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

Global Audience Analysis Market is Segmented by Application (Sales & Marketing, Customer Experience), End-user Industry (BFSI, Telecom & IT, Healthcare, Government, Media & Entertainment, Retail), and Geography (North America, Europe, Asia-Pacific, and Rest of the World). The market sizes and forecasts are provided in terms of value (USD million) for all the above segments.

In 2021, expenditure on third party audience data in the United States amounted to 22 billion U.S. dollars, out of which 13.3 billion was spent on data itself and 8.7 billion on audience data activation solutions.

Audience Analytics Market size was valued at USD 5.6 Billion in 2023 and is projected to reach USD 17.7 Billion by 2030, growing at a CAGR of 12.8% during the forecast period 2024-2030.

Global Audience Analytics Market Drivers

The market drivers for the Audience Analytics Market can be influenced by various factors. These may include:

Growing Adoption of Digital Marketing: Companies are spending more on digital marketing initiatives as a result of the expansion of digital platforms and channels. The need for these kinds of solutions is fueled by audience analytics, which offer insightful data on customer behavior, preferences, and engagement across many digital platforms.
Increasing Focus on Personalization: In order to improve consumer engagement and loyalty, businesses are realizing the value of personalized marketing. Businesses can create more individualized and targeted marketing efforts by using audience analytics to better understand the segments of their audience.
Growth of AI and Big Data Technologies: To extract actionable insights from the growing amount, diversity, and speed of data created by digital interactions, sophisticated analytics techniques are needed. Artificial intelligence (AI) algorithms and big data technologies are used by audience analytics systems to evaluate massive datasets and derive useful insights about audience behavior.
Demand for Real-Time Analytics: Businesses need real-time information to make swift, well-informed choices in today’s fast-paced digital environment. Businesses may react swiftly to shifting customer behavior and market trends by utilizing audience analytics tools with real-time monitoring and analysis features.
Growth of Online Retail and E-commerce: As e-commerce platforms proliferate, a huge amount of data is generated from online transactions, website visits, and social media interactions. E-commerce companies may increase sales and revenue by better understanding consumer preferences, making better product recommendations, and streamlining the customer journey with the use of audience analytics technologies.
Growing Competition and the Need for Competitive Intelligence: Companies are up against fierce competition in the digital sphere, therefore it’s critical to use data-driven insights to obtain a competitive advantage. By examining industry trends, competitor behavior, and customer sentiment, audience analytics offer useful competitive data that keeps organizations one step ahead of the competition.
Data privacy and regulatory compliance: As a result of the introduction of data protection legislation like the CCPA and GDPR, businesses are placing a greater emphasis on adhering to data privacy requirements. In order to address privacy issues and gain the trust of customers, audience analytics systems must abide by these laws and provide strong data protection safeguards.

Users between 18 and 34 years old made up the highest share of the social media advertising audience in Poland in January 2024. The percentage of women was higher in each age group.

