The general taxonomy contains a default scope of data related topics, based on the user's browser and mobile app activity through last 30 days. There are classical Demographic, purchase interests, intentions.

How you can use our data?

There are two main areas where you can use our data: • marketers - targeting online campaigns With our high-quality audience data, you can easily reach specific audiences across the world in programmatic campaigns. Show them personalized ads adjusted to their specific profiles. • ad tech companies - enriching 1st party data or using our raw data by your own data science team

In today’s rapidly evolving digital landscape, understanding consumer behavior has never been more crucial for businesses seeking to thrive. Our Consumer Behavior Data database serves as an essential tool, offering a wealth of comprehensive insights into the current trends and preferences of online consumers across the United States. This robust database is meticulously designed to provide a detailed and nuanced view of consumer activities, preferences, and attitudes, making it an invaluable asset for marketers, researchers, and business strategists.

Extensive Coverage of Consumer Data Our database is packed with thousands of indexes that cover a broad spectrum of consumer-related information. This extensive coverage ensures that users can delve deeply into various facets of consumer behavior, gaining a holistic understanding of what drives online purchasing decisions and how consumers interact with products and brands. The database includes:

Product Consumption: Detailed records of what products consumers are buying, how frequently they purchase these items, and the spending patterns associated with these products. This data allows businesses to identify popular products, emerging trends, and seasonal variations in consumer purchasing behavior. Lifestyle Preferences: Insights into the lifestyles of consumers, including their hobbies, interests, and activities. Understanding lifestyle preferences helps businesses tailor their marketing strategies to resonate with the values and passions of their target audiences. For example, a company selling fitness equipment can use this data to identify consumers who prioritize health and wellness.

Product Ownership: Information on the types of products that consumers already own. This data is crucial for businesses looking to introduce complementary products or upgrades. For instance, a tech company could use product ownership data to target consumers who already own older versions of their gadgets, offering them incentives to upgrade to the latest models.

Attitudes and Beliefs: Insights into consumer attitudes, opinions, and beliefs about various products, brands, and market trends. This qualitative data is vital for understanding the emotional and psychological drivers behind consumer behavior. It helps businesses craft compelling narratives and brand messages that align with the values and beliefs of their target audience.

The Gaming Taxonomy contains a broad scope of Gaming related topics, based on the user's browser and mobile app activity through last 30 days. There are classical Demographic, Game Genre, Title and Studio segments. However, we provide also plenty of specific User Types, which contain e.g. Hardcore Gamers, Big Spenders or Parents of Gamers. There are also audiences categorized by specific Hardware Products and Brands, based on the Intent of these devices' purchase. Moreover, we offer segments for Virtual Reality, interest in Gaming Subscriptions, Payments, Micropayments, Devices and Platforms. We also cover the area of E-sports Enthusiasts and Fandoms Members. In spirit of looking beyond simple game genres, we categorize Games according to their Theme (e.g. Historical), which is definitely important aspects of user experience and purchase decisions. Since Mobile Gaming is a very important part of the Gaming Industry, we distinct special Mobile Gaming segments, which are analogous to the ordinary Gaming segments, with additional categorizations of the Telecommunication Network Providers.

Our data base include millions gamers profiles divided into popular categories. You can choose which target groups you want to reach. Contact us to check all the possibilities: team@oan.pl

Gaming data is just a part of all audience data we provide. We deliver millions of users’ profiles gathered globally and grouped into IAB-compliant segments.

How you can use our data?

There are two main areas where you can use our data: • marketers - targeting online campaigns With our high-quality audience data, you can easily reach specific audiences across the world in programmatic campaigns. Show them personalized ads adjusted to their specific profiles. • ad tech companies - enriching 1st party data or using our raw data by your own data science team

We are ready for a cookieless era. We already gather and provide non-cookie ID - for example Universal IDs, CTV IDs or Mobile IDs.

For each hospital web page, we only recorded data requests that initiated data transfers to third-party domains. We then used the webXray database to determine the corporation associated with the third-party domain and the majority owner of the corporation (i.e., the “parent company”) at the time the study occurred (August 2021). For example, the corporation associated with the third-party domain doubleclick.net was determined to be Google, which is majority owned by Alphabet.

Our research does not indicate that the corporations or parent companies listed in our report received data from hospital website browsing; rather, the parent companies listed owned a corporation affiliated with the third-party domains initiating these data requests. We observed only data transfers from the browser to the domain; we did not observe the subsequent use of the data. We do not claim that any third-party domain listed was requesting or receiving this data in a manner that violated applicable laws or regulations governing consumer data privacy.

Below is a table that lists each parent company and the listed domains associated with a corporation owned by such parent company.

According to Cognitive Market Research, The global third-party risk management market size is USD 5.5 billion in 2023 and will expand at a compound annual growth rate (CAGR) of 17.20% from 2023 to 2030.

The demand for third party risk managements is rising due to Resource optimization to protect the interests of millions of digital financial service consumers.
Demand for cloud remains higher in the third party risk management market.
The BFSI category held the highest third party risk management market revenue share in 2023.
North American third party risk management will continue to lead, whereas the European third party risk management market will experience the most substantial growth until 2030.

