July 20, 2024

The Rise Of Autonomous Retail Robots Is Anticipated To Openup The New Avenue For Retail Robots Market.

The Retail Robots Market is estimated to be valued at US$ 15.63 Bn in 2023 and is expected to exhibit a CAGR of 30% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.

Market Overview:
Retail robots are automated machines that are designed to perform routine tasks in retail stores and warehouses. They are equipped with technologies such as computer vision, 3D sensing, machine learning, and navigation to assist humans. Common applications of retail robots include shelf monitoring, stocking, delivery, and cashierless checkouts. They help retailers improve operational efficiency, reduce costs, and enhance customer experience.

Market Dynamics:
Increasing labor costs: Labor costs have been rising steadily over the years, pushing up the overall operational costs for retailers. Retail robots offer a cost-effective solution as they can perform labor-intensive activities efficiently without additional wages and benefits. This is a key factor driving the adoption of retail robots across industries.
Rapid growth of e-commerce: The accelerated growth of online shopping in recent times has compelled retailers to look for smart automation solutions to manage the complexities of omnichannel fulfillment. Retail robots assist in various e-commerce workflows such as inventory management, order picking, packing, and shipping. Their integration improves warehouse productivity and order processing speeds.

Segment Analysis
The retail robots market is dominated by goods-to-person order picking segment, which holds more than 30% share of the total market. This is because goods-to-person robots help in efficient order picking by bringing shelves of products to the pickers, which significantly increases productivity and reduces manual efforts. These types of robots are highly adopted by large retail warehouses and distribution centers to optimize order fulfillment operations.

PEST Analysis
Political:
Various governments across the world are supporting technological adoption in retail sector through funding and initiatives to enhance customer experience and business productivity.
Economic: High labor costs are driving many retail companies to invest in automation technologies like robots. This is helping reduce operational expenses and boosting profit margins.
Social: Customers appreciate personalized and hassle-free shopping. Retail robots are enhancing convenience by providing information, assisting shoppers, and enabling new engagement models.
Technological: Advancements in AI, machine vision, mobility, and IoT are allowing the development of sophisticated robots for inventory management, customer service, and autonomous delivery of products within retail premises.

Key Takeaways
The Global Retail Robots Market Trend is expected to witness high growth, exhibiting CAGR of 30% over the forecast period of 2023 to 2030, due to increasing focus on operational efficiency and productivity gains through automation. The market size is projected to increase from US$ 15.63 Bn in 2023 to over US$ 100 Bn by 2030.

Regional analysis: North America currently dominates the market with over 35% share due to significant technology adoption among major retail chains. Asia Pacific is anticipated to emerge as the fastest growing regional market, expanding at a CAGR of over 35% during the forecast period, led by countries like China and India rapidly automating retail operations to meet rising demand.

Key players analysis: Key players operating in the retail robots market are Amazon Robotics, Bossa Nova, Simbe Robotics, ABB Robotics, Greyorange, Softbank Robotics, Honda Motor Co. Limited, and others. These companies are focusing on developing autonomous mobile robots as well as goods-to-person order picking robots integrated with advanced computer vision and AI capabilities.

*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it