As AI-driven bidding and automation revolutionize paid media, first-party data has become the most powerful lever marketers control.
In this interview with Search Engine Land, Julie Warneke, founder and CEO of Found Search Marketing, explained why first-party data now supports profitable advertising – regardless of how Google’s position on third-party cookies changes.
What first person data really is – and isn’t
First-party data is customer information the marketer has directly, usually stored in a CRM. Includes:
- Lead details.
- Purchase history.
- Net worth.
- Customer value collected through websites, forms, or physical locations.
It does not include platform-hosted or browser-based data that advertisers cannot fully control.
Why first-party data is more important than ever
Digital advertising has gone from paying for impressions, to clicks, to actions – and now to results. The real goal is no longer just conversion, but profitable conversion, according to Warneke.
As AI systems process far more signals than humans can handle, marketers who provide high-quality customer data gain a clear advantage.
CPCs can go up – but so can profits
Rising cost per click is a reality of paid media. First-party data doesn’t always generate CPCs, but it does improve what matters most: conversion quality, revenue, and return on ad spend.
By focusing on low-level business results instead of high-level metrics, marketers can justify higher costs with stronger results.
How first party data improves ROAS
When marketers feed Google data tied to revenue and customer value, AI bidding systems can prioritize users like high-value customers — often using signals that go beyond demographics or location.
The result is traffic that converts better, even if marketers never see or control the underlying signals.
Performance Max leads the way
Among campaign types, Performance Max (PMax) currently benefits the most from first-person data activation.
PMax works best when marketers move away from manual optimization and instead focus on providing accurate, consistent data, then letting the system learn, Warneke notes.
SMBs are not out of the question — but they do need the right setup
Small and medium-sized enterprises are not disadvantaged by the limited data volume of the first company. Warneke shared examples of success with client lists as small as 100 records.
The real hurdle for SMBs is infrastructure – especially proper tracking, permission management, and reliable data pipelines.
The biggest mistakes marketers make
Two things stand out:
- Weak data capture: Many brands still rely on browser-side tracking, which continues to fail – especially on iOS.
- Broken feedback loops: Others load CRM data periodically instead of building a continuous flow of data that allows AI systems to learn and improve over time.
What marketers should do next
Warneke’s advice: Go back and examine how data is captured, stored, and returned to platforms, then improve it further.
There is no need to change everything at once or risk the entire budget. Even experimenting with 5–7% of the money spent can create a learning curve that brings long-term benefits.
Bottom line
AI processes the signals it receives – good or bad. Advertisers who own and refine their first-party data can shape results in their favor, while those who don’t risk being developed to underperform.
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