Own the measurement
A Marketing Analyst defines useful KPIs, implements tracking and checks that reported leads represent genuine enquiries.
AI5 ACADEMY · MARKETING ANALYTICS LAB · SEPTEMBER 2026
AI Marketing Analyst Professional Program
Learn GA4, GTM, Google Data Studio, Power BI, SQL, CRM Analytics and AI to measure marketing from click to customer and revenue.
For career starters and working marketing professionals.
12 WeeksStructured live program
36 Live Sessions3 sessions each week
10 Portfolio BuildsIncluding final capstone
No Coding BackgroundSQL taught from the basics
THE BUSINESS QUESTION
What is actually generating customers and revenue?
Learn to explain where the marketing money goes, what is wrong with the measurement and what the business should do next.
Connect the evidence
Combine campaign, website, CRM and sales data. Separate cheap leads from qualified prospects and paying customers.
Make a checked recommendation
AI speeds up analysis and reporting. You verify the numbers, explain uncertainty and recommend the next action.
Measure → Track → Validate → Combine → Analyse → Visualise → Explain → Recommend → Automate
THE COMPLETE MEASUREMENT WORKFLOW
Follow the customer. Check every connection.
Campaign
Spend, channels and UTMs
Website
Visits and interactions
GTM
Tags, triggers and events
GA4
Acquisition and journeys
CRM
Genuine, qualified leads
Sale
Verified sales outcomes
Revenue
Value tied to customers
Data Studio / Power BI
Joined, checked dashboards
AI analysis
Questions and explanations
Business decision
Budget and next actions
A learning workflow: connect records with appropriate identifiers and consent. GA4 does not automatically send every visitor into a CRM.
YOUR WORKING TOOLKIT
Learn the tools together, through marketing work.
Marketing and data platforms
Google Ads · Meta Ads Manager · Google Search Console · CRM datasets · Google Ads Data Manager concepts
One reporting automation tool
Make supports one supervised reporting workflow. Measurement and analytics remain the centre of the program.
Both dashboard platforms are mandatory: Data Studio for interactive marketing reporting; Power BI for deeper combined marketing, CRM and sales datasets.
Use training access and realistic exports where direct connectors are unavailable. Bring a laptop; confirm Power BI setup, account access, optional paid AI features, connectors and automation credits with the counsellor. Commercial advertising spend is not required.
12 WEEKS · EXACTLY 36 LIVE SESSIONS
A working Marketing Analytics lab.
Each week: three instructor-led sessions of 60–90 minutes. Approximately 36–54 live hours, with assignments between selected sessions. Understand → Implement → Test → Analyse → Find Problem → Recommend Action.
WEEK 1Marketing measurement foundationsSessions 1–3
SESSION 1
Role of the Modern Marketing Analyst
- Analyst responsibilities
- Marketing Analyst vs Digital Marketer, Performance Marketer and Data Analyst
- measurement lifecycle
- business questions vs vanity metrics
SESSION 2
Marketing Metrics & Business KPIs
- Calculate impressions, reach, CTR, CPC, CPM, conversion rate, CPL, CPA, CAC, ROAS, revenue, revenue per lead and lead-to-sale rate
- define denominators and conversion actions
SESSION 3
Measurement Planning
- Build KPI framework, measurement plan, event plan, conversion plan, UTM structure and campaign naming convention
AI + verification: Ask AI to review the measurement plan; check every metric definition and calculation.
Weekly output: Marketing Measurement Plan
WEEK 2Excel & Google Sheets for marketing analysisSessions 4–6
SESSION 4
Cleaning Marketing Data
- Repair missing values, inconsistent campaign names, duplicates, dates and text
- validate row counts and totals
SESSION 5
Marketing Analysis with Spreadsheets
- SUMIFS, COUNTIFS, XLOOKUP, IF, IFERROR, text/date functions and PivotTables using campaign exports
SESSION 6
Campaign Performance Lab
- Identify strongest and weakest campaigns, expensive leads, poor conversion rates and high-performing channels
AI + verification: Draft formulas with AI, then test sample rows and compare totals manually.