Rising Instances of Cyber-attacks and Frauds in Digital Financial Services to Provide Viable Market Output

With greater internet penetration, the deployment of smart technology has enhanced the appeal of digital financial services such as mobile banking and digital payments. Because of the growth of digital services, businesses must adapt and incorporate sophisticated technologies into their offerings. However, as the use of digital payment systems in the BFSI sector has grown, so have the risks of cyber-attacks and fraud. BFSI stakeholders are investing heavily to protect their clients from such disasters. The market for third-party risk management will develop as resources are optimized to protect the interests of millions of users of digital financial services.

Growing digitization of Businesses to Propel Market Growth

Industry automation and digitization have exacerbated data privacy and security breaches. With growing digitization, various stakeholders become involved, heightening safety issues. This spike in third-party involvement is propelling the third-party risk management market, raising associated hazards. As industries increasingly rely on external partners and vendors, the need for robust risk management solutions to protect against potential vulnerabilities and ensure the integrity of sensitive data becomes critical in the midst of an evolving landscape of technological advancements and increased interconnectivity.

Market Dynamics of

Third Party Risk Management Market

Key Drivers of

Third Party Risk Management Market

Increasing Regulatory Compliance Demands : Organizations are encountering heightened regulatory pressures to ensure that third parties adhere to legal and compliance standards, particularly in sectors such as finance, healthcare, and technology. Regulations like GDPR, HIPAA, and SOX require comprehensive risk assessments and ongoing monitoring. As the consequences of non-compliance become more severe, businesses are allocating resources to third-party risk management platforms to protect their operations and ensure regulatory compliance.

Escalating Outsourcing and Supply Chain Complexity : As organizations expand their global reach and outsource essential services, the intricacy of managing third-party vendors, suppliers, and partners significantly increases. This escalation results in greater exposure to cybersecurity threats, operational interruptions, and data breaches. The demand for real-time visibility, thorough due diligence, and risk profiling across multi-tier vendor ecosystems is a key factor driving the need for effective TPRM solutions.

Increase in Cybersecurity Threats from Third Parties : Third-party vendors frequently represent the most vulnerable aspect of an organization’s cybersecurity framework. Notable breaches associated with third-party failures have raised awareness regarding vendor-related cyber risks. Companies are now pursuing comprehensive tools to continuously monitor vendor activities, implement security measures, and proactively address vulnerabilities, leading to substantial growth in the market for third-party risk management software and services.

Key Restraints in

Third Party Risk Management Market

High Implementation and Operational Costs : Implementing a successful Third-Party Risk Management (TPRM) program often necessitates a significant initial investment in software, training, and resources. For small to medium-sized enterprises, these expenses can be overwhelming. Beyond the initial setup, continuous risk monitoring and compliance audits further elevate operational costs, which can deter adoption among organizations with limited budgets or those lack...

