Seeds
How much more accurate is server-side tracking?
In practice, server-side tracking commonly recovers 15-30% more conversions than client-side alone, with some stores seeing more depending on how privacy-heavy their audience is. The...
What technical challenges does a pipeline face?
Data pipelines face five persistent technical challenges: schema drift (upstream sources changing field names or types without warning), event deduplication (preventing the same conversion from...
How much maintenance does a data pipeline really need?
More than the build, and continuously. A self-maintained pipeline absorbs steady ongoing effort, API updates, bug fixes, monitoring, and schema changes, which over time usually...
What happens when my data pipeline fails at 3am?
That depends entirely on who is on call. In a DIY pipeline, the answer is you, and the failure usually goes unnoticed until morning, by...
Why should I outsource my data pipeline instead of building it?
Because outsourcing moves the complexity, and the on-call burden, off your team. A managed provider absorbs the parts that never stop: API updates, security patches,...
Why are enterprise data solutions so expensive?
Because the price is mostly people and guarantees, not software. Enterprise data contracts fund dedicated engineers, round-the-clock monitoring, uptime and support guarantees, security audits, compliance...
Why can't I just build my own tracking pipeline?
You can build one; what people underestimate is keeping it alive. The first version is achievable, but platform APIs change, services rate-limit you, events fail,...
Why do tracking APIs keep breaking?
Because the platforms behind them change constantly, and your integration has to keep pace. Conversion APIs from Meta, Google, and TikTok are revised regularly, with...
Can AI build me a tracking pipeline?
AI can write the initial code, but writing it is the easy part. A tracking pipeline lives or dies on maintenance: platform APIs change, endpoints...
What happens if I shut down my data pipeline?
You lose function immediately and continuity permanently. Within hours, real-time reports stop updating; within weeks, attribution decays into guesswork; within a month or two, any...
Why would I never want to remove my data pipeline once built?
Because removing it breaks the one thing you cannot rebuild: an unbroken history. Tear the pipeline out and reporting goes dark, attribution reverts to guesswork,...
Why is data pipeline infrastructure strategically important?
Because a clean, owned data history is one of the few advantages a competitor cannot copy. They can clone your product, pricing, and ads, but...