Article
I built my own analytics with the help of AI – cookie-free and GDPR-compliant
Not long ago, I realised I wanted a better understanding of my blog’s traffic.
I like clean and accurate data. But traditional analytics tools like Google Analytics come with serious downsides: inaccurate numbers (due to blocked consent requests and various tracking blockers), the need for a cookie banner, and questionable transparency around privacy.
That is why I decided to build my own analytics – with pure, unfiltered data and full respect for the privacy of my visitors. And since we are living in 2025, I built it with the help of generative AI.
When it comes to programming, I have always considered myself an eternal beginner, ever since I started with web development at the age of 12. But AI has opened up skills and opportunities for me that I never imagined I would have. I have already written here on my blog about how AI helps me improve my coding skills, explaining its steps and decisions along the way. Thanks to that, my horizons have expanded far beyond what I thought possible. One of the results is my own custom-built analytics tool.
Defining the Goals and First Prompts
When building a project like this today, you really need to have a clear idea of what you want it to do and why. Just saying "I want my own analytics" is not enough.
So we started by defining exactly what I wanted to measure: daily traffic, traffic sources, purchases of my premium articles, and a deeper analysis of visitor types (humans vs. suspicious activity vs. bots).
At first, creating the initial tables and charts seemed easy. But it did not take long before the first real challenges emerged.
The issues I had to solve
The first SQL queries we used were slow and inefficient. They dragged the whole website down. We gradually tuned them, replaced wasteful LIKE comparisons with exact matches, and optimised the logic to only process the data we really needed – and suddenly, it started to fly.
Join the Library
Full access to my thoughts, personal stories, findings, and what I learn from the people I meet.
Join the Library · €29.99 per yearGet the full article by email and feel free to reply if you want to discuss it further.
Summary
Common questions on this article's topic
Why is Google Analytics inaccurate?
Is it possible to build web analytics without cookies?
What percentage of web traffic comes from bots?
Can someone with limited programming experience build custom analytics using AI?
How does privacy-first analytics work without tracking individuals?
What were the biggest technical challenges in building custom analytics?
Related articles
This is a serious issue, and it is high time we start acting responsibly.
Sixteen of twenty-seven sources did not check out. They did not exist, led to dead links, or claimed something that was not in them. The report came from one of the largest consulting firms in the world. It was meant to be about cybersecurity. They pulled it.
Seventy per cent. That is where the first AI output begins, even when you give it the full company context and the best examples from the past. We are talking about the kind of output that cannot be defined programmatically. It is more complex. Often it is creative work. On one repeated type of output I reached eighty per cent within a week. Every further percentage point is harder than the one before.
More articles
For a long time we treated the internet as the main road. The place where work and relationships happen. Yet most of what we see on it today is, or soon will be, AI-generated: text, images, profiles and comments. The internet is turning into an online game full of bots, where you cannot be sure that a human is on the other side of anything. So I ask: was the online world the main road, or only a temporary detour that part of us will return from, back offline?
A few days ago I interviewed a senior marketer. An experienced man, years of practice. I asked him about AI. He said he barely uses it. He had one bad experience with the output and decided he was too senior for it to add value when it is not perfect. I know the other side too: professionals who automate everything that can be automated.
Europe does not have the capacity to face a full-scale, mass drone war of the kind we see in Ukraine. Three dependencies weaken it: China supplies the physical material for defence systems, the United States supplies capabilities Europe does not have, and twenty-seven states cannot agree how fast, or who pays. Rearmament plans exist, but they are being carried out slowly.
AI produces the graphic, the newsletter and the product page faster than a person. What is left for the one who used to do it is the judgement, knowing whether the output is good. But most people have worse judgement than AI. And whoever cannot judge quality cannot delegate either. How do you tell whether yours is the judgement a company relies on, or the kind it can replace?
In April, in the first part of this series, I wrote about an AI prediction system I had started building on my own machine. At the time the software was a few hours old and the prediction record was empty. The record since then has shown one thing: the system does not yet understand the market it is being asked to forecast. It can pull macro context, book value, earnings. But it cannot put those together into something that helps it understand the price.
Prague, 13 May 2026. On my way to work I started thinking about something that stayed with me for days. If most routine work on a computer disappears in the next ten years, and a large share of repetitive manual work disappears with it, what happens to the flow of money? Who pays whom for what? Which economic layers will exist, how large will they be, and what relationships will run between them? This is the six-layer map I sketched as an answer.
I am building an AI system to predict the S&P 500. It runs on my own machine, uses free public data (yfinance, FRED, the Shiller dataset), and grades every forecast against reality. This series documents the build itself: the decisions, the methodology, the mistakes. What I will eventually share from the running system is a separate question, and an honest one.
Yesterday I could not tear myself away from the computer. When I lifted my head, it was half past eight in the evening. I had been sitting alone upstairs for about three hours.
Will AI take my job? A certified Google trainer told me in June 2024 that my profession would cease to exist. Twenty-two months later, my job title has not changed, but ninety percent of what I do during the day is different. I have delegated more of my thinking to AI agents than I thought possible. I am not afraid. This is why, and what it means for anyone asking the same question.
Four days in Catalonia. No computer, no AI, almost no social media. I bought this notebook so that I could write down what I would think about, and what I would come across and learn on the trip.