This data release includes tables and plots of results for pesticide compounds (pesticides and degradates) analyzed in groundwater samples collected by the USGS National Water-Quality Assessment Project during water years 2013-18 and in associated quality-control samples that are used to assess the quality of the reported pesticide results. All samples were analyzed by the USGS National Water Quality Laboratory (NWQL) using laboratory schedule 2437. The table of groundwater data includes pesticide results as reported by the laboratory, along with results that represent the application of censoring levels at the 90-percent upper confidence limit of the 95th percentile of laboratory blank concentrations determined by water year. The other seven tables included in this data release contain pesticide results for the following types of quality-control samples: field blanks, matrix spikes, and replicates collected at field sites; laboratory blanks and reagent spikes prepared by the NWQL; and third-party blind blanks and blind spikes prepared by the USGS Quality Systems Branch. The table of pesticide results for field matrix spikes includes the paired groundwater results and other fields needed to calculate spike recovery as described in the data processing steps of the metadata file. The table of pesticide results for field replicates includes the paired groundwater results and other fields needed to calculate variability in detection and (or) concentration as described in the data processing steps of the metadata file. Results included in this data release for laboratory reagent spikes are for water year 2018 only; results for laboratory reagent spikes analyzed in water years 2013-15 are available in Shoda and others (2017) and in water years 2016-17 are available in Wieben (2019). Useful graphical representations of data in the tables are provided in various plots that compare detections and concentrations for groundwater and blank samples, compare recovery results for the different spike types, and illustrate variability in replicate-sample results across concentration ranges. Shoda, M.E., Nowell, L.H., Bexfield, L.M., Sandstrom, M.W., Stone, W.W., 2017, Recovery data for surface water, groundwater and lab reagent samples analyzed by the USGS National Water Quality Laboratory schedule 2437, water years 2013-15: U.S. Geological Survey data release, https://doi.org/10.5066/F7QZ28G4. Wieben, C.M., 2019, Pesticide recovery data for surface-water and lab reagent samples analyzed by the USGS National Water Quality Laboratory schedule 2437, water years 2016-17: U.S. Geological Survey data release, https://doi.org/10.5066/P93MWMVF. There are 8 tables included in this data release: Table1_GroundwaterData2013_2018.xlsx -- Pesticide results for groundwater samples collected by the National Water-Quality Assessment Project, 2013-18. This table includes pesticide results as reported by the laboratory, along with results that represent the application of censoring levels at the 90-percent upper confidence limit of the 95th percentile of laboratory blank concentrations determined by water year. Results that were rejected for data analysis for reasons described in the metadata document and in the associated Scientific Investigations Report are flagged. Table2_FieldBlankData2013_2018.xlsx -- Pesticide results for field blanks collected at groundwater sites by the National Water-Quality Assessment Project, 2013-18. Results that were rejected for data analysis for reasons described in the metadata document and in the associated Scientific Investigations Report are flagged. Table3_FieldSpikeData2013_2018.xlsx -- Pesticide results for field matrix spikes collected at groundwater sites by the National Water-Quality Assessment Project, 2013-18. Results of paired groundwater samples are included. Results that were rejected for data analysis for reasons described in the metadata document and in the associated Scientific Investigations Report are flagged. Fields needed to calculate spike recovery as described in the data processing steps of the metadata file are included. Table4_FieldRepData2013_2018.xlsx -- Pesticide results for field replicates collected at groundwater sites by the National Water-Quality Assessment Project, 2013-18. Results of paired groundwater samples are included. Results that were rejected for data analysis for reasons described in the metadata document and in the associated Scientific Investigations Report are flagged. Fields needed to calculate variability in detection and (or) concentration as described in the data processing steps of the metadata file are included. Table5_LabBlankData2013_2018.xlsx -- Pesticide results for laboratory blanks prepared by the National Water Quality Laboratory, 2013-18. Results that were rejected for data analysis for reasons described in the metadata document and in the associated Scientific Investigations Report are flagged. Table6_LabReagentSpikeData2018.xlsx -- Pesticide results for laboratory reagent spikes prepared by the National Water Quality Laboratory, 2018. Table7_QSBBlindBlankData_2018.xlsx -- Pesticide results for third-party blind blanks prepared by the Quality Systems Branch, 2018. Table8_QSBBlindSpikeData2013_2018.xlsx -- Pesticide results for third-party blind spikes prepared by the Quality Systems Branch, 2013-18. Results that were rejected for data analysis for reasons described in the metadata document and in the associated Scientific Investigations Report are flagged. There are 5 sets of graphical representations of the data. Detailed descriptions of the plots included in this data release are provided in the associated Scientific Investigations Report: PlotGroup1_TimeSeries.pdf – Plots of reported detections and concentrations in groundwater samples (Table 1), field blanks (Table 2), and laboratory blanks (Table 5) for individual compounds by analysis date, showing the frequency, timing, and magnitude of detections among these sample types. Nondetections are plotted as open circles at the standard laboratory reporting level in effect at the time of analysis (identified on each graph) or, if applicable, at the raised reporting level specified for an individual sample. PlotGroup2_EDFsByWY.pdf – Empirical distribution functions illustrating upper percentiles of concentrations for groundwater samples (Table 1) relative to field blanks (Table 2) and laboratory blanks (Table 5) for selected pesticides and water years. Plots are provided for compounds and water years with at least one groundwater detection and a quantifiable (detected) 99th percentile of concentration for laboratory blanks. PlotGroup3_SpikeTimeSeries.pdf – Plots of recoveries for laboratory reagent spikes (Table 6), field matrix spikes (Table 3), and third-party blind spikes (Table 8) for individual pesticides by analysis date, illustrating the range of typical recoveries. Lowess (locally weighted scatterplot smoothing) curves are included to illustrate general changes in recovery through time. Results for laboratory reagent spikes analyzed in water years 2013-15 are available in Shoda and others (2017) and in water years 2016-17 are available in Wieben (2019). PlotGroup4_LabFieldSpikes.pdf – Box plots comparing recoveries for laboratory reagent spikes (Table 6) and field matrix spikes (Table 3). Results for laboratory reagent spikes analyzed in water years 2013-15 are available in Shoda and others (2017) and in water years 2016-17 are available in Wieben (2019). PlotGroup5_FieldRepVar.pdf – Plots of standard deviation and relative standard deviation against mean concentration of field replicate samples (Table 4) for selected pesticides, including assigned boundaries between the lower concentration range where standard deviation generally is more uniform and the upper concentration range where relative standard deviation generally is more uniform. Plots are provided for pesticides that had 10 or more replicate pairs with detections in both samples of the pair.

From October 2017 through September 2022, the National Water Quality Network (NWQN) monitored 110 surface-water river and stream sites and more than 1,800 groundwater wells for a large number of water-quality analytes, for which associated quality-control data and corresponding statistical summaries are included in this data release. The quality-control data—for samples that were collected in the field (at all 110 surface-water sites, 350 groundwater wells, and 16 quality-control-only sites), prepared in the laboratory, or prepared by a third party—can be used to assess the quality of environmental data collected by the NWQN through the estimation of bias and variability in reported results. The general analyte groups that were monitored at NWQN surface-water and (or) groundwater sites and have associated quality-control data in this data release include major ions, nutrients, trace elements, pesticides, volatile organic compounds, hormones, pharmaceuticals, radionuclides, microbial indicators, sediment, and environmental tracers. For each analyte group, the data tables contain results for one or more of the following types of quality-control samples, where relevant: blanks, matrix spikes, and replicates collected at field sites; laboratory blanks, reagent spikes, and matrix spikes prepared by the USGS National Water Quality Laboratory (NWQL) (quality-control samples prepared by other analyzing laboratories are not included in the current data release); and third-party blanks, spikes, and reference samples prepared by the USGS Quality Systems Branch (QSB). For each relevant analyte, tables of summary statistics characterize the frequency and concentrations of blank detections, the typical magnitude of and variability in spike and reference-sample recoveries, and the typical variability between replicate concentrations. Tables included in this data release: Table1_SiteList.txt: Information about National Water Quality Network sites that have associated quality-control data. Table2_AnalyteList.txt: Information about National Water Quality Network analytes that have associated quality-control data, including available aquatic-life and (or) human-health benchmarks and selected information regarding analytical methods. Table3_BlankData.txt: For all relevant analytes, results for blanks collected at field sites, prepared in the laboratory, or prepared by a third party. Table4_SpikeData.txt: For all relevant analytes, results for matrix spikes prepared in the field, matrix spikes prepared in the laboratory, reagent spikes prepared in the laboratory, or reagent spikes prepared by a third party. For matrix spikes, results of paired environmental samples are included. Table5_ReplicateData.txt: For all relevant analytes, results for field replicates and paired environmental samples. Table 6_ReferenceData.txt: For all relevant analytes, results for third-party reference samples. Table7_BlankStats.txt: For all relevant analytes, summary statistics for each type of available blank sample. Table8_SpikeStats.txt: For all relevant analytes, summary statistics for each type of available spike sample. Table9_ReplicateStats.txt: For all relevant analytes, summary statistics for field replicates. Table10_ReferenceStats.txt: For all relevant analytes, summary statistics for reference samples.

