As digital marketers, we often rely on platform interfaces like Google Ads or Meta Ads Manager for insights and actions.

But what if Lars told you that some of the most valuable data and automation opportunities live outside of those interfaces?

In this session, Lars will show you why stepping beyond the UI and embracing tools like the Google Ads API, Meta Marketing API, Python, and AI-assisted development environments like Cursor is essential for the modern marketer.

We’ll explore how to access hidden data, such as product-level performance insights from Meta DPA campaigns, and how to build smarter, more scalable reporting and automation systems that save time and drive better results.

In a world where every marketer is using the same platform tools, real advantage lies in what others don’t see.

By tapping into APIs and leveraging automation, you move from reactive to proactive.
This talk will help you uncover new optimization paths and become the go-to technical marketer in your team.

Learn how to retrieve valuable insights via the Google Ads & Meta APIs, beyond what’s visible in the native dashboard, discover how to automate campaign setup, reporting, and optimizations using Python, AI and Cursor and get inspired by practical examples of how API access and AI-generated scripts can future-proof your marketing operations.

In this session, Amanda will walk through how modern growth is shifting from channel-based marketing to infrastructure-led marketing — where SEO, paid media, data, and AI operate as a single system.
She will explain how leading brands are aligning paid and organic search as a single engine, sharing intent signals, data, and machine-readable structures so platforms and AI agents can accurately interpret and amplify brand visibility.
Amanda will demonstrate how full-funnel acceleration is engineered, with organic insights improving paid efficiency and paid visibility, driving organic lift. She will also cover how AI is being deployed as a core growth engine to automate content velocity, scale performance, and shape algorithmic decision-making.
The session concludes with how to measure what both machines and humans value, adapt in real time to market and algorithm shifts, and apply practical frameworks that teams can execute.