PUBLISHER: Bizwit Research & Consulting LLP | PRODUCT CODE: 1389237
PUBLISHER: Bizwit Research & Consulting LLP | PRODUCT CODE: 1389237
Global Visual Search Market is valued at approximately USD xx billion in 2022 and is anticipated to grow with a healthy growth rate of more than xx% over the forecast period 2023-2030. Visual search is a technology that allows users to search for information using images as the input query, rather than text-based keywords. It involves utilizing computer vision and artificial intelligence to analyze and understand the content of images, and then retrieve relevant results based on the visual attributes of those images. The Visual Search market is expanding because of factors such as the rising number of e-commerce platforms and growing demand for AI and machine learning Visual search enables users to find similar images, products, or content in an intuitive and efficient manner, bridging the gap between the physical and digital worlds. As a result, the demand for Visual Search has progressively increased in the international market during the forecast period 2023-2030.
Visual search can be integrated with personalized recommendations. It analyzes user preferences based on their image searches, e-commerce platforms can offer tailored suggestions that align with the customer's style and preferences. According to Statista, WooCommerce was the worldwide leading e-commerce software platform in 2023, with a market share of 39%. Squarespace Online Stores and Woo Themes ranked second and third, with shares of 14.95 and 14.67%, respectively. Furthermore, in 2021, the global retail e-commerce sales account for approximately USD 5.2 trillion and reach about USD 8.1 trillion by 2026. Another important factor that drives the Visual Search market is the increasing demand for AI and machine learning. Machine learning algorithms can calculate the similarity between images using learned representations. When a user inputs an image query, the system compares the features of the query image with those in its database to find the most visually similar results. In addition, as per Statista, in 2021, with a substantial 57% of cases, the foremost applications of artificial intelligence and machine learning involve enhancing customer experiences. The utilization of these technologies has the potential to drive progress across a range of business operations. Moreover, growing demand for visual search engines and increasing penetration of the internet and smartphones are anticipated to create lucrative growth opportunities for the market over the forecast period. However, high operational cost and a lack of adequate technological infrastructure are going to impede overall market growth throughout the forecast period of 2023-2030.
The key regions considered for the Global Visual Search Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the rising application of visual search engines and increasing technological advancements in the region. The region's dominant performance is anticipated to propel the overall demand for Visual Search. Furthermore, Asia Pacific is expected to grow fastest during the forecast period, owing to factors such as increased adoption of visual search engine solutions for e-commerce applications in the region.
The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.
The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
List of tables and figures and dummy in nature, final lists may vary in the final deliverable
List of tables and figures and dummy in nature, final lists may vary in the final deliverable