According to TechSci Research report, “Global Cognitive Computing in Retail Market By Component (Platform, Services (Managed, Professional)) By Technology (Machine Learning, Natural Language Processing, Deep Learning, Robotics, Computer / Machine Vision) By Deployment (Cloud, On-Premises) By Application (Customer Experience, Price Optimization, Demand Forecasting, Inventory Management, Automation, Others) By Company, By Region, Forecast & Opportunities, 2026”, the global cognitive computing in the retail market is expected to witness steady growth in the next five years. Cognitive computing is defined as self-learning technology that takes the help of algorithms to behave like the human brain’s thought process to efficiently utilize big data. e-Commerce channels integrate cognitive computing technology with their website to help the customers to select the best product based on their preferences. The process can be done by making the potential customers fill up the form by listing the specification, they are looking for a product and all the other crucial information about the customer. The cognitive computing system analyzes multiple sets of data to create personalized shopping experiences. Cognitive computing technology provides the feature of price optimization. It analyzes the demand for a particular product and then decides if the price has to be lowered or raised. Price optimization is also used for competition benchmarking and the retailers use this information to make informed decisions on optimizing their price to make maximum profit.
The COVID-19 outbreak across the world which has been declared as a pandemic by World Health Organization has affected several countries adversely. Leading authorities around the globe imposed lockdown restrictions and released a set of precautionary measures to contain the spread of novel coronavirus. Coronavirus-affected patients started suffering from shortness of breath along with coughing and sneezing. Leading authorities imposed the restrictions on import and export activities which negatively affected the supply chain. Rapid preference shift of the consumers to buy through the online channels to avoid the interaction with other people and practice social distancing contributed to surging the demand for e-commerce sites around the globe.
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Global cognitive computing in retail market is segmented into component, technology, deployment, application, regional distribution, and company. Based on the deployment, the market can be bifurcated into cloud and on-premises. The cloud deployment segment is expected to hold a major market share in the forecast period, 2022-2026. Using the cloud-based model helps in reducing the operational cost and it has unlimited storage capacity. It is scalable and can be accessed from any remote location. Based on the application, the market can be divided into customer experience, price optimization, demand forecasting, inventory management, automation, and others. The demand forecasting segment is expected to witness growth in the next five years. It predicts the number of sales of a particular product and helps organizations to maintain a proper supply chain. It helps in the management of inventories by providing accurate results to make informed decisions.
SparkCognition, Inc., Expert System USA, IBM Corporation, Microsoft Corporation, Google LLC, Teradata Corporation, Cisco Systems, Inc., Hewlett Packard Enterprises Co., CognitiveScale, Inc., Deepmind Technologies, Amazon Web Services, Inc., Enterra Solutions LLC, SAS Institute, Inc., Virtusa Corporation, Tata Consultancy Services Ltd are the leading players operating in global cognitive computing in retail market. Service Providers are increasingly focusing on research and development process to fuel higher growth in the market. To meet evolving customer demand with respect to better efficiency and durability, several cognitive computing in retail service providers are coming up with their technologically advanced offerings.