In a study on the usage of third-party marketing data in the United States it was found that in 2020, industry professionals in the country spent *** billion U.S. dollars on transactional audience data. Demographic data cost marketers around 4.4. billion dollars that year.
In 2021, expenditure on third party audience data in the United States amounted to ** billion U.S. dollars, out of which **** billion was spent on data itself and *** billion on audience data activation solutions.
Discover the perfect third party audience data with OAN. Our audience databases provide access to millions of users’ profiles, organized to maximize your reach with the world's best audience data.
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
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At Factori, we gather various data sets from leading publishers, data platforms, online services, and data aggregators globally, linked to consumers, places, and businesses. We combine this data with public and private sources to derive interests, intent, and behavioral attributes. Our proprietary algorithms clean, enrich, unify, and aggregate these data sets for use in our products. We categorize our audience data into consumable categories such as interest, demographics, behavior, geography, etc.
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 of profiles divided into popular categories. You can choose which target groups you want to reach. Segments based on users' interests, purchase intentions or demography. Contact us to check all the possibilities: team@oan.pl
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.
Low-latency, mobile audience data with 30+ enriched fields. Enhance your first-party data, audience targeting, personalization, and market insights at scale.
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
OAN helps you reach gamers across the world. Our gaming audience data offers categorized audience segments into gamer behavior and gaming trends. This powerful dataset provides a deep understanding of the gaming industry by delivering unique categories such as: demography, interest, hardware, spenders, genres and titles, e-sports fans and players.
By understanding this data, businesses can make data-driven decisions to optimize their marketing strategies, game development, and monetization efforts.
The Gaming Taxonomy contains a broad scope of Gaming related topics, based on the user's browser and mobile app activity through the last 30 days. There are also gamer audiences categorized by specific Hardware Products and Brands, based on the Intent of these devices' purchase. Furthermore, 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 Themes (e.g. Historical), which are 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.
Gaming audience 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. You can choose which target groups you want to reach. Contact us to check all the possibilities: team@oan.pl
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.
Redmob delivers low-latency, privacy-compliant global mobile digital audience data, helping you reach the right people when and where it matters.
Built for adtech platforms, brands, agencies, and data buyers, Redmob gives you real-time access to rich mobile user profile data, enriched with 30+ custom attributes. From smarter segmentation to market insights, it supports strategies that drive real results, whether you're building audiences, optimizing campaigns, or analyzing consumer behavior.
Use Cases
Redmob equips you with the insights to boost performance, sharpen targeting, and understand your market at scale and in real time.
Key Benefits
DRAKO is a Mobile Location Audience Targeting provider with a programmatic trading desk specialising in geolocation analytics and programmatic advertising. Through our customised approach, we offer business and consumer insights as well as addressable audiences for advertising.
Mobile Location Data can be meaningfully transformed into Audience Targeting when used in conjunction with other dataset. Our expansive POI Data allows us to segment users by visitation to major brands and retailers as well as categorizes them into syndicated segments. Beyond POI visits, our proprietary Home Location Model determines residents of geographic areas such as Designated Market Areas, Counties, or States. Relatedly, our Home Location Model also fuels our Geodemographic Census Data segments as we are able to determine residents of the smallest census units. Additionally, we also have audiences of: ticketed event and venue visitors; survey data; and retail data.
All of our Audience Targeting is 100% deterministic in that it only includes high-quality, real visits to locations as defined by a POIs satellite imagery buildings contour. We never use a radius when building an audience unless requested. We have a horizontal accuracy of 5m.
Additionally, we can always cross reference your audience targeting with our syndicated segments:
Overview of our Syndicated Audience Data Segments: - Brand/POI segments (specific named stores and locations) - Categories (behavioural segments - revealed habits) - Census demographic segments (HH income, race, religion, age, family structure, language, etc.,) - Events segments (ticketed live events, conferences, and seminars) - Resident segments (State/province, CMAs, DMAs, city, county, sub-county) - Political segments (Canadian Federal and Provincial, US Congressional Upper and Lower House, US States, City elections, etc.,) - Survey Data (Psychosocial/Demographic survey data) - Retail Data (Receipt/transaction data)
All of our syndicated segments are customizable. That means you can limit them to people within a certain geography, remove employees, include only the most frequent visitors, define your own custom lookback, or extend our audiences using our Home, Work, and Social Extensions.
