Third-party data
Also: 3rd-party data, third party data, purchased data, brokered data, aggregated audience data, donnees tierces
Data purchased from external aggregators, collected from audiences you don't own. It is bought or licensed rather than gathered through your own direct relationships.
What it is
Third-party data is information about individuals or organizations that you did not collect yourself and that comes from sources with which you have no direct relationship. It is typically bought or licensed from data brokers, aggregators, or exchanges that gather signals across many websites, apps, and offline sources, then package and sell it.
It is distinguished from two related categories:
- First-party data: collected directly from your own customers and audiences (purchases, logins, site behavior).
- Second-party data: another company's first-party data, shared or sold to you directly, without an aggregator in the middle.
Third-party data is defined by the absence of a direct relationship with the person the data describes.
Why it matters
- Scale and reach: it lets you target or model people beyond your existing customer base.
- Enrichment: it appends attributes (demographics, firmographics, interests, intent signals) to records you already hold.
- Declining reliability: browser restrictions on third-party cookies, mobile identifier limits, and privacy laws (GDPR, CCPA) have reduced its accuracy and legality.
- Compliance risk: because consent was not obtained by you, provenance and lawful basis can be hard to verify.
How it is used in practice
- Audience targeting in advertising platforms and demand-side platforms.
- Lead scoring and enrichment in B2B sales and marketing.
- Credit and risk models in finance, using bureau and alternative data.
- Market sizing and competitive benchmarking.
A common technique is a data match: you upload hashed identifiers (emails, device IDs), the vendor matches them against its pool, and returns appended attributes or a lookalike segment.
Concrete worked example
A retailer wants to reach likely luxury car buyers. It licenses a segment from a data aggregator labeled "in-market: premium automotive" covering 4 million cookies or device IDs. The retailer pushes this segment into its ad platform and runs a campaign.
- Match rate: only 55 percent of IDs are still active, so effective reach is about 2.2 million.
- Accuracy: the aggregator inferred intent from browsing, so some users are researchers, not buyers.
- Cost: the segment is priced per thousand impressions (CPM) on top of media cost.
The retailer measures conversions against a control group and finds the segment underperforms its own first-party purchase data, a typical outcome that pushes many organizations back toward owned data.