Web Data Analyst
Turn raw clicks and orders into answers: GA4, SQL, Python and reports people act on.
- Level
- Intermediate
- Duration
- ~33 hours
- Live
- 30/94
- Free
- 1
No credit card required. No marketing experience needed.
Program map
30
30 of 94 workouts live today
One bar per module, in program order.
- Has free workouts
- Pro
- Coming soon
From the fundamentals to your own work.
Shared foundations, a focused specialty, and projects that bring your practice together.
1The Marketing FunnelStart here1 freeThe journey that turns a stranger into a customer, and a customer into a loyal fan, plus the metrics that measure each stage.6 workouts, 35 min
- 1What is a marketing funnel?5 min5 minFree
- 2Awareness: meeting someone who has never heard of you6 min6 minPro
- 3Consideration: the "why you?" question6 min6 minPro
- 4Conversion: from click to sale6 min6 minPro
- 5Loyalty: the hidden bottom of the funnel5 min5 minPro
- 6A metric for every stage: CPM, CTR, CVR, CPA, ROAS7 min7 minPro
2Marketing Metrics and KPIsKnowing which numbers really matter: choosing KPIs, unit economics, profitability and setting realistic targets.6 workouts, 37 min
- 1Metric or KPI? Numbers tied to a goal6 min6 minPro
- 2CAC, LTV and payback period7 min7 minPro
- 3ROAS is not enough: profit margin and break-even ROAS7 min7 minPro
- 4The North Star metric and the metric tree6 min6 minPro
- 5Vanity metrics: the likes and followers trap5 min5 minPro
- 6Setting realistic targets: past data, seasonality and budget6 min6 minPro
3The Digital Channel MapSearch, social media, marketplaces, email and messaging: what each channel is good for and where your customers actually spend their time.6 workouts, 34 min
- 1Paid, owned and earned media5 min5 minPro
- 2Search: capturing intent (Google, YouTube, AI assistants)6 min6 minPro
- 3Social media: creating demand6 min6 minPro
- 4Marketplaces: where many shoppers start (Amazon, Etsy, eBay)6 min6 minPro
- 5Email, SMS and WhatsApp: reaching your own audience5 min5 minPro
- 6Choosing channels on a tight budget6 min6 minPro
4Google Analytics 4 BasicsComing soonUnderstanding GA4's event-based model, reading its reports, and tagging and interpreting traffic sources correctly with UTMs.6 workouts, 37 min
- 1The event-based model: everything is an event6 min6 minComing soon
- 2GA4 property, data stream and core settings6 min6 minComing soon
- 3Traffic sources, UTMs and channel groups7 min7 minComing soon
- 4Standard reports and Explorations6 min6 minComing soon
- 5Key events and e-commerce events6 min6 minComing soon
- 6Interpreting the numbers: why is "direct" so high?6 min6 minComing soon
Portfolio project: A UTM standard and a GA4 channel analysis. A UTM naming standard, a UTM builder sheet and a channel performance report.
5Google Tag ManagerComing soonMeasurement without waiting on a developer for every change: tags, triggers, variables, the data layer and testing in Preview mode.6 workouts, 36 min
- 1Tags, triggers, variables6 min6 minComing soon
- 2The data layer: a shared language with developers7 min7 minComing soon
- 3Sending GA4 events with GTM6 min6 minComing soon
- 4Setting up Google Ads, Meta and TikTok tags6 min6 minComing soon
- 5Preview mode and debugging6 min6 minComing soon
- 6Container organization, naming and version control5 min5 minComing soon
Portfolio project: An e-commerce tagging setup. A dataLayer spec, a GTM tag and trigger table and a testing checklist.
6Spreadsheets for AnalystsComing soonGoing beyond basic formulas: cleaning messy exports, joining tables with lookups, QUERY and array formulas, and building sheets other people can trust.6 workouts, 35 min
- 1Cleaning messy exports: trim, split, dedupe, dates6 min6 minComing soon
- 2XLOOKUP and INDEX/MATCH: joining two tables6 min6 minComing soon
- 3Pivot tables in depth: grouping and calculated fields6 min6 minComing soon
- 4QUERY and ARRAYFORMULA: SQL-style work in Sheets7 min7 minComing soon
- 5Importing data and keeping sheets fresh5 min5 minComing soon
- 6Sheets others can trust: structure, checks, documentation5 min5 minComing soon
Portfolio project: Build a clean performance workbook. A workbook with raw, clean and summary tabs, a documented method and three checks showing the totals match the sources.