In 2024, financial media networks (FMNs) accounted for 0.1 percent of digital advertising spending in the United States. The share is expected to quadruple by 2026. FMNs are defined as financial institutions with their own ad networks using their own first-party data to target their customers with third-party ads. Examples include Chase Bank, PayPal, or Klarna.

In 2024, advertising spending on financial media networks (FMNs) was estimated at *** million U.S. dollars in the United States. The value is expected to double in 2025, and then to double again in 2026. FMNs are defined as financial institutions with their own ad networks using their own first-party data to target their customers with third-party ads. Examples include Chase Bank, PayPal, or Klarna.

Snapshot img

Third-Party Banking Software Market Size 2025-2029

The third-party banking software market size is forecast to increase by USD 10.56 billion at a CAGR of 6.6% between 2024 and 2029.

The market is witnessing significant growth, driven by the increasing adoption of digital payment solutions and the incorporation of advanced analytics capabilities. Digital transformation in the banking sector is leading to a surge in demand for third-party banking software that enables seamless integration with various digital payment platforms and provides real-time transaction processing and analysis. Furthermore, the integration of analytics into third-party banking software is enabling financial institutions to gain valuable insights into customer behavior and preferences, thereby enhancing customer experience and loyalty. However, the market also faces challenges related to data privacy and security.
With the increasing use of digital channels for banking transactions, ensuring the security and privacy of customer data is paramount. Breaches and cyber-attacks pose a significant threat to financial institutions and can result in reputational damage and financial losses. Therefore, third-party banking software providers must prioritize data security and privacy to gain the trust of financial institutions and their customers. Additionally, regulatory compliance is another challenge, with financial institutions requiring third-party software providers to adhere to stringent regulatory frameworks to ensure data security and privacy. Companies seeking to capitalize on market opportunities and navigate challenges effectively must focus on providing robust data security and privacy features and ensuring regulatory compliance.

What will be the Size of the Third-Party Banking Software Market during the forecast period?

Request Free Sample

The market continues to evolve, driven by the ever-changing needs of financial institutions and their customers. User interfaces are becoming more intuitive, enabling seamless customer acquisition and retention. Open banking and financial wellness initiatives are integrating personalized services, data analytics, and payment processing to enhance the digital banking experience. Businesses are leveraging real-time data, API integration, and machine learning to optimize financial planning and investment management. Workflow automation and artificial intelligence are streamlining customer relationship management and wealth management processes. Digital transformation is also revolutionizing enterprise resource planning and financial education. Moreover, the integration of loan origination, data visualization, and agile development is enabling financial institutions to provide more efficient and effective services.
Fraud detection and financial inclusion are also becoming essential components of the market, ensuring security and accessibility for all customers. The ongoing digital banking revolution is transforming the financial landscape, with mobile banking and cloud computing playing a significant role. The market's continuous dynamism is reflected in its ability to adapt to emerging trends, such as financial literacy and account aggregation, and incorporate them into its offerings. The future of the market is bright, with endless possibilities for innovation and growth.

How is this Third-Party Banking Software Industry segmented?

The third-party banking software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Core banking software
  Omnichannel banking software
  Business intelligence software
  Wealth management software


Deployment

  On-premises
  Cloud


Application

  Risk Management
  Information Security
  Business Intelligence


Service Model

  Managed Services
  Professional Services
  Implementation Services


Geography

  North America

    US
    Canada


  South America

    Brazil
    Argentina


  Middle East and Africa

    UAE


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Type Insights

The core banking software segment is estimated to witness significant growth during the forecast period.

The market encompasses various solutions that empower financial institutions to enhance their operations and deliver superior customer experiences. Core banking software, a significant segment, focuses on essential banking processes such as loan, credit, deposit, and funds transfer. Multi-channel access via ATMs, Internet banking, and phone banking are also facilitated through this software. The retail banking sector's expansion, driven by government initiatives encouraging account opening, is fueling the demand f

