Why I Built a Cookieless Analytics Tool Before Writing About Privacy
Before I wrote a single guide about data privacy for small businesses, I built the thing I was going to tell people to build. That is not virtue — it is the only honest way to give advice about operational tools. If I cannot make it work for myself, I have no business telling you to try it.
The problem I was actually solving
I wanted to understand how people use this platform — which pages they visit, where they come from, what they engage with — without collecting anything that would require a consent banner or create privacy obligations I was not prepared to manage.
The standard solution is Google Analytics. I know GA well. I have implemented it dozens of times. I chose not to use it here for a specific reason: GA collects far more than I need, creates a dependency on a third party whose incentives are not aligned with mine, and sends data to infrastructure I do not control. For a platform built around data privacy practices, using GA would be incoherent.
So I built a cookieless beacon instead.
What I actually built
A small JavaScript snippet on every page fires on load and sends a minimal event to my own server: page path, referrer, and a daily hash of the IP address that cannot be reversed to identify a visitor tomorrow. My server writes the event to a Postgres table I control. A nightly job rolls up the raw events into daily aggregates.
No cookies. No browser storage. No third-party script loading a tracking network I did not choose. The measurement stack is mine — the same infrastructure that runs everything else on this platform.
That architecture is simpler than most people expect. The complexity in traditional analytics usually comes from identity persistence, cross-site tracking, and vendor-side data enrichment — not from counting page views and referrers.
Three things building it taught me
First: cookieless analytics is not harder than cookied analytics — it is simpler. There are fewer moving parts, fewer vendor dependencies, and fewer things that can break. When something looks wrong in the dashboard, I can trace it through code I wrote and tables I own. That matters when you are a small operator without a dedicated analytics team.
Second: aggregate data is usually enough. I can see which pages people visit most, where they come from, and which content gets engagement. That is enough to make meaningful decisions about what to write next, which entry points to improve, and where traffic is actually coming from. The cases where you genuinely need individual-level data across sessions are rarer than the analytics industry would have you believe — especially for a business making operational decisions rather than running retargeting campaigns.
Third: the data feels different when it lives in infrastructure you control. Not just from a privacy standpoint — from a trust standpoint. I know exactly what is being collected and why. I could explain it to any user in two sentences if they asked. That clarity changes how you think about measurement. You stop treating analytics as something that happens to your site and start treating it as something your operation runs.
What this means if you are evaluating analytics for your own site
If you are a small business owner trying to decide whether you need a full analytics stack, start with what decisions you actually need to make — not what metrics are available. Most operators I talk to need trend visibility, source attribution, and content performance. They do not need a 40-metric dashboard that updates in real time.
Cookieless measurement can deliver that without the consent-banner friction that suppresses your data and adds legal anxiety for teams without outside counsel on retainer. It is not a loophole. It is a different architecture — one where you collect less, store less, and own what you keep.
The analytics capability I built for this platform is now available as a product for other businesses to use on their own sites. I built it for myself first. That matters. I know where the tradeoffs are because I live with them every day.
If you want to see how it works, start at /privacy-analytics. Read the measurement model before you install anything on your site. Understand what you are collecting and why — that habit is worth more than any dashboard feature.