7Marketing Data Analysis: From Spreadsheets to CohortsComing soonAnalyzing data yourself with Google Sheets, pivot tables and basic SQL, and understanding user behavior with funnel and cohort analysis.6 workouts, 36 min
- 1Pivot tables and core formulas in Google Sheets6 min6 minComing soon
- 2SQL for marketers: SELECT, WHERE, GROUP BY7 min7 minComing soon
- 3Querying GA4 data in BigQuery6 min6 minComing soon
- 4Funnel analysis: where do users drop off?6 min6 minComing soon
- 5Cohort analysis and the retention curve6 min6 minComing soon
- 6Telling stories with data5 min5 minComing soon
Portfolio project: A cohort and funnel analysis report. Funnel and cohort tables (Sheets or SQL queries), a retention chart and an analysis report with 3 recommendations.
8SQL for Marketing DataComing soonThe SQL a marketing analyst uses every week: joins, CTEs, window functions and date logic, applied to campaigns, orders and customers.6 workouts, 38 min
- 1Joins: connecting campaigns, orders and customers7 min7 minComing soon
- 2Dates and time windows: weeks, months, rolling periods6 min6 minComing soon
- 3CTEs and subqueries: queries people can read6 min6 minComing soon
- 4Window functions: running totals, ranks and first touch7 min7 minComing soon
- 5Funnel and cohort queries7 min7 minComing soon
- 6Checking your work and keeping queries cheap5 min5 minComing soon
Portfolio project: Answer five business questions with SQL. Five documented queries with their results, a one-sentence answer for each and the assumptions behind it.
9GA4 and BigQuery ExportComing soonWorking with raw GA4 events: linking the export, understanding the nested tables, rebuilding sessions and reconciling with what the GA4 interface shows.6 workouts, 38 min
- 1Linking GA4 to BigQuery: setup, daily or streaming, costs6 min6 minComing soon
- 2The events table: one row per event, nested parameters7 min7 minComing soon
- 3UNNEST: pulling values out of event_params7 min7 minComing soon
- 4Rebuilding sessions and traffic sources7 min7 minComing soon
- 5E-commerce events and revenue in BigQuery6 min6 minComing soon
- 6Why BigQuery and the GA4 interface differ5 min5 minComing soon
Portfolio project: Model sessions and revenue from raw GA4 data. A saved set of queries that outputs sessions, orders and revenue by source/medium and date, with a short note on the differences.
10Python Basics for Marketing AnalysisComing soonEnough Python to load, clean and analyze marketing data with pandas, chart it, and automate a report you would otherwise rebuild by hand every week.6 workouts, 38 min
- 1Notebooks and your first analysis: cells, variables, libraries6 min6 minComing soon
- 2Loading and cleaning data with pandas7 min7 minComing soon
- 3Grouping, merging and pivoting7 min7 minComing soon
- 4Charts you can explain: matplotlib and seaborn6 min6 minComing soon
- 5Reading from CSV files and BigQuery6 min6 minComing soon
- 6Automating a weekly report, and knowing when not to6 min6 minComing soon
Portfolio project: Build a reusable campaign analysis notebook. A notebook with text explanations, three charts and a findings summary, plus a short README for running it on new data.
11Reporting with Looker StudioComing soonTurning data into a dashboard that drives decisions: data sources, choosing charts, calculated fields and presenting reports to managers.5 workouts, 30 min
- 1A good report: the question first, then the chart6 min6 minComing soon
- 2Connecting data sources: GA4, Google Ads, Sheets6 min6 minComing soon
- 3Choosing the right chart5 min5 minComing soon
- 4Calculated fields and data blending7 min7 minComing soon
- 5Presenting a report: writing insights and recommendations6 min6 minComing soon
Portfolio project: A multi-channel performance dashboard. A shareable Looker Studio dashboard (or a design mockup) and a weekly insights summary.
12Attribution and Measurement StrategyComing soonWhich channel drove the sale? Attribution models, double counting across platforms, attribution windows and the measurement triangle.5 workouts, 31 min
- 1What is attribution, and why does every channel claim the sale?6 min6 minComing soon
- 2Last-click and data-driven attribution6 min6 minComing soon
- 3Why do platform reports add up to more than the total?6 min6 minComing soon
- 4View-through conversions and attribution windows6 min6 minComing soon
- 5The measurement triangle: attribution, incrementality, MMM7 min7 minComing soon
Portfolio project: An attribution gap report. A cross-source comparison table, explanations for each gap and a one-page measurement framework.
