New to product: Build foundations · Core
Learn the numbers product managers use
PMs use a small set of numbers to see whether a product works: how many people try it, how many stay and whether a change made a difference. You do not need to be a data scientist, but you do need to read numbers well.
About 3-5 daysEvergreenLast reviewed 9 November 2026
Who this applies to
- Skills it builds
- Data and measurement
- PM types
- All
- Product types
- All
- Starting points
- Exploring product management
- Ways of working
- All
- Experience
- Beginner (under 1 year)
- Size of organisation
- All
Steps
- Learn four ideas: a funnel (how many people complete each step), retention (how many come back), a north star metric (the one number that shows value) and an experiment (comparing two versions). Write one example of each from a product you know.
- Read the funnel analysis guide. Sketch a funnel for signing up to a service you use, mark where you think people drop off and say why.
- Read how a retention analysis is built. Describe how you would check whether people were still using a new feature a month later.
- Read about north star metrics. Write one for a product you know, then list two other measures that would warn you if chasing it caused harm.
- Read an introduction to controlled experiments. Note what makes a result trustworthy: a clear hypothesis, enough users, a long enough run and one change at a time.
- If you want to go further, spend an hour on the interactive SQL lessons in the sources. Understanding how to ask a database a question helps with every conversation with analysts.
- Take one chart or statistic from a news story and list the questions you would ask before trusting it.
Tool examples
- Google Docs
- Keep a one-page glossary of the terms with an example for each.
- Claude
- Ask it to explain one measure with a made-up example, then check the explanation against a source.
Definition of done
- One example of each of the four ideas
- A sketched funnel with guessed drop-offs
- A list of questions for one chart
Common pitfalls
- Chasing a single number without checking side effects
- Reading small changes in small samples as proof
- Skipping the basics to jump straight to dashboards
Do these first
Sources
- Funnel analysis: find drop-offs (Amplitude)(opens in a new tab)
- Build a retention analysis (Amplitude docs)(opens in a new tab)
- The North Star Playbook (Amplitude)(opens in a new tab)
- Trustworthy online controlled experiments (Kohavi, Tang and Xu, Cambridge University Press)(opens in a new tab)
- SQLBolt: interactive SQL lessons(opens in a new tab)