Global Image Recognition in CPG Market By Component (Hardware, Solution, Services), By Application (Inventory Analysis, Product and Shelf Monitoring Analysis, Auditing Product Placement, Product Placement Trend Analysis, Assessing Compliance and Competition, Category Analysis, Gauging Emotions), By Deployment Type (Cloud, On-Premise), By Region, and Key Companies - Industry Segment Outlook, Market Assessment, Competition Scenario, Trends and Forecast 2022-2032

Image Recognition in CPG Market Overview

Computer technology that uses algorithms and machine learning to recognize certain humans, animals, objects, or other distinct themes is called image recognition. It is connected to computer vision, allowing things such as persons to be recognized.

Machines operating aggressively on image data are called image recognition machines. It can be done in various ways, but convolutional neural networks are one of the most popular methods to filter images through a succession of artificial neuron layers. The convolutional neural network was built specifically for recognition and similar imaging.

The convolutional neural filter creates images to help identify the subject matter in machine learning systems using various techniques such as max packaging, phase setting, and padding. A photo is viewed as a raster, while an image is viewed as a vector by the machine. Raster images refer to a series of color pixels, and vector images are a collection of color-annotated polygons.

In the CPG business, image recognition software and services provide various advantages, including the precise identification of out-of-stock products on shelves, planogram compliance, product recommendations, greater product visibility, and the analysis of future requirements.

Detailed Segmentation –

Global Image Recognition in CPG Market is segmented based on Component, Application, Deployment Type, and Region. Represented below is a detailed segmental description:

Based on Component:

• Hardware
• Solution
• Services

Based on Application:

• Inventory Analysis
• Product and Shelf Monitoring Analysis
• Auditing Product Placement
• Product Placement Trend Analysis
• Assessing Compliance and Competition
• Category Analysis
• Gauging Emotions

Based on Deployment Type:

• Cloud
• On-Premise

Based on Region

• North America
• Europe
• Asia-Pacific
• South America
• Middle East & Africa

Market Dynamics –

Image recognition software is changing how consumer packaged goods firms handle customer interactions, sell products online & offline, and manage store inventories. Image recognition technology is increasingly being used to find things for purchase on the internet.

For instance, Snap, Snapchat’s parent company, is working on a visual product feature in Snapchat that will employ image recognition technology to allow users to capture images of objects in the real world and identify, explore, and purchase items on Amazon.

With the rise of the e-commerce industry, especially during the COVID-19 pandemic, entrepreneurs and merchants have realized that traditional sales promotions, marketing, and visual merchandising methods in the CPG industry will not be sustainable in the long run. Hence, to provide a next-level consumer experience, merchants are swiftly adjusting to the new era of AI and image recognition.

The application of picture recognition for shelf identification, product placement, and merchandising standards compliance is gradually gaining traction. Manufacturers, merchants, and marketers may use image recognition technology to understand their markets better and react quickly.

The expensive cost of developing image recognition systems may be a stumbling block to this market’s further expansion. Face recognition, deep learning, computer vision, AI, machine learning, and gesture recognition are enabling technologies with high development costs. Thus, companies with limited financial resources do not opt for picture recognition services, even if they want to boost efficiency with such solutions.

Microsoft Computer Vision API, Microsoft Emotion API, Amazon Recognition, Google Cloud Vision API, and IBM Watson Visual Recognition are among the most expensive vendor solutions, making it difficult for small CPG firms to compete. Small retail and e-Commerce enterprises would be deterred by the high costs of adopting image recognition solutions and teaching AI enablers to perform a specific task; this could be a limitation for image recognition solution vendors throughout the forecast period.

Competitive Landscape –

• IBM
• Google
• Qualcomm
• Microsoft
• AWS
• Trax
• Catchoom
• Slyce
• LTU Tech
• Imagga
• Vispera
• Blippar
• Ricoh innovations
• Clarifai
• Deepomatic
• Wikitude
• Huawei
• Honeywell
• Toshiba
• Oracle
• Others

Key developments –

2020:

• In April 2020, Coca-Cola and Microsoft teamed up. The alliance intends to centralize its corporate processes on the Microsoft Azure cloud while providing rich new digital experiences and innovative solutions. These technologies will help Coca-Cola gain fresh insights from data across the organization, allowing for a 360-degree perspective of the business and bettering customer and employee experiences.
• In March 2020, Trax purchased Survey.com to merge the two firms’ technology, better serve the demands of the burgeoning CPG market and supermarket merchants, and improve its position in the retail image recognition market.

For the Image Recognition in CPG Market research study, the following years have been considered to estimate the market size: