Third-Party Data
Third-party data is information collected by an entity that does not have a direct relationship with the user, typically aggregated from multiple sources and sold or shared for advertising targeting and audience enrichment.
Also known as: 3P data, purchased data, external data
Why It Matters
Third-party data has historically powered much of digital advertising. Advertisers could purchase audience segments based on demographics, interests, and purchase intent without ever interacting with those users directly. This enabled precise ad targeting at scale - showing car ads to people identified as "in-market for a new vehicle" based on their browsing behavior across thousands of sites.
However, third-party data is in rapid decline. Browser vendors (Safari, Firefox, and eventually Chrome) are eliminating third-party cookies that enable cross-site tracking. Privacy regulations require explicit consent for data sharing across organizations. And consumers increasingly use ad blockers and privacy tools that prevent third-party data collection.
The deprecation of third-party data is forcing a fundamental shift in digital marketing toward first-party data strategies, contextual targeting, and privacy-preserving advertising technologies. Companies that continue to depend heavily on third-party data face growing accuracy problems, rising costs, and regulatory risk.
Industry Applications
An ecommerce brand that previously spent 40% of its ad budget on third-party audience targeting shifts to first-party data lookalike audiences and contextual targeting, achieving similar ROAS with better privacy compliance.
A B2B SaaS company replaces purchased intent data with first-party website behavior signals and email engagement data for lead scoring, finding that their own data predicts conversion 2x better than third-party intent signals.
How to Track in KISSmetrics
KISSmetrics operates entirely on first-party data, making it well-positioned for the post-third-party-cookie era. To reduce your dependence on third-party data, invest in building robust first-party data collection through KISSmetrics and focus on converting anonymous visitors into known users through login incentives and value exchanges.
Common Mistakes
- -Building critical marketing programs on third-party data without a transition plan to first-party alternatives.
- -Assuming third-party data accuracy matches first-party data - third-party segments can have error rates of 30-50%.
- -Not considering the reputational risk of using third-party data that may have been collected without proper user consent.
- -Conflating third-party data with third-party cookies - they are related but distinct concepts.
Pro Tips
- +Audit your current reliance on third-party data across all marketing and analytics activities. Build a prioritized migration plan toward first-party alternatives.
- +Explore privacy-preserving alternatives like Google Topics API, contextual targeting, and publisher first-party data partnerships.
- +Use first-party data lookalike modeling as a replacement for third-party audience segments.
- +If you still use third-party data, validate its accuracy by comparing it against your first-party data for overlap segments.
Related Terms
First-Party Data
First-party data is information collected directly by a company from its own customers and website visitors through owned channels, including behavioral data, purchase history, and voluntarily provided personal information.
Cookie
A cookie is a small text file stored by a web browser on a user's device that allows websites to remember information between page loads and across visits, widely used in analytics to identify returning visitors.
Pixel
A tracking pixel is a tiny, invisible image (typically 1x1 pixel) or JavaScript snippet embedded in a web page or email that sends data to a server when loaded, used to track page views, conversions, and user behavior.
User Identity
User identity in analytics refers to a unique identifier - such as an email address, user ID, or account number - that links a specific real person to their tracked behaviors and interactions across sessions and devices.
Identity Resolution
Identity resolution is the process of connecting multiple identifiers and data points across devices, channels, and sessions to create a single, unified profile for each individual user.
See Third-Party Data in action
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