Third Party Audience Data
What is third party audience data?
Third party audience data provides information about potential and existing customers, including their behavior, interests, and location details. Typically linked to a specific device ID, audience data provides insights on how individuals spend time online, their information consumption patterns, spending habits, movements, and events they attend.
You can use audience data to create the ideal audience for your products and services, information and promotions, and personalized communication.
Where does this data come from?
Audience and customer data is collected by surveys and by tracking the online behavior of device IDs using various methods, such as cookies. Some data providers collect audience information through their apps and websites to create their own native database. This data can be purchased from third-party data providers, data aggregators, data exchanges, and data marketplaces.
The online sources for cookie tracking include news and informational websites, discussion forums, shopping sites, social media sites, and apps. Cookies are small text files saved in a browser or app with user-specific tracking information. The cookie information includes the time individuals visit a website, how they land on the site, the average time they spent on the site, the products they browsed, items they saved in the shopping cart, and more, depending on various settings. At times username may be part of the cookie data.
Digital fingerprinting is a similar method, providing unique attributes of the device such as the IP address, browser version, screen resolution, and time zone. The digital fingerprint is the aggregated device profile used for identifying bots and possible suspicious activities.
Surveys are typical outbound market research activities. They help understand the opinions, choices, or interests of the respondents which are then used to segment new audiences, target new customers, launch retargeting ad campaigns, and build lookalike audiences. Phone calls and in-person surveys are now being replaced with online or in-app surveys, which provide accurate, real-time data for generating real-time insights.
What types of attributes should I expect?
Audience data can have the following attributes:
- Behavioral data: presents the behavior of the audience, including the time spent and the different actions taken on websites.
- Social engagement data: delivers information about the view, like, share, and post actions on social media platforms.
- Entertainment consumption data: reflects the TV channels and streaming platforms watched, the average duration of a watch, and other related attributes.
- Voter data: indicates the audience alignment towards certain political parties that can be used for campaigning.
- Cross-device identity data: provides attributes helpful to identify audiences accessing your products and services from different devices.
- Contact data: contact information including address, phone number, and other channels to deliver the message to the right audience.
- Demographic data: presents the demographic attributes of the audience, including age, gender, education level, and income bracket. These attributes are critical in customer segmentation and for building custom audiences.
How should I test the quality of the data?
Audience data is derived primarily from cookie tracking and surveys. Testing the quality of these sources should be your fundamental concern. High-quality data that is accurate, consistent, and timely is essential to the credibility of your analysis.
Besides these major factors, make sure that the data is privacy-compliant (CCPA and GDPR), as personal information is part of the attributes.
To test the quality of the data:
- Ensure the credibility of the diverse sources providing the data.
- Test the data for accuracy and frequency of updates.
- Ascertain that the vendor guarantees identity validation of the tracked data.
- Confirm that the data is privacy-compliant.
- Validate the methodology and models used by the vendor.
- Test with a sample to ensure the dataset can easily integrate with your systems and models.
Who uses third party audience data?
The right data helps marketers understand their target audience to build targeted marketing campaigns and improve customer experiences. Small, medium, and large companies use this 3rd party data for a wide range of advertising and marketing use cases.
Digital marketing demands actionable insights for agile response to customer needs, and audience data provides the required inputs. Companies leverage audience data to:
- Target potential customers with correctly aligned content and advertisements.
- Engage current customers with personalized offers.
- Win back past customers with improved products and services.
What are the common challenges when buying third party audience data?
Accuracy is the topmost challenge when buying audience data. Only accurate data can deliver trusted insights required for audience targeting. The data sources vary from surveys to cookie tracking, and assuring source credibility for data accuracy is difficult. This concern of data accuracy is common for most categories of demographic data, as the data may not get updated frequently, and its sources may not be reliable. While surveys typically gather accurate basic information, survey respondents may not record their opinions and choices truthfully. On the other hand, cookie tracking precisely provides device-related information, though it may not ensure reliable identity validation across multiple devices.
Along with accuracy, ensuring data timeliness and compliance with privacy regulations are key challenges for audience data.
- Data accuracy: Authenticity of audience interests and opinions is critical for driving correct segmentation and targeted promotions. The methods of data collection, tools used for online tracking and identity validation, and the strict quality testing from the vendor side determine the accuracy of data.
- Data timeliness and consistency: Audience choices are changeable, and their activities are dynamic. Data updated in real-time can portray the most recent characteristics of a segment to personalize the message accordingly. In addition to timeliness, data must be consistent across diverse sources to deliver trusted insights into the audience.
- Privacy compliance: Audience data often includes personally identifiable information (PII). The vendor must certify the data as privacy-compliant for all the required privacy regulations.
What are similar data types?
Audience data is similar to demographic data, social media presence, consumer lifestyle data, and other related consumer data categories used in audience insights and targeting.
You can find a variety of examples of consumer and demographic data in the Explorium Data Gallery.
Sign up for Explorium’s 14-day free trial to access the data available on the platform.
What are the most common use cases of third party audience data?
The most common use cases for audience data include audience insights, audience segmentation, and audience targeting. As with other demographic data, this data is also used extensively in digital marketing to enrich the audience profiles. Many companies maintain their native audience database and augment it with third-party data specific to their target customer segment.
- Audience insights: Identifying and refining audience needs, perceptions, motivations, and choices relevant to specific products or services provide deep insights into their behavior. Companies leverage the enhanced understanding of the audience to deliver the most effective personalized communication. Insights into audience needs can drive the development of better products and a broader range of services.
- Audience segmentation: Beginning with audience analysis and insights, marketers typically segment the audience into smaller groups. Smaller segments empower companies to address specific needs with improved user experience and optimize their resources for better ROI. Audience data enriches audience profiles and refines the segmentation for targeted communication and promotional offers.
- Audience Targeting: Digital marketing uses the strategy of identifying accurate target audiences by their behavioral characteristics. Marketers then focus on the group that most likely will buy the products and services. Targeting such a group helps deliver personalized communication, engage more closely, build loyalty, and realize better ROI on marketing spend. Continuously interacting with the target audience also helps understand their needs and develop products or services to fulfill those needs.
Which industries commonly use this type of data?
Most consumer companies commonly use this data for marketing and advertising. The industries include eCommerce, retail, CPG, travel, hospitality, leisure, entertainment, financial service providers, insurance providers, and banking.
How can you judge the quality of your vendors?
Vendors use diverse sources for audience data, including surveys and cookie tracking. As this data drives the personalization of messages and offers, it must be accurate and recently updated. You can judge the quality of vendors supplying audience data by how their customers rate them, how they can demonstrate the offerings to you, and how their reps can respond to your specific queries.
- Customer reviews and case studies: Satisfied customers highlight the positive points about the vendor in testimonials, while others may point out opportunities for improvements. Both types of reviews offer you the market assessment of the vendor. If the vendor website lists case studies in detail, they can show the level of vendor engagement and ability to provide custom solutions. Case studies demonstrate the range and quality of data attributes, which you can evaluate for your requirements.
- Demo: A live or recorded demo can immediately illustrate the data, suitable use cases, and the ease of integration. Many vendors provide sample datasets along with demos to help your assessment.
- Interacting with vendor reps: Customer reviews and demos help you arrive at a shortlist of few suitable vendors. Contacting and discussing your requirements with their reps can decide the next step. The vendor reps address your queries and may offer custom datasets for your use cases. At times, interaction with reps can create a long-term partnership that can be beneficial to both parties.