We collect, validate, model, and segment raw data signals from over 900+ sources globally to deliver thousands of mobile audience segments. We then combine that data with other public and private data sources to derive interests, intent, and behavioral attributes. Our proprietary algorithms then clean, enrich, unify and aggregate these data sets for use in our products. We have categorized our audience data into consumable categories such as interest, demographics, behavior, geography, etc. Audience Data Categories:Below mentioned data categories include consumer behavioral data and consumer profiles (available for the US and Australia) divided into various data categories. Brand Shoppers:Methodology: This category has been created based on the high intent of users in terms of their visits to Brand outlets in the real world. To create segments containing users with a high-affinity index, we use a precise determination of the number of occurrences at a given time. Place Category Visitors:Methodology: This category has been created based on the high intent of users visiting specific places of interest in the real world. To create segments containing users with a high-affinity index, we use a precise determination of the number of occurrences at a given time. Demographics:This category has been created based on deterministic data that we receive from apps based on the declared gender and age data. Marital Status, Education, Party affiliation, and State residency are available in the US. Geo-Behavioural:This category has been created based on the high intent of users in terms of the frequency of their visits to specific granular places of interest in the real world. To create segments containing users with a high-affinity index, we use a precise determination of the number of occurrences at a given time. Interests:This segment is created based on users' interest in a specific subject while browsing the internet when the visited website category is clearly focused on a specific subject such as cars, cooking, traveling, etc. We use a deterministic model to assign a proper profile and time that information is valid. The recency of data can range from 14 to 30 days, depending on the topic. Intent:Factori receives data from many partners to deliver high-quality pieces of information about users’ shopping intent. We collect data from sources connected to the eCommerce sector and we also receive data connected to online transactions from affiliate networks to deliver the most accurate segments with purchase intentions, such as laptops, mobile phones, or cars. The recency of data can range from 7 to 14 days depending on the product category. Events:This category was created based on the high interest of users in terms of content related to specific global events - sports, culture, and gaming. Among the event segments, we also distinguish categories related to the interest in certain lifestyle choices and behaviors. To create segments containing users with a high-affinity index, we use a precise determination of the number of occurrences at a given time. App Usage:Mobile category is a branch of the taxonomy that is dedicated only to the data that is based on mobile advertising IDs. It is based on the categorization of the mobile apps that the user has installed on the device. Auto Ownership:Consumer Profiles - Available for US and AustraliaThis audience has been created based on users declaring that they own a certain brand of automobile and other automotive attributes via a survey or registration. These audiences are currently available in the USA. Motorcycle Ownership:Consumer Profiles - Available for US and AustraliaThis audience has been created based on users declaring that they own a certain brand of motorcycle and other motorcycle-based attributes via a survey or registration. These audiences are currently available for the USA. Household:Consumer Profiles - Available for the US and AustraliaThis audience has been created based on users' declaring their marital status, parental status, and the overall number of children via a survey or registration. These audiences are currently available in the USA. Financial:Consumer Profiles - Available for the US and Australia this audience has been created based on their behavior in different financial services like property ownership, mortgage, investing behavior, and wealth and declaring their estimated net worth via a survey or registration. Purchase/ Spending Behavior:Consumer Profiles - Available for the US and AustraliaThis audience has been created based on their behavior in different spending behaviors in different business verticals available in the USA. Clusters:Consumer Profiles - Available for the US and AustraliaClusters are groups of consumers who exhibit similar demographic, lifestyle, and media consumption characteristics, empowering marketers to understand the unique attributes that comprise their most profitable consumer segments. Armed with this rich data, data scientists can drive analytics and modeling to power their brand’s unique marketing initiatives. B2B Audiences;Consumer Profiles - Available for US and AustraliaThis audience has been created based on users declaring their employee credentials, designations, and companies they work in, further specifying business verticals, revenue breakdowns, and headquarters locations. Customizable Audiences Data Segment:Brands can choose the appropriate pre-made audience segments or ask our data experts about creating a custom segment that is precisely tailored to your brief in order to reach their target customers and boost the campaign's effectiveness. Location Query Granularity:Minimum area: HEX 8Maximum area: QuadKey 17/City

The global audience analytics market size was estimated at USD 4.16 billion in 2022 and is expected to grow at a CAGR of 11.8% from 2023 to 2030

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 2.5 billion U.S. dollars on transactional audience data. Demographic data cost marketers around 4.4. billion dollars that year.

Increasing number of viewers on Over-The-Top (OTT) media platforms and increasing video content among rapidly expanding audiences during and after COVID-19 lockdowns are key factors driving revenue growth of the global video audience measurement market | TV & Video Audience Measurement | Video Audience Measurement & OTT Analytics Platform

As of January 2024, it was found that 18 percent of TikTok's global audience were women between the ages of 18 and 24 years, while male users of the same age made up approximately 18.6 percent of the platform's audience. The online audience of the popular social video platform was further composed of 15 percent female users aged between 25 and 34 years, and 17.6 percent of male users in the same age group.

