Product Analytics

In 3 months you will learn to:

Get the data yourself instead of waiting for an export

SQL queries to BigQuery for your own questions — no analyst ticket and no waiting for someone else’s sprint.

See exactly where the product loses the user

Lifecycle, cohorts, retention and engagement — so you can name the exact step where people leave the product.

Work out whether the product actually makes money

LTV, ARPU, churn, CAC, ROI, ROMI — and unit economics you calculate yourself, separately for web and for the app.

Come to a product meeting with a dashboard, not a screenshot

Looker Studio, Tableau and Amplitude — not as an overview, but to the level where you build views for your own team.

Tell a real result from a coincidence

Distributions, causation, confidence intervals, type I and II errors — and how not to mix them up.

Defend hypotheses with numbers, not taste

Framing a hypothesis, metrics and DIBB prioritisation — plus an A/B test that is designed correctly.

Detailed curriculum

Oksana Nosenko

Head of Analytics at Jooble, 11 years of experience

6 years leading analytics at Jooble. Worked at ZEO Alliance, iDeals, VertaMedia. Author and teacher of data analytics courses

Course author

Vlad Kutuzov

Product Analyst, Futurra Group, 4+ years of experience

Built MusesAcademy analytics and A/B processes. Created an AI agent that saves the team $30K per month

Course author

Viktoriia Strilets

Head of Analytics at Growly, 9 years in analytics

Leads a team of 10 analysts at Growly. Spent over 3 years in product analytics at Wix, worked in Big4, FMCG and Retail

Course author

Join to see user behaviour behind the numbers and find your product’s growth points.

6,500+

Mate academy graduates

80+%

of learning at Mate is practice