Report Description
Visual search is changing the face of machine learning and artificial intelligence with a potential to reform how consumers buy and find products. By streamlining the method of search, organizations can move closer to instant gratification that most customers demand. With help of studies, it is observed that more than 60% of millennials desire the convenience of visual search over any other novel technology and the likes of Google, Pinterest and Amazon have already developed substantial capabilities in this field.
The global Visual Search Technology: Changing The Way We Search! market is anticipated to increase at a 17.50 % CAGR to reach value USD 32,984.022 million in 2028
.jpg "The Global Visual Search Technology Market 2018-2028 (USD Million)")
“The future of search will be about pictures rather than keywords,” stated Pinterest CEO, Ben Silbermann. And with so much consumer and brand weight behind it, it’s no surprise that visual search promises to be a breakout trend of 2019.
The accuracy of visual search has improved as image recognition tools have access to big training sets of images, and visual search engines learn about the implicit questions users ask when submitting images. This has created a virtuous cycle, where more people use visual search, which in turn creates more accurate visual search tools.
Mobile visual search has gained high popularity in APAC, especially in Japan, China and South Korea where it is used in online fashion stores. Not only this, visual search engines are also used as tools for mapping, concept generation and outlining. Top global visual search providers are slowly and steadily announcing their products in the emerging countries of Asia like Indonesia and India due to their enormous market potential.
Application of visual search technology includes baggage scanning, security screening, electronic component manufacturing, navigation systems and in retail for jewelry and clothing. Since past few years, the market had witnessed a huge growth in varied end-users mainly aviation, automotive OEMs, e-commerce, electronics, forestry and many more. Currently, e-commerce dominates other all end-users segment and is anticipated to remain the same in the forthcoming years. Growing rate of investments in visual search technology coupled with higher adoption of visual search engines is projected to propel the visual search market.
Market Research and Market Trends of Visual Search
Currently, the visual search engines are witnessing significant demand due to its increasing applications in retail and e-commerce sectors. This is mainly due to the capabilities of visual search which identifies an image accurately using advanced machine learning and AI technology
Companies’ huge investments, joint venture and partnerships activities in this market lead to the exchange of methodologies and technology for new developments of these visual search engines which is likely to boost the global visual search market.
Many research and development activities to increase the efficiency of visual search machines are being undertaken which is enhancing the market growth. The integration of machine learning with visual search engines has improved the image processing drastically.
Some of the prominent key players operating the visual search technology market are Google (U.S.), Slyce (Canada), Clarifai (U.S.), Veritone (U.S.), ViSenze (Singapore), Ever AI (U.S.).
Visual Search Technology Scope
| Metrics | Details |
| Base Year | 2022 |
| Historic Data | 2018-2019 |
| Forecast Period | 2022-2028 |
| Study Period | 2018-2028 |
| Forecast Unit | Value (USD) |
| Revenue forecast in 2028 | USD 32,984.022 million |
| Growth Rate | CAGR of 17.50 % during 2018-2028 |
| Segment Covered | By Offering Analysis, Vertical Analysis, Type, Application, Regions |
| Regions Covered | North America, Europe, Asia Pacific, South America, Middle East and Africa |
| Key Players Profiled | IBM (US), Google (US), Qualcomm (US), Microsoft (US), AWS (US), Trax (Singapore),NEC Corporation (Japan), Catchoom (Spain), Slyce (US), LTU Tech (France), Vispera(Turkey), Blippar(UK), Clarifai(US), Wikitude (Austria), Huawei (China), Honeywell (US), Toshiba (Japan), Oracle (US), Trigo(Israel), INFFRD (US), AIRY3D(Canada), Standard Cognition (US), Unispectral LTD (Israel), Snap2Insight(US), restb.ai(Spain), Vize by Ximilar(Czech Republic), Mirror that Lock (US) |
Frequently Asked Questions (FAQ) :
The top companies that hold the market share in visual search technology market are IBM (US), Google (US), Qualcomm (US), Microsoft (US), AWS (US), Trax (Singapore),NEC Corporation (Japan), Catchoom (Spain), Slyce (US), LTU Tech (France), Vispera(Turkey), Blippar(UK), Clarifai(US), Wikitude (Austria), Huawei (China), Honeywell (US), Toshiba (Japan), Oracle (US), Trigo(Israel), INFFRD (US), AIRY3D(Canada), Standard Cognition (US), Unispectral LTD (Israel), Snap2Insight(US), restb.ai(Spain), Vize by Ximilar(Czech Republic), Mirror that Lock (US).
To get latest version of visual search technology market report can be obtained on demand from the website.
The base year for the report is 2022 in visual search technology market.
Analyst Commentary:
Tech giants such as Microsoft, Google, AWS, IBM, and Baidu are investing relentlessly in new technological advancements. In 2016, an investment of around USD 30 Billion was made with more than 90% on the R&D activities and remaining 10% on the merger and acquisition activities. Moreover, seed investment, venture capital investment and private equity financing also grew substantial amounting to a total of over USD 6 Billion.
The development of the deep learning algorithms and machine learning and technological advancement are also major driving factors for the AI in retail market. Machine learning is projected to propel in AI in retail market at more than 40% CAGR. The growth is also driven by higher adoption of technology by the retailers to offer improved customer experience and provide personalized shopping experience to the customer.
Technological advancements around visual search have been making rounds in 2018. It remains a tiny fraction of total search volume, perhaps topping 1 billion monthly searches, compared to hundreds of billions of text searches. Even so, growth has been strong, with Pinterest, for instance, seeing monthly visual search jump from 250 million in February 2017 to 600 million in February 2018. The move towards visual search is not going unnoticed.
Images are returned for more than 15% of search queries on Google. There are over 600 million visual searches on Pinterest each month. Image-based Pinterest Ads have a very conversion rate, almost 8.5% and Pinterest is projected to clear nearly USD 1 billion a year in ad revenue by 2020. The image recognition market is expected to grow to USD xx.xx billion by 2019. By 2021, early adopter brands which redesign their websites to support visual and voice search will increase digital commerce revenue by nearly 30%.
Some retailers are exploiting the integration of chatbots and visual search into the shopping experiences. Retailer Target corp. has been using Pinterest Lens for the past year. WSJ Pinterest is combining visual search with text search, which should increase its reach in the future. Visual platforms like Instagram and Snapchat have a natural tie-in with visual search, if they can make the shopping experience as frictionless as possible. Brands (notably, Mastercard) are dropping text from their images altogether in favor of a design-driven expression of their identity.
Fast-fashion brands are competing against each other for online marketshare, and visual search offers a way to gain ground. Today, Forever 21 begins offering “Discover Your Style” on its web and mobile homepages through a partnership with visual search engine Donde Search. A shopper can click on icons representing features they want in apparel, specifying factors such as silhouette and color, to see corresponding results in Forever 21’s inventory. This is an expansion of a pilot of the technology launched on the retailer’s mobile app in May, which was so successful at increasing conversions and average purchase value that the company decided to “fast track” its large-scale web integration.