In addition to our syndicated segments, we’re also able to run custom queries return to you all the Mobile Ad IDs (MAIDs) seen at in a specific location (address; latitude and longitude; or WKT84 Polygon) or in your defined geographic area of interest (political districts, DMAs, Zip Codes, etc.,)
Beyond just returning all the MAIDs seen within a geofence, we are also able to offer additional customizable advantages: - Average precision between 5 and 15 meters - CRM list activation + extension - Extend beyond Mobile Location Data (MAIDs) with our device graph - Filter by frequency of visitations - Home and Work targeting (retrieve only employees or residents of an address) - Home extensions (devices that reside in the same dwelling from your seed geofence) - Rooftop level address geofencing precision (no radius used EVER unless user specified) - Social extensions (devices in the same social circle as users in your seed geofence) - Turn analytics into addressable audiences - Work extensions (coworkers of users in your seed geofence)
Data Compliance: All of our Audience Targeting Data is fully CCPA compliant and 100% sourced from SDKs (Software Development Kits), the most reliable and consistent mobile data stream with end user consent available with only a 4-5 day delay. This means that our location and device ID data comes from partnerships with over 1,500+ mobile apps. This data comes with an associated location which is how we are able to segment using geofences.
Data Quality: In addition to partnering with trusted SDKs, DRAKO has additional screening methods to ensure that our mobile location data is consistent and reliable. This includes data harmonization and quality scoring from all of our partners in order to disregard MAIDs with a low quality score.
During a 2023 survey carried out among media strategists, planners and buyers from North America who worked on programmatic campaigns, respondents were asked to rank the importance of a range of factors influencing the choice of a third-party data provider. Audience size ranked first, having received 4.45 point on a scale from 1 to 5.
During a late 2022 survey carried out among marketers from the United Kingdom (UK), **** percent of respondents named reaching audiences at scale as one of the main digital advertising strategy challenges as a result of third-party cookie deprecation. Frequency capping ranked second, mentioned by ** percent of responding marketers.
Redmob delivers low-latency, privacy-compliant mobile digital audience data for clients who are interested to grow their presence in Asia.
Built for adtech platforms, brands, agencies, and data buyers, Redmob gives you real-time access to rich mobile user profile data, enriched with 30+ custom attributes. From smarter segmentation to market insights, it supports strategies that drive real results, whether you're building audiences, optimizing campaigns, or analyzing consumer behavior.
Use Cases
Redmob equips you with the insights to boost performance, sharpen targeting, and understand your market at scale and in real time.
Key Benefits
The charts shows the share of marketers worldwide who believed their organization targeted audiences effectively with use of data as of ********, by business type. According to the study from Quantcast, ** percent of global direct brand marketers believed their company was effectively using first-party data to target audiences, while ** percent said the same about their use of third-party data.
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The global third party insurance market size was valued at approximately USD 250 billion in 2023 and is projected to reach USD 450 billion by 2032, growing at a compound annual growth rate (CAGR) of 6.5% during the forecast period. The market is poised to grow due to increasing legal requirements, rising awareness among consumers about the benefits of insurance, and the expanding scope of applications across various sectors.
One of the primary growth drivers for the third party insurance market is the increasing legal requirements and regulations mandating insurance coverage. Governments worldwide are implementing stringent laws to ensure that individuals and businesses possess adequate insurance to cover potential liabilities. For instance, in many countries, third party insurance is mandatory for vehicle owners, providing indemnity against potential claims from third parties in case of accidents or damages. This regulatory push is significantly contributing to market growth.
