, personalized shopping experiences, and comprehensive data analytics. Companies like these target high-end retail brands and online platforms where a segment of consumers that are willing to pay premium prices for the most modernized AI-based solutions in the field of retail.
In addition, market share positioning is also influenced by collaborations and strategic partnerships within Applied AI in Retail & E-commerce Market. Many companies flirt with alliances involving e-marketplace platforms, brick-and-mortar retailers or parcel delivery services to improve how their AI solutions can be used in retail sector. Through this collaboration, they have been able to develop a wider range of services for different retailers giving them a better market reach while at the same time addressing any unique requirements from each retailer. Furthermore, partnering with established retail chain owners or major online stores on joint projects or long-term supply contracts gives them a stable income source with stronger presence in the market.
Customer-centric strategies are vital to increasing market share within the Applied AI in Retail & E-commerce Market position. Firms that concentrate on offering seamless buying encounters backed by personalized suggestions and responsive customer care establish strong bonds with retailers and e-consumers alike. This way, positive user experiences lead to customer loyalty among others leading to increased market shares over time through word of mouth referrals thereby causing amplification effects. Moreover, understanding specific retail and e-commerce needs/cases enables customization of AI solutions across specific market segments resulting into competitive advantages.
Report Attribute/Metric | Details |
---|---|
Market Opportunities | AI can facilitate international expansion by automating translation, currency conversion, and localization efforts for e-commerce businesses |
Market Dynamics | Growing demand due to capability of Applied AI offering tailored product recommendations, pricing, and content, enhancing customer satisfaction & conversion rates Ability of Applied AI of demand forecasting, inventory management, and logistics optimization leading to cost savings, reduced stockouts, and improved order fulfillment |
Applied AI in Retail & E-commerce Market Size was valued at USD 22.1 billion in 2022. The Applied AI in Retail & E-commerce Market is projected to grow from USD 34.2 billion in 2023 to USD 325.5 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 30.86% during the forecast period (2023 - 2032). Growing demand due to capability of Applied AI offering tailored product recommendations, pricing, and content, enhancing customer satisfaction & conversion rates and ability of Applied AI of demand forecasting, inventory management, and logistics optimization leading to cost savings, reduced stockouts, and improved order fulfillment. These are just few of the market drivers that are driving the market.
FIGURE 1: APPLIED AI IN RETAIL & E-COMMERCE MARKET SIZE, 2019-2032 (USD BILLION)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Growing demand due to capability of Applied AI offering tailored product recommendations, pricing, and content, enhancing customer satisfaction & conversion rates is propelling the market growth
The growing demand for Applied AI-driven tailored product recommendations, pricing, and content in the retail and e-commerce market is a significant driver for the adoption of Applied AI. AI algorithms analyze a customer's past behavior, preferences, and purchase history to recommend products that are highly relevant to them. This level of personalization creates a more satisfying shopping experience. Tailored recommendations and pricing make customers feel valued and understood, which can lead to increased loyalty and repeat purchases. AI recommendations ensure that customers see products that match their interests and needs, reducing the time and effort required to find suitable items. This convenience contributes to higher customer satisfaction. This can result in fewer returns and exchanges, leading to greater customer satisfaction. Personalized content and recommendations typically lead to higher CTRs in marketing campaigns. Retail Industry AI Applications are helping retailers create more personalized shopping experiences, optimize operations, reduce costs, and stay competitive in the evolving retail landscape. This growing recognition of the impact of AI-driven personalization is a driving force behind the expanding adoption of Applied AI in the retail and e-commerce market and the market CAGR.
The ability of Applied AI to excel in demand forecasting, inventory management, and logistics optimization plays a pivotal role in driving the adoption of Applied AI in the retail and e-commerce market. AI utilizes historical sales data, market trends, seasonality, and other relevant factors to generate highly accurate demand forecasts. This precision enables retailers to align their inventory levels with actual customer demand. AI-driven systems can monitor inventory levels in real-time and trigger automatic replenishment orders when stock reaches predefined thresholds. With improved demand forecasting, inventory management, and logistics optimization, retailers and e-commerce companies can lower their overall operating costs, including reduced labor costs and transportation expenses. Due to this, the ability to achieve cost savings, reduce stockouts, and enhance order fulfillment efficiency is a compelling driver for the adoption of Applied AI in the retail and e-commerce market. E-commerce AI enhancements are continuously evolving, driven by advancements in AI technology and the increasing demand for personalized and efficient online shopping experiences. Thus, it is anticipated that this aspect will accelerate the Applied AI in Retail & E-commerce Market revenue globally.
