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Learn Marketing Analytics

Measure which marketing works and turn numbers into budget decisions.

Free to start. Built from a single prompt. No credit card.

Marketing analytics is measuring marketing performance and using the results to decide where to spend. It combines tracking (tags, UTM parameters and conversion events in tools like Google Analytics 4), funnel and cohort analysis, unit economics like customer acquisition cost and lifetime value, and methods for separating cause from coincidence: attribution models, A/B tests, holdout experiments and marketing mix modeling. Spreadsheets and SQL do much of the work, and dashboards in tools like Looker Studio share it. Learnr builds a personalized marketing analytics course from a single prompt and teaches it in short lessons.

How to learn Marketing Analytics, step by step

Write a measurement plan first. List business goals, the KPI for each, the events that feed it and how they will be tracked. This keeps you from collecting everything and analyzing nothing, and it defines what "working" means before campaigns launch.
Get tracking right. Learn GA4 events and conversions, set a UTM naming convention for source, medium and campaign, and test every link. Most analysis problems trace back to inconsistent tags like "Facebook" versus "facebook".
Analyze funnels and cohorts. Build a funnel from visit to signup to purchase and find the largest drop. Then group customers by acquisition month and channel to compare retention, since a cheap channel with poor retention can cost more.
Learn the unit economics. Calculate CAC by channel, estimate lifetime value from margin and retention, and compute payback period. Practice in a spreadsheet with a sample dataset until the formulas are second nature.
Separate correlation from causation. Understand last-click and data-driven attribution, then learn why they still miss incrementality. Practice designing a holdout test or geo experiment, and learn when marketing mix modeling is worth it.
Practice analysis in short daily sets. Interpreting numbers is a skill that grows with repetition. Bite-sized Learnr lessons with interactive questions and a streak give you that steady practice between real reports.

What you'll learn

Set up consistent UTM tagging and conversion tracking
Analyze a funnel to find the biggest drop-off
Calculate CAC, LTV, ROAS and payback period
Compare attribution models and their blind spots
Design an A/B test or holdout to measure incremental impact

What's inside your Marketing Analytics course

A sample path Learnr builds for Marketing Analytics. Your real course adapts to your goal and level.

1. Marketing goals, KPIs and measurement plans
2. Tracking: tags, events, UTMs and GA4
3. Funnels, cohorts and retention
4. Unit economics: CAC, LTV, ROAS and payback
5. Attribution, incrementality and marketing mix modeling
6. Dashboards, reporting and turning insight into decisions

How long does it take to learn Marketing Analytics?

Plan on about 2 to 3 months at 4 to 6 hours a week for tracking, funnels, unit economics and testing. Adding SQL fluency or statistical modeling for MMM takes several months more.

What you need before you start

Spreadsheet skills and basic marketing knowledge. Introductory statistics helps with testing, and SQL becomes important once data outgrows spreadsheets.

Common mistakes to avoid

Trusting last-click attribution as the full truth, which undervalues channels that create demand earlier in the journey.
Calling an A/B test early when one variant pulls ahead. Decide the sample size and duration before starting, then wait.
Building dashboards full of metrics nobody acts on. Tie every chart to a decision someone will make.

How Learnr builds your course

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Tell Learnr you want to learn Marketing Analytics, or get as specific as you like.

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Learn and level up

Move through bite-sized lessons and interactive practice, earning XP and keeping your streak.

Marketing Analytics questions, answered

Do I need SQL for marketing analytics?

Not to start. Spreadsheets and analytics tools cover the basics. SQL becomes very useful once you work with exported or warehouse data, joining ad spend, web events and sales.

What is the difference between attribution and incrementality?

Attribution assigns credit for conversions to touchpoints. Incrementality measures how many conversions would not have happened without the marketing, usually through controlled experiments.