Joel Miller is the co-founder of The SkyFloor, a digital agency he has run alongside his identical twin brother since 2008. The SkyFloor works across industries — churches, retail, education, and service organizations — with a philosophy centered on long-term partnerships and outcome-driven strategy rather than one-off deliverables. Joel writes regularly on digital strategy and business growth at theskyfloor.com/ideas.
What We Cover - Why the highest-value work any agency or consultant does is enabling clients to become who they want to be — and why AI can't replicate that
- A real-world custom GPT case study: how 30–40 hours of human listening made AI call analysis actually work
- What AI Overviews are doing to organic click-through rates, ad keyword availability, and SERP composition
- Why owned audience channels — especially email — are now the most durable marketing asset in a Google-disrupted world
- The AI slop problem and why authentic human presence is becoming the scarcest commodity online
Episode Highlights Joel opens by reframing what The SkyFloor actually sells: not services, but outcomes. He describes their team as problem solvers who work backward from what a client wants to become — whether that's a more efficient church, a retail brand competing online, or an education company ready to grow beyond referrals. That outcome-first philosophy maps onto what Jeremy calls the pyramid of value: executing a tactic at the base, saving time in the middle, and enabling the client to become who they want to be at the top. As Joel puts it, the human ingenuity required to genuinely partner with a client is still a distinctly human task — one AI cannot replicate at the top of that pyramid.
The conversation gets practical fast with Joel's sales call analysis case study. A client had lead conversion problems, and rather than feeding transcripts into a model, Joel listened to 30–40 hours of incoming calls himself — catching tone, the weight of a specific pause, the difference between enthusiasm and polite deflection. Once he'd mapped those human-observed patterns, he built a custom GPT framework and connected it to CallRail for automatic call scoring. The human defines the problem; AI scales the execution. Joel was equally candid about LLM limitations: ask an LLM for an answer and you've already biased the output. It is an answer engine, not an objective analyst — and the good prompt engineers know how to work around that tendency.
"An audience can't just be taken away if it's your audience, no matter what Google does next."
Joel is watching AI Overview impact in real time across his client accounts: impressions holding or growing, clicks down ~40%, and SERP layouts restructured so that for many queries, organic results appear nowhere above the fold. The composition is now AI Overview, then local pack, then sponsored results — organic is buried or absent. On the paid side, keyword categories that used to reliably trigger ad placements have been absorbed by overview content. His adaptation: heavier investment in high-intent near-me queries that still trigger standard ad slots, and a shift away from treating search volume as the primary planning input toward full SERP composition audits.
The most durable advice from the episode is Joel's audience ownership argument. He's actively steering clients toward email lists and direct subscriber relationships — assets that t...
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