DAD014: Discussing Compliance, GTM/GA4 & Automation with Dan Truman

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DAD014: Discussing Compliance, GTM/GA4 & Automation with Dan Truman

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【Amazonプライム会員限定】今ならプレミアムプランが4か月月額99円。

10月19日まで。※適用条件あり

This episode explores the state of digital analytics across consent and ethics, UK/EU regulatory shifts, implementation pitfalls in GA4 and GTM (client‑side and server‑side), what “good” governance looks like, misconceptions that hold businesses back, and how automation and AI will reshape MarTech. The discussion balances NON-legal guidance (we are not lawyers - we will discuss how we would guide our clients) & ethical nuance (cookie consent, PECR/ePrivacy, “ads‑or‑data” paywalls, consent mode ambiguity) with hands‑on implementation guidance (trigger ordering, config tags, enhanced measurement pitfalls, server‑side GTM on first‑party endpoints). It closes with pragmatic views on analytics as a revenue function and near‑term opportunities to productise repeatable work with automation and AI agents.

Rising public awareness of data collection and the messy reality of consent banners, paywalls, and browser‑level signals—and how this varies by market.
Regulatory ambiguity (UK guidance, PECR/ePrivacy/DUAA interplay, “statistical analysis” carve‑outs) and why organisations must define a clear legal/ethical risk posture—not just a technical stance.
Consent Mode, Google Signals, and the “German GTM ruling”: what actually triggered panic, why context matters, and how intent and downstream controls are key.
GA4/GTM mistakes: firing order and race conditions, multiple config tags, over‑reliance on Enhanced Measurement, noisy form submits, undocumented “cute” renames, legacy tags, and excessive custom JS.
Server‑side GTM: value, common missteps (not truly first‑party endpoints, A‑record/IP mismatches), and SaaS vs self‑host trade‑offs.
Analytics isn’t “plug‑and‑play”; “capture everything” promises just shift effort from engineering to data teams. Analytics is a revenue function that powers activation and models.
AI/automation: use agents and scripts to productise repeatable tasks, orchestrate tools, and summarise outputs rather than “let AI do it all.”

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