The Applied AI in Retail & E-commerce Market segmentation, based on Technology, includes Machine Learning, Natural Language Processing (NLP), Computer Vision, Speech Recognition, and Predictive Analytics. The Machine Learning segment held the majority share in 2022 in the Applied AI in Retail & E-commerce Market data and is projected to be the fast-growing segment in the forecast period. Machine learning is a critical segment within the field of Applied AI in the retail and e-commerce market. It plays a central role in driving personalization, optimizing operations, and enhancing decision-making processes. Machine learning algorithms analyze customer data, such as browsing history, purchase behavior, and preferences, to provide personalized product recommendations. These recommendations increase the likelihood of customers finding and purchasing products that align with their interests.
The Applied AI in Retail & E-commerce Market segmentation, based on Application, includes Customer Service & Support, Sales & Marketing, Supply Chain Management, Price Optimization, Payment Processing, and Product Search & Discovery. The Customer Service & Support segment dominated the market growth in 2022 and is projected to be the faster-growing segment during the forecast period, 2023-2032. The Customer Service & Support segment is a crucial area of Applied AI in the retail and e-commerce market, as it enables businesses to provide efficient, personalized, and 24/7 customer assistance. AI-powered chatbots and virtual assistants handle routine customer inquiries, such as order tracking, product information, and return requests, freeing up human agents to focus on more complex issues. AI can route customer queries to the most appropriate human agents or departments, ensuring that customers receive prompt and accurate responses.
FIGURE 2: APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2022 & 2032 (USD BILLION)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
The Applied AI in Retail & E-commerce Market segmentation, based on Deployment Mode, includes on-premise, and cloud based. The on-premise segment held the majority share in 2022 in the Applied AI in Retail & E-commerce Market data and is projected to be the fast-growing segment in the forecast period. The On-Premise segment in the Applied AI in Retail & E-commerce Market refers to the deployment mode where AI solutions and systems are hosted and operated within the physical infrastructure of the retailer or e-commerce company, rather than being hosted on cloud-based servers or third-party data centers. In this deployment model, AI applications, servers, storage, and other necessary hardware and software components are located within the retailer's or e-commerce company's own data centers or facilities.
The Applied AI in Retail & E-commerce Market segmentation, based on End User, includes Retailers, E-commerce Platforms, Consumer Goods Manufacturers, Logistics & Supply Chain Companies, and Others. The Retailers segment held the majority share in 2022 in the Applied AI in Retail & E-commerce Market data and is projected to be the fast-growing segment in the forecast period. Retailers use Applied AI to analyze customer data and behavior, enabling personalized product recommendations and content to improve the AI-powered shopping experience. AI optimizes supply chain operations, reducing costs and enhancing the efficiency of inventory movement and logistics. Retailers analyze customer behavior through AI to gain insights into shopping patterns, preferences, and trends.
By region, the study provides the market insights into North America, Europe, Asia-Pacific, Middle East & Africa, and South America. North America Applied AI in Retail & E-commerce Market accounted for USD 7.65 billion in 2022 with a share of around 34.61% and is expected to exhibit a significant CAGR growth during the study period. The growth of Applied AI in the Retail & E-commerce Market in North America is driven by several key factors that reflect the region's strong technology infrastructure, consumer demand for personalized experiences, and the competitive nature of the retail industry. North America, particularly the United States, boasts a mature and robust technology ecosystem with a concentration of AI research, development, and innovation centers. This fosters a conducive environment for the growth of Applied AI applications in retail and e-commerce. Consumers in the region value convenience and expect seamless shopping experiences, which Applied AI can deliver through features like chatbots, virtual assistants, and smooth checkout processes.
Further, the major countries studied in the market report are: The U.S, Canada, Germany, France, UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.
