Image Recognition in Retail Market Report 2025

The image recognition in retail market size has grown exponentially in recent years. It will grow from $2.38 billion in 2024 to $2.88 billion in 2025 at a compound annual growth rate (CAGR) of 20.7%. The growth in the historic period can be attributed to efforts to enhance customer engagement, growing importance of visual merchandising, increased availability of high-quality data, competition and differentiation in retail, customer expectations for seamless shopping, enhanced security and loss prevention, regulatory compliance and privacy measures.

The image recognition in retail market size is expected to see exponential growth in the next few years. It will grow to $6.09 billion in 2029 at a compound annual growth rate (CAGR) of 20.6%. The growth in the forecast period can be attributed to continued growth of online shopping, global expansion of e-commerce platforms, rise of visual search engines, enhanced in-store shopping experiences, demand for sustainable and ethical products, personalized marketing campaigns, demand for contactless shopping, focus on accessibility and inclusivity. Major trends in the forecast period include visual search capabilities, personalized shopping recommendations, in-store customer analytics, automated checkout systems, ai-powered customer service, real-time pricing and competitor analysis, integration with e-commerce platforms.

The increasing adoption of smartphones is anticipated to boost the demand for image recognition in the retail market in the future. A smartphone is a mobile electronic device that merges the capabilities of a traditional mobile phone with advanced computing functionalities. The widespread use of smartphones creates a large user base for image recognition applications and services. For example, in February 2024, Uswitch Limited, a UK-based financial conduct authority, reported that mobile connections in the UK reached 71.8 million, reflecting a 3.8% increase from the previous year, amounting to approximately 2.6 million additional connections. Furthermore, it is projected that the UK's population will grow to 68.3 million by 2025, with an estimated 95% of the population, or around 65 million people, owning a smartphone. Thus, the rising use of smartphones is expected to drive the growth of image recognition in the retail market.

The growth of online retail is projected to drive the expansion of image recognition in the retail market in the future. Online retail, commonly referred to as e-commerce, involves the buying and selling of goods and services over the Internet. Image recognition technology enhances the online shopping experience by enabling features such as visual search, personalized product recommendations, and augmented reality, all of which improve customer engagement and streamline the purchasing process. For example, in April 2024, the European Commission, a governing body in Belgium responsible for implementing decisions and upholding EU treaties, reported that among individuals aged 16-74 surveyed, 92% had used the internet in the past year, with 70% making purchases, reflecting a 2% increase from 2022. Additionally, 75% of EU internet users bought items online in 2023, underscoring the continued growth of e-commerce. Consequently, the expansion of online retail is driving the growth of image recognition in the retail market.

Technological advancement is a significant trend gaining traction in the image recognition segment of the retail market. Key players in this sector are prioritizing technological innovations to maintain their competitive edge. For example, in December 2023, Mastercard, a US-based credit card company, introduced Shopping Muse, an AI tool designed to provide product recommendations. This tool features advanced image recognition capabilities, enabling users to upload images of desired products, after which it suggests similar items based on visual similarities, even if those products do not have specific technical tags. This functionality enhances the personalization and precision of product recommendations, making it especially valuable in retail environments where visual aesthetics heavily influence consumer choices.

Major players in the image recognition retail sector are intensifying their focus on AI-powered tools to gain a competitive advantage. One such tool, Shopping Lens, enables users to visually search and shop for real-world items through their smartphones. For instance, Klarna launched Shopping Lens in October 2023, leveraging AI to translate product images into search terms, guiding users to the best deals available on its app. This move aims to enhance the shopping experience for approximately 150 million active Klarna users, aligning with the growing demand for AI-driven shopping assistants and personalized experiences.

In March 2024, BigBear.ai, a US-based provider of AI-driven business intelligence solutions, acquired Pangiam Intermediate Holdings LLC for $70 million. This acquisition seeks to leverage Pangiam's expertise in facial image recognition and advanced biometrics, integrating it with BigBear.ai's existing computer vision capabilities. Pangiam Intermediate Holdings, LLC specializes in vision AI technology, encompassing image recognition and advanced biometrics for various sectors, including global trade, retail, travel, and digital identity.

Major companies operating in the image recognition in retail market are Catchoom Technologies S.L., Ricoh Innovations Corporation, Blippar Ltd., Jumio Corporation, Google LLC, Wikitude GmbH, Trax Retail Solutions Pte. Ltd., Snap2Insight Inc., Clarifai Inc., Slyce Inc., ParallelDots Inc., NEC Corporation, Huawei Technologies Co. Ltd., Qualcomm Incorporated, Amazon Web Services Inc., Zippin Inc., Vispera Information Technologies Ltd., Hitachi Ltd., NVIDIA Corporation, International Business Machines Corporation, Intel Corporation, Toshiba Corporation, Honeywell International Inc., Sharp Corporation, Attrasoft Inc., Syte Visual Conception Ltd., Shutterstock Inc.

North America was the largest region in the image recognition in retail market share in 2024. The regions covered in the image recognition in retail market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the image recognition in retail market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Image recognition in retail involves algorithms that analyze images or videos, decoding their content to identify specific brands, products, categories, or other relevant elements. This technology serves various purposes within retail, such as maintaining shelf organization, ensuring display compliance, gaining competitive insights, and adhering to planograms.

Several types of image recognition are employed in retail settings. These include code recognition, digital image processing, facial recognition, object recognition, and other related methods. Code recognition, for instance, serves as an identification solution capable of reading and validating QR codes, traditional barcodes, and 2D data matrix codes. This technology utilizes a combination of hardware, software, and services, deployable through both on-premises and cloud-based systems. Its applications span across functionalities like scanning, image search, security and surveillance, augmented reality, marketing, advertising, and more.

The image recognition in retail market research report is one of a series of new reports that provides image recognition in retail market statistics, including image recognition in retail industry global market size, regional shares, competitors with an image recognition in retail market share, detailed image recognition in retail market segments, market trends and opportunities, and any further data you may need to thrive in the image recognition in retail industry. This image recognition in retail market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The image recognition in retail market consists of revenues earned by entities by providing image recognition in retail for planogram compliance, detecting empty shelves, assessing competition and personalized searches for customers. The market value includes the value of related goods sold by the service provider or included within the service offering. The image recognition in retail market also includes sales of hardware and software that are used to provide image recognition solutions in retail. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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