Weekly output: Campaign Performance Workbook
WEEK 3Google Analytics 4Sessions 7–9
SESSION 7
GA4 Architecture
- Users, sessions, events, parameters, traffic acquisition vs user acquisition, engagement, landing pages and key events
- advertising conversion concepts
SESSION 8
GA4 Marketing Analysis
- Source, medium, campaign, channels, engagement and campaign traffic
- Search Console queries, pages, clicks, impressions, CTR and average position
- compare organic landing-page performance with GA4
SESSION 9
GA4 Explorations
- Build segments, funnels, path analysis, comparisons and custom analysis
- explain why GA4 and Search Console totals differ
AI + verification: Use AI to suggest analytical questions and check answers against GA4 exports.
Weekly output: GA4 Marketing Performance Analysis
WEEK 4Google Tag ManagerSessions 10–12
SESSION 10
GTM Fundamentals
- Containers, tags, triggers, variables, GA4 integration, Preview mode and Tag Assistant in a training website
SESSION 11
Marketing Event Tracking
- Implement CTA click, successful form submission, phone click, WhatsApp click, demo booking, thank-you page and outbound click
- distinguish intent clicks from accepted leads
SESSION 12
Advanced Tracking & Data Layer Fundamentals
- Custom events, event parameters, data layer concepts, campaign tracking, event naming and conversion architecture
- no advanced server-side GTM engineering
AI + verification: Review AI-suggested triggers in Preview mode and verify the resulting events.
Weekly output: Working GTM Measurement Implementation
WEEK 5Tracking QA & advanced GA4Sessions 13–15
SESSION 13
Tracking Debugging
- Diagnose duplicate and missing events, incorrect triggers, failed-form tracking, button clicks counted as leads, page reload issues and incorrect conversions
SESSION 14
GA4 vs CRM Reconciliation
- Investigate excess GA4 form submissions against genuine CRM leads
- compare date ranges, time zones, duplicates, validation, popup forms, demo bookings and event firing rules
SESSION 15
Analytics Audit Lab
- Audit a simulated education website
- record evidence, reproduce errors, propose fixes and retest
- distinguish event counts, users, key events and CRM records
AI + verification: Use AI to propose possible causes; accept a cause only after a reproducible test.
Weekly output: Marketing Measurement Audit Report
WEEK 6Google Ads & Meta analyticsSessions 16–18
SESSION 16
Google Ads Analytics
- Impressions, clicks, CTR, CPC, conversions, CPA, conversion value, ROAS, campaigns, ad groups and search terms
- Google Ads Data Manager concepts
SESSION 17
Meta Advertising Analytics
- Reach, impressions, frequency, CPM, CTR, CPC, leads, purchases, cost per result and ROAS
- compare attribution windows and platform definitions
SESSION 18
Cross-Channel Campaign Analysis
- Compare Google Ads, Meta, Organic, Direct and Referral
- recommend budget/action changes
- first-party data and qualified-lead/offline conversion concepts
AI + verification: Compare AI campaign explanations with spend, conversion definitions and revenue evidence.
Weekly output: Cross-Channel Marketing Performance Report
WEEK 7Google Data Studio (formerly Looker Studio)Sessions 19–21
SESSION 19
Dashboard Fundamentals
- Connectors, dimensions, metrics, charts, scorecards, filters and date controls
SESSION 20
Marketing Dashboard Development
- Connect available GA4 training access, Google Sheets and supplied advertising datasets
- build acquisition, campaign and landing-page views
SESSION 21
Management Dashboard
- Calculated fields, comparisons, blended data concepts, executive KPIs and dashboard storytelling
- validate join grain and totals
AI + verification: Draft dashboard commentary with AI; verify filters, date ranges and calculated fields.
