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Image Recognition in Retail Market Growing at a CAGR 22.0% | Key Player AWS, IBM, Google, Microsoft, TRAX

Image Recognition in Retail Market Growing at a CAGR 22.0% | Key Player AWS, IBM, Google, Microsoft, TRAX

“Google (US), Microsoft (US), AWS (US), IBM (US), Trax (Singapore), NEC Corporation (Japan), Qualcomm (US), Slyce (US), Catchoom (Spain), Intelligence Retail (US), Imagga (Bulgaria), Vispera (Turkey), Snap2Insight (US), ParallelDots (US), Clarifai (US), Deepomatic (France), Blippar (UK), Ricoh Innovations (US), LTU (France), ShelfWise (Poland), Trigo (Israel)”
Image Recognition in Retail Market by Technology (Code Recognition, Digital Image Processing) Component (Software and Services), Application (Visual Product Search, Security Surveillance), Deployment Type, and Region – Global Forecast to 2025

MarketsandMarkets forecasts the Image Recognition in Retail Market size to grow from USD 1.4 billion in 2020 to USD 3.7 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 22.0% from 2020 to 2025. Increasing technological developments to boost the adoption of image recognition solutions among retailers; and need to increase on-shelf availability, enhance customer experience, and maximize RoI are expected to increase the adoption of image recognition in retail across the globe during the forecast period.

Professional services to account for the highest market share during the forecast period

Service providers provide professional services, such as consulting, training, support, and maintenance services that help retailers gain descriptive knowledge about software. Vendors also provide online and onsite training so that retailers can use software in a better way. Providing training and support services while deploying image recognition software has generated a level of awareness about the use of the software, thus strengthening the growth for the services segment. Continuous training sessions to resolve business complexities further enable retailers to gain expertise in newly adopted software.

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Cloud segment to grow at a higher CAGR during the forecast period

The increasing use of the internet, along with the high adoption of innovative technologies, such as the web, mobile, social media, and analytics supplement the growth of cloud-based image recognition techniques. Retailers deploy image recognition software solutions on-premises to encourage and strengthen marketing endeavors, which involve high costs with limited scalability. This has encouraged retailers to adopt cloud-based image recognition solutions as they do not involve high upfront costs. Cloud-based services reduce licensing costs, cut down on unnecessary IT staff, focus on maintenance, and offer retailers with greater flexibility to expand their business. However, to implement a cloud model deployment, enterprises first need to analyze the benefits of their existing set-up and those that a cloud-based service can give them. In addition, security concerns remain a critical issue that restricts its adoption; however, the security issue is gradually being eliminated through rigorous security tests of the highest standards by third parties

The image recognition in retail market includes major vendors, such as Google (US), Microsoft (US), AWS (US), IBM (US), Trax (Singapore), NEC Corporation (Japan), Qualcomm (US), Slyce (US), Catchoom (Spain), Intelligence Retail (US), Imagga (Bulgaria), Vispera (Turkey), Snap2Insight (US), ParallelDots (US), Clarifai (US), Deepomatic (France), Blippar (UK), Ricoh Innovations (US), LTU (France), ShelfWise (Poland), Trigo (Israel), Wikitude (Austria), Standard Cognition (US), Huawei (China), Honeywell (US), and Zippin (US). These players have adopted different growth strategies to expand their global presence and increase their market shares. New product launches, partnerships, and acquisitions are some of the important strategies adopted by the major players to grow further in the image recognition in retail industry.

Trax (Singapore) is recognized as one of the leading vendors in the image recognition in retail market. The company uses combination of image recognition, deep learning, and data science technologies to provide fast, accurate, and optimizing solutions. With the help of these technologies, it further provides real-time actionable insights from the given shelf images. These insights help businesses make informed decisions, improve efficiency, measure and track their in-store execution performance, enhance product availability, minimize distribution gaps, recognize category opportunities, and increase their sales. Further, the company majorly focuses on inorganic business growth strategies. For instance, in March 2020, Trax acquired Through this acquisition, Trax would combine technologies from both the companies to cater to the needs of the emerging CPG market and grocery retailers and strengthen its position in image recognition in retail market.

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IBM (US) is one of the major providers of various technology products, solutions, and services. The company firmly believes in providing its customers with enhanced product offerings pertaining to the current market trends of image recognition in retail. IBM provides Watson Visual Recognition in image recognition in retail market. It uses deep learning algorithms to analyze images for objects, faces, and other content. Moreover, it speedily and accurately tags, and classifies and trains visual content using ML. It offers various features, such as custom object detection, custom classification, general tagging, and auto labeling.

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