Something keeps bothering me. In most projects, analytics feels like infrastructure that no one is genuinely excited about. People rarely want to invest in it when building a product. It’s treated as something you should have, not something you want to have.
Teams are “happy” to pay for software development, advertising, copywriting, design. Those are seen as directly useful. Analytics (GA4, event tracking, or even more structured setups like CDPs) is often perceived as background noise, necessary to keep the engine running, but not something that meaningfully moves the product forward day to day.
In practice, many teams end up using only a handful of metrics to make decisions, even when a complex analytics stack exists underneath. The rest is there “just in case.”
I’m curious whether others see the same pattern. Is analytics undervalued because its ROI is indirect and delayed? Or is most analytics work simply over-engineered for the actual decisions teams make? At what point does analytics shift from “necessary plumbing” to a real competitive advantage?
Would love to hear perspectives from founders, engineers, and product folks who’ve built and scaled things.
lbhdc•2h ago
I think it often comes down to who is responsible for making decisions with that data. If a product or business person is the one driving a feature, and looking for adoption, the engineers likely aren't going to be invested in building out sophisticated metrics. They get the metrics they are responsible for from their cloud provider (resource use/latency/scale).
I think that problem is compounded by the perception that these integrations are going to tank your products perf (may hurt the metrics engineers care about).
I think all of those dynamics change in really big companies with thousands of engineers. Then you can often end up in a situation where engineers are now required to maximize product metrics, and need visibility into their small slice of the pie.
So, I think its largely incentive, which is why I see all of the metrics vendors targeting product and sales people in small/mid sized companies.
tiazm•38m ago
Because of that, the analytics layer is often seen as something secondary. As long as the top line numbers are moving, there’s little perceived urgency to invest in a structured analytics foundation that explains why those numbers move.
So even when incentives exist, they’re often too outcome focused. Analytics that helps understand mechanisms, not just results, struggles to justify itself until something breaks or growth stalls.