Additionally, the rising awareness among consumers about the benefits of third party insurance is another crucial factor propelling market expansion. Individuals and businesses are increasingly recognizing the importance of safeguarding against unforeseen liabilities, be it in automotive, healthcare, or other sectors. This heightened awareness is driving higher penetration rates of third party insurance products, thus broadening the market base. Marketing campaigns and educational initiatives by insurance companies are also playing a key role in enhancing consumer understanding and uptake of such insurance policies.
Technological advancements and digital transformation in the insurance industry are also major growth catalysts. The adoption of innovative technologies such as artificial intelligence, machine learning, and blockchain is revolutionizing the way insurance companies operate. These technologies are enhancing product offerings, streamlining claim processes, and improving customer experiences. The advent of online distribution channels has further simplified the purchasing process, making third party insurance more accessible to a wider audience. These advancements are expected to continue driving market growth over the forecast period.
Regionally, the market for third party insurance exhibits varied growth patterns. North America, with its well-established insurance industry and robust regulatory framework, holds a significant share of the market. Europe follows closely, driven by stringent regulations and high insurance penetration rates. The Asia Pacific region is anticipated to witness the highest growth rate, fueled by increasing urbanization, rising disposable income, and growing awareness about insurance. Latin America and the Middle East & Africa are also emerging markets, with steady growth expected due to improving economic conditions and regulatory developments.
Ancillary Insurance, often considered a supplementary form of coverage, plays a pivotal role in enhancing the overall insurance portfolio for individuals and businesses. This type of insurance covers additional risks that are not typically included in standard policies, providing a safety net for unforeseen circumstances. In the context of third party insurance, ancillary insurance can offer added protection against specific liabilities, such as legal fees or specialized damages, that might arise from unique situations. As the insurance market continues to evolve, the demand for comprehensive and customizable insurance solutions, including ancillary coverage, is expected to rise. This trend highlights the importance of understanding and integrating ancillary insurance into broader risk management strategies.
The third party insurance market can be segmented by type into liability insurance, property damage insurance, and personal injury insurance. Liability insurance, which covers legal liabilities for damages caused to a third party, is one of the most common types. It encompasses various sub-categories such as general liability, professional liability, and product liability insurance. This segment holds a significant share of the market due to its wide applicability across different industries and its importance in mitigating financial risks associated with legal claims.
Property damage insurance, on the other hand, covers damages caused to third party property. This type of insurance is crucia
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The global third-party logistics (3PL) market is anticipated to grow from USD 1263.4 Billion in 2024 to USD 2549.17 Billion by 2034, at a CAGR of 9.03 % during the forecast period.
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People often exhibit more socially favorable behaviors when observed by others, potentially influencing their cognitive skills and prosocial tendencies. Recent studies have found that individuals with intrinsic prosocial tendencies are non-responsive to social observation in various prosocial decision tasks. This study aimed to investigate whether individuals with intrinsic prosocial tendencies also exhibit a lack of change in their cognitive ability under social observation. We used the Prosocial Reinforcement Learning Task (PRLT) to assess the interaction effect of social observation and intrinsic prosocial tendency on prosocial learning tendency. A total of 102 participants were randomly assigned to either the observation or control group while performing a two-armed bandit task under self- and other-reward conditions, and their behavioral outcomes were analyzed using a reinforcement learning computational model. Under social observation, participants who were previously less prosocial exhibited increased prosocial learning. In contrast, those who were already more prosocial showed no significant changes in prosociality, and demonstrated only a numerical—but statistically non-significant—increase in learning for self. Our findings revealed the differential effects of social observation on modulating one’s prosociality and cognitive ability according to individual differences in intrinsic prosocial tendencies.
According to our latest research, the global online advertising market size reached USD 536.5 billion in 2024, with a robust year-over-year growth trajectory. The market is expected to register a CAGR of 10.2% from 2025 to 2033, ultimately reaching a projected value of USD 1,288.4 billion by 2033. This expansion is being propelled by the rapid digitization of businesses, rising internet penetration, and the increasing shift of advertising budgets from traditional to digital channels. The online advertising market's dynamic nature and adaptability to emerging technologies are key drivers of its sustained growth.
