In this episode of E-Coffee with Experts, Austin Willman sits down with Julien Simon, Co-Founder at 1UP Digital Marketing, to unpack how agencies must evolve in the age of AI. Julien shares why he believes the number of agencies will shrink, but the ones that survive will be the ones building AI-powered systems rather than offering commoditized, task-based services.

The conversation dives deep into 1UP’s approach to transparency, including the client-facing “hub” they’re building to centralize performance data, KPIs, invoices, and project status in real time. Julien also breaks down the technical side of marketing measurement, explaining server-side tracking, why third-party cookie loss is costing brands 20-50% of their data, and how to align GA4, CRM, and ad platform numbers to make real decisions instead of guesses.

Julien also discusses how 1UP earns visibility in LLM tools like ChatGPT, why AI search impressions are still a vanity metric until click data arrives, and how Google’s push against filler content rewards brands with real first-hand experience and a clear point of view.

Rounding out the episode, Julien explains how 1UP’s core values (we care, we lead, we make a positive impact) shape hiring, client selection, and team culture through initiatives like their positive impact committee and monthly community challenges.

Whether you’re an agency owner rethinking your service model or a marketer trying to make sense of attribution in a privacy-first world, this episode offers a grounded, practical look at where digital marketing is headed.

Takeaways:

  1. Agencies must build AI-powered systems, not manage tasks manually
  2. Client-facing hubs centralize KPIs, invoices, and project updates
  3. Server-side tracking preserves first-party data from browser restrictions
  4. Aligning GA4, CRM, and ad platforms is critical before trusting data
  5. AI search impressions remain a vanity metric without click data
  6. Google rewards content with first-hand experience over generic filler
  7. Core values should filter hiring, clients, and partnership decisions
  8. Focus on 2-3 key KPIs before diagnosing a bigger data problem