Amazon not only boasts a hugely successful online retail platform but also a thriving digital marketplace which is seamlessly integrated with the main retail shopping experience. That being said, in the first quarter 2025, ** percent of paid units were sold by third-party sellers. 1P and 3P Amazon sellers There are many ways of selling on Amazon. Firstly there are first-party (1P) vendor sales, where vendors send their inventory to Amazon, who in turn control the pricing and include “ships from and sold by Amazon.com” on product listings. The benefits of 1P sales on Amazon are wholesale purchases from Amazon, priority selling and brand trust through Amazon’s credibility as a seller. Amazon also permits third-party (3P) sales on its marketplace. Both individuals and professional sellers can sell on Amazon Marketplace. When it comes to order fulfillment, possible options are Fulfillment by Amazon (FBA) and Fulfillment by Merchant (FBM). Items are displayed as “sold by MERCHANT and Fulfilled by Amazon / Fulfilled by MERCHANT”. 3P sales are a popular strategy for sellers to make up for certain 1P sales disadvantages, namely improved margins through better pricing control, more favorable payment terms and less reliance on the relationship with Amazon. Amazon seller revenues This magic formula has ultimately cashed in for Amazon, which has seen its net revenues multiply in recent years. In 2023, the e-commerce giant generated approximately *** billion dollars in third-party seller services, an increase of about ** billion dollars from the previous year. While these figures are the product of orders throughout the year, a significant chunk is attributable to special offer and discount days. According to a survey, Black Friday is the shopping event driving the largest sales increase for Amazon sellers, followed by two of the company's own events, Prime Day and Amazon Summer Sale. In the context of the coronavirus pandemic, Amazon Prime Day played a particularly decisive role for small and medium-sized businesses around the world, many of which had to turn to online sales overnight in order to survive.

San Francisco Campaign and Governmental Conduct Code ("S.F. C&GC Code") sections 1.143(c), 1.152(a)(3), 1.161(b), 1.161.5, and 1.160.5 require persons who make any independent expenditure, electioneering communication, or member communication that clearly identifies a candidate for City elective office or who authorizes, administers or pays for a persuasion poll to file disclosure statements with the Ethics Commission. For detailed instructions, please see Third Party Disclosure Form Regarding Candidates.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

Snapshot img

US Third-Party Logistics (3Pl) Market Size 2025-2029

The us third-party logistics (3pl) market size is forecast to increase by USD 132.3 billion at a CAGR of 8.2% between 2024 and 2029.

The Third-Party Logistics (3PL) market in the US is experiencing significant growth, driven by the increasing trend of cross-border trade. As globalization continues to expand, businesses are increasingly turning to 3PL providers to manage their international logistics needs. Another key trend shaping the market is the emergence of advanced technologies such as blockchain and Radio Frequency Identification (RFID) in logistics. These technologies offer enhanced supply chain visibility, security, and efficiency, making them valuable tools for 3PLs to offer their clients. However, the market is not without challenges. The ongoing trade war between major economies poses a significant risk to the market, with potential tariffs and trade restrictions impacting logistics costs and operations. Additionally, the increasing complexity of global supply chains and customer expectations for faster delivery times require 3PLs to continually innovate and adapt to remain competitive. Companies seeking to capitalize on market opportunities and navigate challenges effectively must focus on leveraging technology, building resilient supply chains, and providing exceptional customer service.

What will be the size of the US Third-Party Logistics (3Pl) Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

The 3PL market in the US is witnessing significant advancements, driven by the integration of digital twin technology and blockchain in logistics operations. Order accuracy and customer satisfaction are prioritized through value-added services, network optimization, and demand forecasting. Green logistics and data-driven decisions are essential for competitive advantage, with automation technologies streamlining contract logistics and delivery speed. Damage prevention and inventory control are enhanced through supply chain transparency and warehousing optimization. Capacity planning and transportation mode selection are crucial for cost-effective solutions, while emerging technologies such as sustainability initiatives and supply chain visibility continue to shape the industry. Network planning and competitive advantage are intertwined, as companies leverage digital transformation to mitigate supply chain disruptions and offer dedicated logistics services.

How is this market segmented?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. End-userRetailManufacturingAutomotiveFood and beveragesOthersServiceTransportationWarehousing and distributionOthersGeographyNorth AmericaUS

By End-user Insights

The retail segment is estimated to witness significant growth during the forecast period.

In the dynamic retail industry, both organized retail and consumer goods sectors experience significant growth. Fast-moving consumer goods (FMCGs) and slow-moving consumer goods (SMCGs) are distinct categories. FMCGs, with a shelf life under a year, consist of household and cleaning products, personal care items, tobacco, apparel and footwear, and pet food/pet care. These goods are bought frequently due to recurring expenditures. SMCGs, characterized by a longer shelf life, include home improvement products, furniture, and household appliances. To stay competitive, industry players invest substantially in product innovation. Data analytics and predictive analytics are crucial tools for understanding consumer behavior and market trends. Last-mile delivery solutions enhance customer satisfaction, while pick-and-pack services ensure efficient order fulfillment. Freight forwarding streamlines transportation management, and robotics and automation improve efficiency. Cloud-based logistics software, business intelligence, and real-time visibility enable cost optimization and supply chain resilience. Reverse logistics, compliance, and regulations are essential for managing returns and maintaining inventory. E-commerce integration, packaging, and labeling, and delivery network design are vital for seamless omni-channel fulfillment. Risk management, route optimization, security and safety, and mobile technology are integral components of modern logistics. Artificial intelligence and machine learning enable advanced sorting, sequencing, and load planning. Fleet management, big data, and customer service are critical for maintaining a competitive edge. In this evolving landscape, players must adapt to meet the changing demands of consumers and the market.

The general taxonomy contains a default scope of data related topics, based on the user's browser and mobile app activity through last 30 days. There are classical Demographic, purchase interests, intentions.

How you can use our data?