One of the primary growth factors for the online advertising market is the exponential increase in internet users globally, which has directly contributed to the surge in digital content consumption. As of 2024, more than 5.1 billion people are active internet users, representing a vast audience for targeted advertising. The proliferation of smartphones and affordable data plans has made it easier for advertisers to reach consumers at any time and place, further enhancing the efficacy of online campaigns. Moreover, the rise of social media platforms, streaming services, and e-commerce websites has created a plethora of opportunities for brands to engage with their target demographics. These trends underscore the market's evolution, as advertisers continue to leverage data-driven insights and advanced analytics to optimize campaign performance and maximize return on investment.
Another critical driver is the advancement of programmatic advertising technologies, which have revolutionized the way digital ads are bought, placed, and optimized. Programmatic platforms utilize artificial intelligence and machine learning algorithms to automate the ad buying process, enabling real-time bidding and precise audience targeting. This has resulted in higher efficiency, reduced costs, and improved campaign outcomes for advertisers. Additionally, the integration of big data analytics allows for granular segmentation and personalization, ensuring that ads are delivered to the most relevant audiences. As privacy regulations evolve and third-party cookies phase out, advertisers are increasingly investing in first-party data strategies and contextual targeting methods to maintain campaign effectiveness and compliance.
The online advertising market also benefits from the growing adoption of innovative ad formats and immersive technologies, such as augmented reality (AR) and virtual reality (VR) ads. Brands are experimenting with interactive experiences, shoppable videos, and influencer collaborations to capture consumer attention and drive engagement. The rise of connected TV (CTV) and over-the-top (OTT) platforms has opened new avenues for video advertising, enabling brands to reach cord-cutters and younger audiences who are shifting away from traditional television. Furthermore, the integration of e-commerce functionalities within social and video platforms is blurring the lines between content and commerce, creating seamless shopping experiences that drive conversions and boost advertiser revenues.
Regionally, North America continues to dominate the online advertising market, accounting for the largest share in 2024, followed closely by Asia Pacific and Europe. The United States, in particular, remains a global leader due to its mature digital ecosystem, high ad spend per capita, and early adoption of advanced advertising technologies. Asia Pacific is witnessing the fastest growth, driven by the rapid expansion of internet infrastructure, rising smartphone adoption, and increasing digital literacy in countries such as China, India, and Southeast Asian nations. Europe maintains strong momentum, supported by robust regulatory frameworks and a diverse mix of established and emerging markets. Meanwhile, Latin America and the Middle East & Africa are experiencing steady growth, albeit from a lower base, as more businesses embrace digital transformation and online advertising strategies.
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In intergroup conflicts, expressed emotions influence how others see and react to those who express them. Here, we investigated whether this in turn implies that emotions may be expressed strategically. We tested whether emotion expression can differ from emotion experience, and whether emotion expression (more than emotion experience) is used to pursue specific goals. Specifically, we focused on whether support-seeking emotions (fear and sadness) are used to call for support from a powerful third party and contempt to distance from an antagonistic out-group. In two studies, using the same ostensible conflict, we manipulated whether participants communicated their emotions towards the out-group (no vs. yes) and third party (no vs. yes) and employed a between-subjects design in Study 1 (N = 86) and a within-subjects design in Study 2 (N = 83). In both studies, we found that members of a disadvantaged group expressed reduced support-seeking emotions towards the out-group than they experienced (i.e., in conditions without an audience), providing support for the assumption that emotion expression does not necessarily reflect experience. Further, in Study 2, we found in line with expectations that the goal to call for support was more important in the communication with the third party than with the antagonistic out-group. The goal was best predicted by expressed support-seeking emotions, providing support for the assumption that emotion expression is used to pursue goals. Interestingly, we only found this association for a beneficial goal (i.e., calling for support) and not for distancing, a destructive goal. These results support the proposed strategic use of emotion expression and as such advance our understanding of the function of expressed emotions.
In a study on the usage of third-party marketing data in the United States it was found that in 2020, industry professionals in the country spent *** billion U.S. dollars on transactional audience data. Demographic data cost marketers around 4.4. billion dollars that year.