Figure 3: APPLIED AI IN RETAIL & E-COMMERCE MARKET SHARE BY REGION, 2022 & 2032 (USD BILLION)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Europe Applied AI in Retail & E-commerce Market accounts for the second-largest market share. The e-commerce sector in Europe has experienced significant growth, and it continues to expand rapidly. This growth has incentivized retailers and e-commerce platforms to invest in Applied AI technologies to stay competitive and improve operational efficiency. Moreover, Germany Applied AI in Retail & E-commerce Market held the largest market share, and the UK Applied AI in Retail & E-commerce Market was the fastest growing market in the European region.
Asia-Pacific Applied AI in Retail & E-commerce Market accounts for the third-largest market share and is projected to continue increasing due to rapid digital transformation. Asia-Pacific is experiencing rapid digital transformation, with more consumers and businesses going online. Retailers and e-commerce platforms are leveraging Applied AI to enhance their digital offerings and customer experiences. Further, the China Applied AI in Retail & E-commerce Market held the largest market share, and the India Applied AI in Retail & E-commerce Market was the fastest growing market in the region.
The Middle East & Africa Applied AI in Retail & E-commerce Market is rapidly growing due to increasing cross border trade. Cross-border e-commerce is growing in Middle East & Africa, and Applied AI helps retailers manage international operations, currency conversions, and localization to cater to a diverse customer base. The region's e-commerce market is competitive, with both local and international players. AI is used to gain a competitive edge through improved customer experiences, personalized recommendations, and efficient supply chain management.
Also, The South America Applied AI in Retail & E-commerce Market is growing due to increase in Tech-Savvy Consumers. South America has a growing population of tech-savvy consumers who are increasingly comfortable with digital technologies. AI-driven features such as personalized recommendations and mobile commerce are well-received by this demographic.
Major market players are spending a lot of money on R&D to increase their product lines, which will help the Applied AI in Retail & E-commerce Market grow even more. Market participants are also taking a range of strategic initiatives to grow their worldwide footprint, with key market developments such as new product launches, mergers and acquisitions, contractual agreements, increased investments, and collaboration with other organizations. Competitors in the Applied AI in Retail & E-commerce industry must offer cost-effective items to expand and survive in an increasingly competitive and rising market environment.
One of the primary business strategies adopted by manufacturers in the global Applied AI in Retail & E-commerce industry to benefit clients and expand the market sector is to manufacture locally to reduce operating costs. In recent years, Applied AI in Retail & E-commerce industry has provided Technology segment with some of the most significant benefits. The Applied AI in Retail & E-commerce Market major player such as Quantifind, OpenAI, Accenture, DataRobot, SAS, IBM, Microsoft, Adobe, NVIDIA, Intel, Google, Amazon, and other market players.
Brain Corp, San Diego, is a technology-based company specializing in the development of intelligent, autonomous navigation systems for everyday machines. In March 2023, Brain Corp has rolled out its autonomous floor scrubber ‘Auto-C’ that cleans the aisle of a Walmart’s store and captures in real-time, images of every single item in the store.
Quantifind
OpenAI
Accenture
DataRobot
SAS
IBM
Microsoft
Adobe
NVIDIA
Intel
Amazon
Others
August 2023:The Singapore MIT-Alliance for Research and Technology (SMART), a research enterprise in Singapore, has launched a new interdisciplinary research group working on rise of artificial intelligence and other new technologies.Â
September 2023:Zomato, a leading online meal delivery service, has introduced ‘Zomato AI’, an interactive chatbot to make food ordering process more convenient & personalized.
Machine Learning
Natural Language Processing (NLP)
Computer Vision
Speech Recognition
Predictive Analytics
Customer Service & Support
Sales & Marketing
Supply Chain Management
Price Optimization
Payment Processing
Product Search & Discovery
On-premise
Cloud-based
Retailers
E-commerce Platforms
Consumer Goods Manufacturers
Logistics & Supply Chain Companies
Others
US
Canada
Germany
France
UK
Italy
Spain
Rest of Europe
China
Japan
India
Australia
South Korea
Rest of Asia-Pacific
South Africa
Brazil
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