Using third-party data to train AI: A guide for marketers
Large language models and artificial intelligence are quickly becoming essential for Australian marketers looking to bring personalisation, efficiency, and scale to their omnichannel strategies. Whether it’s tailoring offers in real time or orchestrating the perfect mix of touchpoints, AI helps turn sprawling data into focused and ever-improving action.
To train these models, brands are increasingly relying on their own first-party data. It’s a strong starting point, but no single dataset can capture the full complexity of today’s customer journey. First-party data reflects what a brand already knows, but not always what it needs to know. This is where high-quality third-party data becomes critical: It fills the gaps, extends visibility, and ensures that AI-driven insights are complete and representative.
Here are three practical scenarios showing how third-party data plays a critical role in training AI to deliver better marketing outcomes.
Eyeota, a Dun & Bradstreet company, is a trusted global provider of audience solutions that empower brands to enrich insights, enhance personalisation, and transform omnichannel targeting. Founded in 2010 to meet the rising demand for high-quality audience data in an emerging programmatic ecosystem, Eyeota created a global data marketplace built for scale, transparency, and performance. As digital marketing evolved, Eyeota quickly became a leader in the data space, culminating in its acquisition by Dun & Bradstreet in 2021.
Today, Eyeota is recognized as the #1 Global Data Provider, offering marketers independently audited audience data they can trust.
