IBM (US), Google (US), Qualcomm (US), Microsoft (US), AWS (US), Trax (Singapore), Catchoom (Spain), Slyce (US), LTU Tech (France), Imagga (Bulgaria), Vispera (Turkey), Blippar (UK), Ricoh innovations (US), Clarifai (US), Deepomatic (France), Wikitude (Austria), Huawei (China), Honeywell (US), Toshiba (Japan), Oracle (US).

MarketsandMarkets forecasts the Image Recognition in CPG 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 21.7 % from 2020 to 2025. Increased in the need for efficient and profitable retail execution processes with adherence to compliance standards and technological advancements to boost the adoption of image recognition in CPG market across the globe during the forecast period.

Based on component, the hardware segment to account for the largest market size during the forecast period

This segment includes image sensors integrated with cameras. Hardware is an integral part of image recognition technology in the CPG market. Many companies like IBM and Qualcomm provide their company made sensors which help detect products, shelf life and even trends. For instance, Qualcomm offers the Vision Intelligence 400 platform that is built with powerful image processing and ML for smart camera products; it performs face detection, face recognition, product classification, and license plate recognition.

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Based on application, the product and shelf monitoring analysis segment to account for the largest market size during the forecast period

The pandemic situation has forced people to concentrate more on online e-commerce businesses. Many leading retailers and CPG companies have adopted AI and image recognition technology for shelf monitoring and product identification. Computer vision and image recognition are used for product discovery, product recommendations and trend analysis.

The image recognition in CPG market includes major vendors, such as IBM (US), Google (US), Qualcomm (US), Microsoft (US), AWS (US), Trax (Singapore), Catchoom (Spain), Slyce (US), LTU Tech (France), Imagga (Bulgaria), Vispera(Turkey), Blippar(UK), Ricoh innovations (US), Clarifai(US), Deepomatic (France), Wikitude (Austria), Huawei (China), Honeywell (US), Toshiba (Japan), Oracle (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 CPG market.

IBM has been leading the field of AI since the 1950s, bringing one of the most innovative solutions to the market in the field of image recognition. IBM introduced Watson, an AI technology that can be applied across various verticals, such as finance, retail, travel and hospitality, and healthcare. Watson uses NLP and ML to reveal significant insights from large volumes of unstructured data. Using the Watson suite of APIs, retailers can receive immense benefits by segmenting customers individually and personalizing their shopping experiences. This ultimately results in more frequent shopping and thereby ensures higher customer loyalty. A retailer incorporating Watson API into the online shopping experience can deliver personalized advice on clothing with the help of NLP. As customers shop online, their choices can be refined, based on factors such as location, activity, gender, past purchase behaviour, and month of the year. By processing such data, recommendations will be provided based on the occasion and weather conditions in the region.

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Google specializes in offering search, ads, mobile, Android, online video, apps, ML, and Virtual Reality (VR) solutions. It is a major player in the global image recognition in CPG market. The company offers Vision AI to derive insights from product images in the cloud.  Vision AI is categorized into AutoML Vison and Vision API. AutoML Vision simplifies the uploading image process whereas Vision API helps to understand the content of an image by encapsulating powerful ML models, classifies images into thousands of categories, automatically detects individual objects and faces within images, and finds and reads printed words contained within images. The company focuses on adopting organic and inorganic growth strategies to gain a strong foothold in the market. It has invested in new businesses, products, services, and technologies and is expected to continue doing so. Google is expanding its pool of ML talent with the purchase of a startup that specializes in smartphone image recognition.

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