There are two main areas where you can use our data: • marketers - targeting online campaigns With our high-quality audience data, you can easily reach specific audiences across the world in programmatic campaigns. Show them personalized ads adjusted to their specific profiles. • ad tech companies - enriching 1st party data or using our raw data by your own data science team

The awareness among worldwide consumers about companies selling their personal data to third parties has grown in recent years. As of July 2022, three in four consumers in selected countries worldwide said they knew that companies sell personal information. In comparison, in 2020, this share was a little over 60 percent.

Snapshot img

Insurance Third Party Administrators Market Size 2025-2029

The insurance third party administrators market size is forecast to increase by USD 136.5 billion at a CAGR of 7.3% between 2024 and 2029.

The Insurance Third Party Administrators (TPA) market experiences robust growth, driven by the increasing demand for specialized services in the insurance industry. As businesses seek to streamline operations and improve efficiency, the outsourcing of administrative functions to TPAs becomes an attractive option. Technological advancements further fuel market expansion, enabling TPAs to offer advanced services such as digital claims processing and data analytics. However, market growth is not without challenges. Regulatory hurdles impact adoption, with stringent regulations governing data privacy and security, requiring TPAs to invest significantly in compliance measures.
Supply chain inconsistencies also temper growth potential, as TPAs rely on various stakeholders, including insurance companies, healthcare providers, and claims adjusters, to deliver services effectively. Despite these challenges, the market presents significant opportunities for companies that can navigate these complexities and provide innovative solutions to meet the evolving needs of the insurance industry.

What will be the Size of the Insurance Third Party Administrators Market during the forecast period?

Request Free Sample

Understanding the Dynamics and Trends in the US Third-Party Administration Market The third-party administration (TPA) market in the US is experiencing significant growth and innovation, driven by the increasing demand for efficient and effective management of employee benefits and insurance programs. TPA services encompass various functions, including utilization management, performance measurement, change management, and fraud detection in life insurance, group health plans, and government programs. Customer experience is a top priority, with machine learning and predictive modeling enabling personalized services and real-time analytics. Data governance and interoperability are essential for ensuring data security and accuracy in data warehousing and API integration.
Ethical practices and industry consortiums promote social responsibility and transparency. TPA companies invest in innovation hubs, agile development, and mobile applications to streamline policy administration and claims processing. Compliance consulting and risk modeling help organizations navigate complex regulatory requirements. Wellness programs and provider contracting are crucial components of managed care, while network management and medical billing optimize costs and improve financial reporting. Security audits, disaster recovery, business continuity, and project management ensure business resilience, while data visualization and business intelligence tools enhance customer satisfaction. Long-term care and compliance consulting further expand the scope of TPA services.

How is this Insurance Third Party Administrators Industry segmented?

The insurance third party administrators industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Service Type

  Health plan administrators
  Workers compensation TPA
  Third party claims administration


Type

  Large enterprises
  Small and medium enterprise


Service

  Claims management
  Policy management
  Commission management


Application

  Healthcare
  Construction
  Real estate
  Hospitality
  Others


Geography

  North America

    US
    Canada
    Mexico


  Europe

    France
    Germany
    Italy
    Spain
    The Netherlands
    UK


  Middle East and Africa

    UAE


  APAC

    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Service Type Insights

The health plan administrators segment is estimated to witness significant growth during the forecast period.

Health plan administrators, including those serving Large Enterprise Insurance and Health Insurance, play a pivotal role in the healthcare ecosystem by managing various administrative tasks related to health insurance plans on behalf of employers, insurance companies, or self-insured organizations. Their primary responsibilities include claim processing, enrollment and eligibility management, and premium billing and management. The integration of technology is significantly impacting the operations of health plan administrators. For instance, Cloud Computing facilitates data accessibility and storage, enabling real-time data processing and analysis. Data Security ensures the confidentiality and integrity of sensitive health information. Digital Transformation, including Workflow Automation and Process Effic

Report Overview

The global Privacy Management Software market has become a vital sector in the technology landscape. With increasingly sophisticated cyber threats, organizations are investing heavily in advanced solutions. In 2023, the market value stood at USD 3.0 billion, and it is projected to soar to USD 83.7 billion by 2033, growing at an impressive CAGR of 39.50% between 2024 and 2033. This surge is fueled by the rapid adoption of digital transformation strategies, growing reliance on cloud infrastructure, and the ever-increasing risk of cyberattacks.

AI and ML are playing a pivotal role in automating privacy management processes. These technologies enable real-time data monitoring, identify compliance risks, and offer predictive insights to mitigate potential breaches. For instance, AI-based solutions can now detect anomalies in large data sets, improving compliance efficiency. By 2024, over 40% of privacy management tools will incorporate AI-driven analytics.

With regulations such as GDPR, CCPA, and China's Personal Information Protection Law (PIPL), companies are prioritizing consumer rights like data portability, the right to be forgotten, and opt-out preferences. Privacy management solutions are increasingly equipped with features to address these rights efficiently. For example, the demand for data subject access request (DSAR) management tools has surged by nearly 35% annually.

Privacy management software is being integrated with broader cybersecurity platforms to create unified solutions. This integration helps companies streamline compliance while protecting data from unauthorized access. Gartner predicts that by 2025, 60% of the privacy management software market will be bundled with cybersecurity suites to address overlapping challenges.

