Myth: Marketing needs a data lake to be data-driven Someone always proposes a data lake for the marketing org. The correction: marketing's data is structured and modest in scale — a warehouse with dbt…
Myth: No-code automation scales your ops forever The pitch: replace engineers with no-code and never look back. The correction: Zapier/Make sprawl becomes an unversioned, untested production system th…
Myth: Reverse ETL is just a cheaper CDP The shorthand says reverse ETL = budget CDP. The correction: they solve different layers — reverse ETL moves data, a CDP also owns identity, consent, and audien…
Myth: A bad tool means it's time to rip and replace The reflex when a platform underperforms: tear it out, re-evaluate, re-implement. The correction: most stack pain is configuration and ownership, no…
Myth: Personalization has to be real-time to matter Vendors sell millisecond decisioning as table stakes. The correction: for most lifecycle and email use cases, a batch refresh every few hours lifts …
Myth: A bigger stack means a more sophisticated team The LinkedIn flex is a 90-logo stack diagram. The correction: utilization data shows the median martech stack uses only a third of what it pays for…