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How to directly access your PM data

Data · · 3 min read

This is less a tool choice than a habit change: the goal is that no product question waits two days for an analyst.

What “direct access” means for a product leader. You can answer these yourself, today, without a ticket:

  • What share of active accounts touched this feature last month?

  • Which step in the flow loses the most people?

  • Did retention move after the launch?

  • Who are the ten accounts most likely to churn, and what do they have in common?

If any of those needs someone else, you don’t have direct access — you have a dashboard.

The three layers, and you need all three:

  1. Product analytics — Amplitude, Mixpanel, PostHog. Event data: who clicked what, funnels, retention curves. Nearly all of them now have a natural-language query layer. Good for the first three questions above. Weak for anything joined with revenue, support, or sales data.

  2. The warehouse — BigQuery, Snowflake, Postgres, wherever the real tables live. This is where the fourth question gets answered, and where the retention simulator lives. It needs SQL, or a tool that writes SQL for you.

  3. The unstructured layer — support tickets, sales calls, NPS comments, reviews. No dashboard covers this; it’s where your interview synthesizer and status drafter get their raw material.

How to pick, or rather, how to get access:

  • Analytics: you usually don’t choose; you inherit. Learn what’s there deeply before asking for anything new. The tool is rarely the bottleneck; instrumentation is. Your first project is checking whether the events you care about are even being tracked.

  • Warehouse: ask for read-only access to the warehouse or a replica. This is the single most valuable request you can make in your first month at any company, and it’s usually granted if you ask for read-only. Then use your agentic coding tool to write the SQL — it’s good at it, and it’s the fastest way to learn the schema.

  • Unstructured: get an export path. A weekly dump of tickets to a folder is enough to start.

The test for any data tool:

  1. Can you ask a question in plain language and get a number with the query shown? If the query is hidden, you can’t check it, and you’ll eventually present a wrong number to leadership.

  2. Can you join across sources — usage plus revenue, usage plus support? Single-source tools give single-source answers.

  3. Can you save and rerun? A question you’ll ask monthly should be a saved query, not a repeated conversation.

  4. Can it push to you? A metric that changes should tell you, not wait to be looked at. This is the seed of the metric watcher.

Two cautions:

  • Natural-language-to-SQL is confidently wrong more often than people expect, especially on joins and date logic. Always look at the generated query, and sanity-check the number against something you know.

  • Read-only means read-only. Never ask for write access to production data as a PM. You don’t need it and it removes the safety net.

For you: the retention simulator and portfolio generator you already built are this layer, done well. The CV bullet is honest. The upgrade is making it standing rather than something you run — which is exactly item four’s “push to you” test, and Part 4 of your series.