Crowd-Sourced Data Collection Market: Global Demand Analysis & Opportunity Outlook 2030” which delivers detailed overview of the global crowd-sourced data collection market in terms of market segmentation by platform type, end user, and by region.

Further, for the in-depth analysis, the report encompasses the industry growth indicators, restraints, supply and demand risk, along with detailed discussion on current and future market trends that are associated with the growth of the market.

Read more @ https://www.researchnester.com/reports/crowd-sourced-data-collection-market/3459

The global crowd-sourced data collection market is expected to garner a large revenue by growing at a notable CAGR throughout the forecast period, i.e., 2022 – 2030, owing to the rising implementation of artificial intelligence into several crowd sourcing platforms, and increasing advancements in crowd-sourced data collection techniques. Furthermore, growing investments by companies for developing innovative machine learning concepts is also estimated to fuel the expansion of market in the coming years.

Growing Implementation of AI into Crowd-Sourcing Platforms to Drive Market Growth

Over the last few years, researchers working on artificial intelligence are involved in implementing different approaches for combining AI and crowds to make effective choices and developing data labeling for machine learning. This is considered to be a crucial factor projected to boost the growth of the market in the upcoming years.

According to recent study by Research Nester, the commercial telematics market size is anticipated to surpass USD XX Bn by 2029 and is projected to expand at CAGR of over 14.3% from 2022 to 2029.

Major players include in the global Crowd-Sourced Data Collection Market:

·        SoundHound Inc.

·        Uber Technologies Inc.

·        Kaggle Inc.

·        Ponoko Inc.

·        Mechanical Turk, Inc.

·        TrendWatching BV

·        Carmera, Inc.

·        Hive Technology, Inc.

·        Lusha Ltd.

·        DIVEVIZ

·        LLC

Get Your Free Sample Copy of this Report @https://www.researchnester.com/sample-request-3459

The market is segmented on the basis of platform type and end user. On the basis of platform type, the managed service platform segment is anticipated to gather the largest share during the forecast period in view of the ability of this platform to upgrade systems as needed, without requirement of outside employees. Additionally, based on end user, the IT & telecommunication segment is expected to grab the largest market share during the forecast period owing to the benefits provided by crowd sourcing for launching software updates to improve performance.

Regionally, the global crowd-sourced data collection market is segmented into five major regions including North America, Europe, Asia Pacific, Latin America and the Middle East & Africa. Asia Pacific is expected to witness the highest growth in the market over the forecast period, which can be attributed to the escalating establishment of startups in the IT sector and rising technological advancements in data crowdsourcing in the region.

The research was global in nature and conducted in North America (U.S., Canada), Europe (U.K., Germany, France, Italy, Spain, Hungary, Belgium, Netherlands & Luxembourg, NORDIC (Finland, Sweden, Norway, Denmark), Poland, Turkey, Russia, Rest of Europe), Latin America (Brazil, Mexico, Argentina, Rest of Latin America), Asia-Pacific (China, India, Japan, South Korea, Indonesia, Singapore, Malaysia, Australia, New Zealand, Rest of Asia-Pacific), Middle East and Africa (Israel, GCC (Saudi Arabia, UAE, Bahrain, Kuwait, Qatar, Oman), North Africa, South Africa, Rest of Middle East and Africa).

In addition, areas like Market size, Y-O-Y growth & Opportunity Analysis, market players competitive study, investment opportunities, demand for future outlook etc. have been covered and displayed in the research report to ensure it dives deep to achieve strategic competitive intelligence in the segment.

However, less awareness about crowd-sourced data collection in lower economic regions is expected to operate as key restraint to the growth of the global crowd-sourced data collection market over the forecast period.

This report also provides the existing competitive scenario of some of the key players of the global crowd-sourced data collection market which includes company profiling of SoundHound Inc., Uber Technologies Inc., Kaggle Inc., Ponoko Inc., Mechanical Turk, Inc., TrendWatching BV, Carmera, Inc., Hive Technology, Inc., Lusha Ltd., DIVEVIZ, LLC and others.

The profiling enfolds key information of the companies which encompasses business overview, products and services, key financials and recent news and developments. On the whole, the report depicts detailed overview of the global crowd-sourced data collection market that will help industry consultants, equipment manufacturers, existing players searching for expansion opportunities, new players searching possibilities and other stakeholders to align their market centric strategies according to the ongoing and expected trends in the future.     

“The Final Report will cover the impact analysis of COVID-19 on this industry.”

Buy a Copy of this Strategic Report to drive your Business Growth  @https://www.researchnester.com/purchage/purchase_product.php?token=3459

Research Nester is a one-stop service provider, leading in strategic market research and consulting with an unbiased and unparalleled approach towards helping global industrial players, conglomerates and executives to make wise decisions for their future investment and expansion by providing them qualitative market insights and strategies while avoiding future uncertainties. We believe in honesty and sheer hard work that we trust is reflected in our work ethics. Our vision is not just limited to gain the trust of our clients but also to be equally respected by our employees and being appreciated by the competitors.

For more information, please contact:

AJ Daniel

Research Nester
Email: info@researchnester.com
Tel: +1-6465869123