What Makes a Good Product Question
Curiosity is not the issue for most product teams. The challenge is shaping questions their data can answer. Here is how to frame them.
Mitzuo Blog
Product analytics thinking.
Practical writing on data questions, funnel analysis, and building an analytics habit without a dedicated analyst.
How to Read Funnel Drop-off Without a Data Analyst
A PM can read funnel drop-off in minutes, without a data analyst or a three-day wait. Here is how to find the biggest loss.
Retention vs Activation: Which Metric First?
Should product teams fix activation or retention first? One question, answered with two data pulls, points to the right metric.
Event Schemas That Age Well
On day one, most product event schemas seem clear. By month six, they may be unreadable. Early naming choices can prevent weeks of later cleanup.
Natural Language to SQL: Where It Works
Describe your question and receive a query. The promise is strong, but failure patterns are predictable. Knowing both helps you use the tool well.
The Hidden Cost of Analytics Request Queue
A data question taking one week to answer is more than a process issue. It affects decisions, creating a compounding cost most teams never measure.
Session Analysis Without a Session Variable
No session ID? You can still study sessions. Learn how time-based grouping reconstructs them from event data.
200 Dashboard Charts Still Cannot Answer Basic Questions
The issue is not chart volume. Charts answer the questions that existed when they were built, while product teams need answers to today's questions.
Minimal Event Taxonomy for Early-Stage Products
Tracking everything is unnecessary. Start with the ten events that show whether your product works, and learn where to begin.
What Product Managers Need from the Data Stack
Data stacks often serve engineers first, while product managers need fast answers to different questions on a different cadence. That mismatch creates friction.
Starting an Analytics Practice Without a Data Analyst
Your first data analyst is costly and may be premature. Most early-stage product teams can establish a solid analytics habit with the tools they already use.