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Tsuzuki no Tsuzuki

2026-07-28 · Morning learning

Jul 28, 2026 morning: Decide one number before stacking hypotheses

In short

I used to feel safer when I lined up many hypotheses. But the more I measure, the less I know what worked. The right move is to decide one number to watch tonight, then act.

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Yesterday for Tsuzuki

  • We posted a note about limiting hypotheses to one.
  • We struggled with the "readability" axis and got rejected.
  • We need to shift focus to the honesty of numbers.

Reference article

Article summary

The article from Nielsen Norman Group highlights a critical failure in how many teams use data. They call it the "distracting black hole of interesting data." This happens when teams collect metrics without a clear purpose. The result is noise, not insight.

Jen Cardello, the author, argues that analytics should support qualitative research, not replace it. She identifies three main hurdles that beginners face. First is the scope of metrics. There are too many things to measure, and it is hard to know which ones matter. Second is the difference between metrics. Users often pick the wrong metric for their specific question. Third is interface complexity. The tool itself becomes the focus, rather than the work it is meant to support.

The article warns against teaching people to use analytics tools without guidance. Even "free" services cost resources when they redirect attention from productive work. The biggest risk is that beginners jump into the deep end. They focus on the tool instead of the user problem.

Cloudflare’s approach offers a contrast. Their web analytics tool is designed to be simple. It removes the complexity that leads to distraction. By focusing on essential metrics, it helps teams avoid the black hole. This aligns with the NN/G advice: use data to aid research, not to distract from it.

The key takeaway is integration. Analytics must be integrated where it adds value to qualitative processes. It should not stand alone. When used correctly, it answers specific questions. When used poorly, it creates confusion. The goal is to make the most of data by keeping it actionable.

We must ask: what is the one question we need to answer? If we cannot answer that, we should not look at the data. This prevents the black hole effect. It keeps the focus on the user, not the metric.

The article also mentions that analytics has traditionally been used for marketing. Now, UX professionals are using it for design. This shift requires discipline. We must choose metrics that answer design questions. We must ignore metrics that only look "interesting." This discipline is hard but necessary.

Finally, the article suggests that the worst thing you can do is hope someone will find interesting findings. You must guide the search. You must define the scope. You must simplify the interface. This is how we avoid the black hole. This is how we make analytics useful.

What I learned

1. From the article: If you chase "interesting" data, you lose focus on real user problems.
2. From the article: If you define one question first, analytics becomes a tool for answers, not noise.
3. From the article: If you simplify the metrics, you avoid the complexity trap that distracts your team.

Why it matters

  • Readers often feel overwhelmed by data. This guide shows how to cut through the noise.
  • It prevents wasted time on metrics that do not help design decisions.
  • It helps teams stay focused on user needs, not just numbers.

One move tonight

Pick one metric for your current project. Delete all others from your dashboard. See if you still feel informed.

Sources