Industries like healthcare, finance, and e-commerce are seeing tailored privacy management solutions that cater to specific compliance needs. For example, healthcare providers are adopting tools to meet HIPAA compliance, while financial institutions are leveraging software that ensures data security in line with GDPR and PSD2 regulations.

Organizations are increasingly concerned about the data shared with third-party vendors. Privacy management tools now include third-party risk assessment capabilities to evaluate vendor compliance with privacy standards. According to a recent survey, 55% of organizations implemented third-party risk management in 2023, a figure expected to grow significantly in 2024.

As businesses migrate to cloud environments, cloud-based privacy management software is becoming a preferred choice due to its scalability and ease of integration. Currently, 67% of businesses prefer cloud-based solutions, a number anticipated to grow as remote work and digital transformation expand.

Governments worldwide are enforcing data localization rules, requiring businesses to store user data within specific geographic boundaries. Privacy management tools now offer features to ensure compliance with such laws, enabling organizations to align with region-specific data storage requirements.

To meet growing consumer expectations, organizations are deploying privacy dashboards that allow users to view, manage, and delete their data. These dashboards are becoming a standard feature, with 30% of companies globally adopting them in 2023 to improve transparency.

Organizatio...

The 1860 election cemented the Republican Party's position as one of the two major parties in U.S. politics, along with the already-established Democratic Party. Since this time, all U.S. presidents have been affiliated with these two parties, and their candidates have generally performed the best in each presidential election. In spite of this two-party dominance, there have always been third-party or independent candidates running on the ballot, either on a nationwide, regional or state level. No third-party candidate has ever won a U.S. election, although there have been several occasions where they have carried states or split the vote with major party candidates. Today, the largest third-party in U.S. politics is the Libertarian Party, who are considered to be socially liberal, but economically conservative; in the 2016 election, their nominee, Gary Johnson, secured just over three percent of the popular vote, while their latest candidate, Jo Jorgenson, received just over one percent of the vote in the 2020 election.

Theodore Roosevelt The most successful third-party nominee was Theodore Roosevelt in the 1912 election, who was the only third-party candidate to come second in a U.S. election. The former president had become disillusioned with his successor's growing conservatism, and challenged the incumbent President Taft for the Republican nomination in 1912. Roosevelt proved to be the most popular candidate in the primaries, however Taft had already secured enough Republican delegates in the south to seal the nomination. Roosevelt then used this split in the Republican Party to form his own, Progressive Party, and challenged both major party candidates for the presidency (even taking a bullet in the process). In the end, Roosevelt carried six states, and won over 27 percent of the popular vote, while Taft carried just two states with 23 percent of the vote; this split in the Republican Party allowed the Democratic nominee, Woodrow Wilson, to win 82 percent of the electoral votes despite only winning 42 percent of the popular vote.

Other notable performances The last third-party candidate to win electoral votes was George Wallace* in the 1968 election. The Democratic Party had been the most popular party in the south since before the Civil War, however their increasingly progressive policies in the civil rights era alienated many of their southern voters. Wallace ran on a white supremacist and pro-segregationist platform and won the popular vote in five states. This was a similar story to that of Storm Thurmond, twenty years earlier.

In the 1992 election, Independent candidate Ross Perot received almost one fifth of the popular vote. Although he did not win any electoral votes, Perot split the vote so much that he prevented either Clinton or Bush Sr. from winning a majority in any state except Arkansas (Clinton's home state). Perot ran again in 1996, but with less than half the share of votes he received four years previously; subsequent studies and polls have shown that Perot took an equal number of votes from both of the major party candidates in each election.