13Experiment Design and A/B TestingComing soonTest instead of guessing: writing hypotheses, prioritizing experiments, calculating sample size and reading the result correctly.6 workouts, 36 min
- 1A good hypothesis: because, if, then5 min5 minComing soon
- 2Prioritizing experiments: ICE and PIE6 min6 minComing soon
- 3Sample size and test duration7 min7 minComing soon
- 4Statistical significance: the p-value in plain English7 min7 minComing soon
- 5Common mistakes: stopping early, multiple testing, the novelty effect6 min6 minComing soon
- 6Experimentation culture and the experiment log5 min5 minComing soon
Portfolio project: A quarterly experiment roadmap. A prioritized experiment list, a sample size calculation and a complete experiment doc (hypothesis, metric, duration, decision rule).
14Data Storytelling and Decision-Ready ReportsComing soonTurning analysis into decisions: finding the one point that matters, choosing and annotating charts, structuring a story and showing uncertainty honestly.6 workouts, 34 min
- 1Start with the decision, not the data5 min5 minComing soon
- 2One chart, one message: choosing and annotating6 min6 minComing soon
- 3Story structure: situation, finding, action6 min6 minComing soon
- 4Misleading charts and honest uncertainty6 min6 minComing soon
- 5Dashboards, reports and decks: which one to build5 min5 minComing soon
- 6Presenting to stakeholders and handling questions6 min6 minComing soon
Portfolio project: Write a findings memo and a readout. A one-page memo, a five-slide readout and an appendix of supporting charts.
15AI in MarketingMake AI your teammate for content, ad creative, analysis and research, and understand how AI search is changing marketing.6 workouts, 35 min
- 1Writing good prompts: role, context, examples, format6 min6 minPro
- 2Creating content with AI: speed, brand voice and control6 min6 minPro
- 3AI for ad images and video creative6 min6 minPro
- 4AI for data analysis: from spreadsheet to insight6 min6 minPro
- 5AI search: how ChatGPT, Gemini and AI Overviews are changing traffic6 min6 minPro
- 6Risks: hallucinations, copyright, privacy and brand safety5 min5 minPro
16Portfolio, Resume and InterviewsProve what you have learned to a recruiter: a project portfolio, an ATS-friendly resume, a LinkedIn profile and case interview practice.6 workouts, 35 min
- 1Portfolio: turning your projects into case studies6 min6 minPro
- 2A marketing resume: write results, not duties6 min6 minPro
- 3Setting up your LinkedIn profile for recruiters5 min5 minPro
- 4The case interview: "How would you spend this budget?"7 min7 minPro
- 5Take-home assignments: structure and presentation6 min6 minPro
- 6Job offers: salary research and negotiation5 min5 minPro
30 of 94 workouts in this program are live today, across 16 modules. Workouts take 5 to 7 minutes; projects need a longer, focused session.
What you'll be able to practice
You collect clean data with GA4 and Google Tag Manager, then go deeper than the interface: spreadsheets for analysts, SQL, the GA4 BigQuery export and Python with pandas. You build Looker Studio reports, learn what attribution can and cannot tell you, read A/B tests carefully and present findings so a team can make a decision.
Roles it prepares you for
Job titles you'll see in listings for this work. Titles differ from company to company, so read the duties in the listing, not just the title.
- Web Data Analyst
- Digital Analyst
- Data Analyst
- Marketing Data Analyst
- Web Analytics Specialist
- Analytics Specialist
What the work looks like day to day, pay by level and country, and how the role grows: Data Analyst
- Set up GA4 and Google Tag Manager for an online store and check that the data they collect is accurate.
- Clean and join marketing exports in spreadsheets, then repeat the work in SQL.
- Query the GA4 BigQuery export to rebuild sessions, sources and revenue, and explain gaps with the GA4 interface.
- Use Python and pandas to analyze campaign data and automate a weekly report.
- Read an A/B test result and explain what it does and does not prove.
- Present findings as a one-page memo with a clear recommendation.
Work you can explain.
A portfolio project at the end of every module.
Example portfolio direction
Map a brand's funnel
Using the ad and sales data of a fictional brand, map every stage of its funnel, pick one metric for each stage and find the stage where the most customers drop off.
What you hand in: A one-page funnel map: stages, metrics, the weakest stage and two improvement ideas.
How the project is judged
- Accuracy
- Diagnosis
- Ideas
- Clarity
A clear place to begin.
Built for complete beginners and career switchers. You don't need a client account or your own ad budget: you work with realistic, fictional-brand scenarios.
Start with one decision.
Your first workout is ready when you are.
No credit card required. No marketing experience needed.