As of January 2024, Meta's largest audience were women aged 25 to 34 years, who made up 12.4 percent of users. Men of the same age group followed, accounting for 11.9 percent of users. Overall, less than 15 percent of Meta's audience, which includes platforms Facebook, Instagram, and Messenger, were aged between 65 years and above.

The data presented in this paper is used to examine the behavioral factors that influence the preferences of foods in Indonesia, and Indonesian audiences’ segmentation behind those preferences, provided by social media data. We collected the data through an online platform by performing a query search on Facebook Audience Insights Interests. The keywords that we use in the question quest are based on the United Nations Food and Agriculture Organisation (FAO) Food Balance Sheet (FBS) which is retrieved from FAOStat in May 2020. The data was gathered between 15 May and 2 July 2020. With a sample size of 100-150 million viewers or about 36.95 per cent-55.43 per cent of Indonesia 's 2019 population, we limited our sample to Indonesia. The dataset is made up of ten tables that can be separately analyzed. For each table, we carry out exploratory data analysis (EDA) to provide more insights. Such data could be of interest to various fields, including food scientists, government and policymakers, data scientists/analysts, and marketers. This data could also be the complementary source for the scarcity of food survey data from the government, particularly the behavioral aspects.

This targeting database gives you an in-depth understanding of your potential audience. With this wealth of information, you can make personalized marketing efforts that speak directly to the needs and wants of your target users.

We can also provide region-specific data (MENA, Africa, APAC, etc.) based on your specific requirements. Our pricing model includes an annual licensing option, and we provide free sample data so that you can evaluate the quality of our dataset for yourself.

The charts shows the share of marketers worldwide who believed their organization targeted audiences effectively with use of data as of May 2018, by business type. According to the study from Quantcast, 83 percent of global direct brand marketers believed their company was effectively using first-party data to target audiences, while 65 percent said the same about their use of third-party data.

As of January 2024, the advertising audience in Romania across Facebook, Instagram, and Facebook Messenger was mainly composed of people of ages between 25 and 44 years old. At the same time, the audience consisted of more women than men.

Redmob’s audience data enables you to connect with the ideal users from over 130 countries, expertly crafted to suit your requirements. Key attributes of our data include MAID, interests, location, device manufacturers, and more.

Our Audience Data serves as a powerful tool for businesses seeking to understand and engage with their customers on a deeper level. With this data at your fingertips, you can transform your audience's understanding and ultimately set your business apart in today's competitive landscape.

We can also provide region-specific data (MENA, Africa, APAC, etc.) based on your specific requirements. Our pricing model includes an annual licensing option, and we provide free sample data so that you can evaluate the quality of our dataset for yourself.

Raw data signals from our SDK and direct publisher integrations are used to model our audiences. To model demographic data such as age and gender, we use machine learning algorithms. We create a model of user interest based on app usage and ad engagement. We also use location data to intersect with known POIs to model interest.

Deterministic audiences are based on device metadata such as the make and model of the device, the carrier of the sim and cell, and some are based on app users (i.e. users who have Netflix installed).

Signals such as GPS, Wifi, and cell towers are used to create location-based audiences. Furthermore, we enhance accurate location data utilising advanced enticements techniques.

The global audience analytics market size was valued at USD 4.62 billion in 2023. It is estimated to reach USD 11.90 billion by 2032, growing at a CAGR of 11.09% during the forecast period (2024–2032). The world has transitioned towards digitiz Report Scope:

We collected the data through an online platform by performing a query search on Facebook Audience Insights Interests. The keywords that we use in the question quest are based on the United Nations Food and Agriculture Organisation (FAO) Food Balance Sheet (FBS) which is retrieved from FAOStat in May 2020. The data was gathered between 15 May and 2 July 2020. With a sample size of 100-150 million viewers or about 36.95 per cent-55.43 percent of Indonesia's 2019 population, we limited our sample to Indonesia. The dataset is made up of ten tables that can be separately analyzed. For each table, we carry out exploratory data analysis (EDA) to provide more insights.