This data release includes tables and time-series plots of results for volatile organic compounds (VOCs) analyzed in samples of groundwater used for public supply that were collected by the USGS National Water-Quality Assessment (NAWQA) Project and the California State Water Resources Control Board’s Groundwater Ambient Monitoring and Assessment Program Priority Basin Project (GAMA-PBP) during 2013-19; results for associated quality-control samples also are included. All samples were analyzed by the USGS National Water Quality Laboratory (NWQL) using laboratory schedules 4436 and 4437. The table of groundwater data includes VOC results as reported by the laboratory, along with results that represent the application of censoring approaches described in the metadata file and associated journal article. The other seven tables included in this data release contain VOC results for the following types of quality-control samples: field blanks and replicates collected at field sites; laboratory blanks, reagent spikes, and matrix spikes prepared by the NWQL; and third-party blind blanks and blind spikes prepared by the USGS Quality Systems Branch. The tables of VOC results for matrix spikes and field replicates include the paired groundwater results. For convenience, plots are provided of reported VOC detections and concentrations in groundwater samples, field blanks, and laboratory blanks for individual compounds by analysis date. Plots also are provided of recoveries for laboratory reagent spikes, laboratory matrix spikes, and third-party blind spikes for individual VOCs by analysis date. This data release includes 8 tables and 2 series of laboratory results plots: Table1_GroundwaterData2013_2019.csv: VOC results for samples collected by NAWQA and GAMA-PBP of groundwater used for public supply, 2013-19. This table includes VOC results as reported by the laboratory, along with results that represent the application of censoring approaches described in the associated journal article. Results that were rejected or censored for data analysis for reasons described in the metadata document and in the associated journal article are identified using attribute values described in the process steps for this table. Table2_FieldBlankData2013_2019.csv: VOC results for field blanks collected at applicable groundwater sites by NAWQA and GAMA-PBP, 2013-19. Results that were rejected for data analysis for reasons described in the metadata document and in the associated journal article are identified using attribute values described in the process steps for this table. Table3_MatrixSpikeData2013_2019.csv: VOC results for samples collected for laboratory matrix spikes at applicable groundwater sites by NAWQA and GAMA-PBP, 2013-19. Results of paired groundwater samples are included. Results that were rejected for data analysis for reasons described in the metadata document and in the associated journal article are identified using attribute values described in the process steps for this table. Fields needed to calculate spike recovery as described in the data processing steps of the metadata file are included. Table4_FieldRepData2013_2019.csv: VOC results for field replicates collected at groundwater sites by NAWQA and GAMA-PBP, 2013-19. Results of paired groundwater samples are included. Fields needed to calculate variability in detection and (or) concentration as described in the data processing steps of the metadata file are included. Table5_LabBlankData2013_2019.csv: VOC results for laboratory blanks prepared by the National Water Quality Laboratory, 2013-19. Table6_LabReagentSpikeData2013_2019.csv: VOC results for laboratory reagent spikes prepared by the National Water Quality Laboratory, 2013-19. Table7_QSBBlindBlankData2016_2019.csv: VOC results for third-party blind blanks prepared by the Quality Systems Branch, 2016-19. Table8_QSBBlindSpikeData2013_2019.csv: VOC results for third-party blind spikes prepared by the Quality Systems Branch, 2013-19. Results that were rejected for data analysis for reasons described in the metadata document are flagged. PlotGroup1_GW_Blank_TimeSeries.pdf: Plots of laboratory-reported (uncensored) detections and concentrations in groundwater samples (Table 1), field blanks (Table 2), laboratory blanks (Table 5), and third-party blind blanks (Table 7) for individual VOCs by analysis date, showing the frequency, timing, and magnitude of detections among these sample types. Nondetections are plotted as open circles at the standard laboratory reporting limit in effect at the time of analysis (identified on each graph) or, if applicable, at the raised reporting limit specified for an individual sample. PlotGroup2_SpikeTimeSeries.pdf: Plots of recoveries for laboratory reagent spikes (Table 6), laboratory matrix spikes (Table 3), and third-party blind spikes (Table 8) for individual VOCs by analysis date, illustrating the range of typical recoveries. Kernel regression smoothing curves are included to illustrate general changes in recovery through time. False-negative results from third-party blind samples also are shown.

Third-Party Logistics (3PL) Market Outlook

According to our latest research, the global Third-Party Logistics (3PL) market size reached USD 1,180.5 billion in 2024, reflecting robust demand across various industries. The market is set to grow at a CAGR of 7.3% from 2025 to 2033, with the total market value forecasted to reach USD 2,218.7 billion by 2033. This growth is primarily driven by the escalating complexity of supply chains, the rapid expansion of e-commerce, and the increasing adoption of advanced logistics technologies. As per our latest research, the 3PL market is witnessing a transformative period, with digitalization and sustainability initiatives shaping the competitive landscape.

The primary growth factor for the Third-Party Logistics (3PL) market is the exponential rise in global trade and cross-border e-commerce activities. As businesses expand their reach to international markets, they are increasingly relying on 3PL providers to navigate the complexities of customs regulations, tariffs, and last-mile delivery challenges. The surge in online shopping, particularly post-pandemic, has created an unprecedented demand for agile and scalable logistics solutions. 3PL companies are responding by investing in automation, real-time tracking, and integrated IT platforms, enabling their clients to offer faster and more reliable deliveries. This, in turn, is fostering long-term partnerships between shippers and logistics providers, further propelling market expansion.

Another significant driver is the growing trend toward supply chain outsourcing among manufacturers and retailers. Companies are seeking to streamline operations and reduce costs by entrusting non-core activities such as warehousing, transportation, and inventory management to specialized 3PL firms. This strategic shift allows organizations to focus on their core competencies while leveraging the expertise, infrastructure, and economies of scale offered by logistics partners. In addition, the adoption of value-added services such as packaging, kitting, and reverse logistics is enhancing the value proposition of 3PL providers. As supply chains become more dynamic and customer expectations rise, the ability of 3PLs to offer customized and end-to-end solutions is becoming a key differentiator in the market.

Technological advancements are playing a pivotal role in shaping the future of the Third-Party Logistics (3PL) market. The integration of artificial intelligence, machine learning, and data analytics is enabling logistics providers to optimize routing, predict demand, and enhance visibility across the supply chain. The deployment of Internet of Things (IoT) devices and RFID technology is improving asset tracking and inventory accuracy, while blockchain is being explored for its potential to increase transparency and security in logistics operations. These innovations are not only driving operational efficiencies but also enabling 3PLs to deliver superior customer experiences, thereby attracting new clients and expanding their service portfolios.

From a regional perspective, the Asia Pacific region continues to dominate the Third-Party Logistics (3PL) market, driven by the rapid industrialization, booming e-commerce sector, and significant investments in logistics infrastructure. China, India, and Southeast Asian countries are at the forefront of this growth, benefiting from favorable government policies and rising consumer demand. North America and Europe also represent substantial market shares, fueled by technological innovation and the presence of established 3PL providers. Meanwhile, emerging markets in Latin America and the Middle East & Africa are experiencing steady growth, supported by increasing trade activities and the modernization of supply chains. The global outlook remains highly positive, with all regions contributing to the overall expansion of the 3PL industry.

Service Type Analysis

The Service Type segment in the Third-Party Logistics (3PL) market encompasses a diverse r