Weekly output: Interactive Marketing Dashboard
WEEK 8CRM & funnel analyticsSessions 22–24
SESSION 22
Marketing-to-Sales Funnel
- Model impression → click → visit → lead → qualified lead → demo → sale → revenue
- first-party data, CRM outcomes, offline sales, privacy and consent fundamentals
SESSION 23
Lead Quality Analytics
- Calculate lead-to-qualified, qualified-to-demo, demo-to-sale and lead-to-sale rates
- CPL, qualified CPL, CAC and revenue per lead
SESSION 24
Channel Revenue Analysis
- Combine marketing, CRM and sales
- identify channels producing most leads, best lead quality, sales and revenue
- map offline conversion flow, enhanced conversion concepts and Google Ads Data Manager without API development
AI + verification: Check AI segment comparisons against source records; remove personal data from training prompts.
Weekly output: Marketing Funnel & Revenue Report
WEEK 9SQL for Marketing AnalystsSessions 25–27
SESSION 25
SQL Foundations
- SELECT, WHERE, ORDER BY, LIMIT and basic filtering taught from the beginning
SESSION 26
Marketing Aggregation
- COUNT, SUM, AVG, GROUP BY, CASE WHEN and date grouping using marketing business questions
SESSION 27
Marketing Data Joins
- Join campaign, lead and customer/sales tables
- check one-to-many relationships, duplicate rows and totals
- answer channel and revenue questions
AI + verification: Generate draft SQL with AI, run it and test row counts and sums against spreadsheets.
Weekly output: Marketing SQL Mini Project
WEEK 10Power BI for marketing & CRM analysisSessions 28–30
SESSION 28
Power BI Fundamentals
- Data import, Power Query, cleaning, relationships and basic data modelling for combined business datasets
SESSION 29
Marketing + CRM Dashboard
- Combine campaign, leads, sales and revenue tables
- define basic measures and check model relationships
SESSION 30
Management BI Dashboard
- Build decision-focused marketing and revenue reporting, filters and funnel comparisons
- validate totals and explain management actions
AI + verification: Use AI for model troubleshooting and commentary, checking measures against source totals.
Weekly output: Marketing & Revenue Power BI Dashboard
WEEK 11Attribution, experimentation & forecastingSessions 31–33
SESSION 31
Marketing Attribution
- First-click and last-click concepts, data-driven attribution, direct traffic, assisted journeys and attribution limits
- distinguish conceptual models from options currently available in GA4
SESSION 32
A/B Testing
- Hypothesis, control, variant, primary metric, sample-size concept, noise, false winners and business impact
- practical statistics
SESSION 33
Budget & Forecasting Lab
- Forecast leads, estimate CPA/CAC, model revenue, compare scenarios and recommend budget allocation with assumptions and sensitivity checks
AI + verification: Challenge AI forecasts using alternative assumptions; do not confuse correlation with causation.
Weekly output: Marketing Budget Recommendation
WEEK 12AI, automation & capstoneSessions 34–36
SESSION 34
AI for Marketing Analysts
- ChatGPT/Gemini dataset questions, SQL and formula help, anomaly explanations, campaign comparisons, hypotheses, dashboard commentary, summaries, scenarios and tracking-plan review
- AI output → verification → analyst judgment
SESSION 35
Marketing Reporting Automation
- Build one Make workflow: marketing dataset → processing → AI analysis → management summary
- handle missing/repeated data and human review. Marketing Analytics in the Agentic AI Era: conversational analytics, anomaly detection, autonomous systems, governance and the analyst’s changing role
SESSION 36
Capstone Presentation
- Present cleaned data, tracking audit, campaign/CRM analysis, SQL, Data Studio and Power BI dashboards, attribution review, checked AI findings and budget recommendations
- defend conclusions and limitations
AI + verification: Present the evidence behind each AI-assisted recommendation and retain human approval for actions.
Weekly output: Final Marketing Analyst Capstone
HANDS-ON LABS
Find the fault. Prove the fix.
The “too many leads” audit
GA4 shows more submissions than CRM leads. Test duplicate events, validation failures, popup forms, demos and page reloads before proposing a fix.
The cheap-lead trap
Compare Google Ads, Meta, Organic, Direct and Referral on qualified leads, sales and revenue—not just CPL.
The offline conversion loop
Map ad click → website → lead → CRM → qualified lead → sale → revenue → advertising measurement. Cover first-party data, consent and offline outcomes without API development.
10 PORTFOLIO BUILDS
Evidence of what you can do.
Build progressively during the program. The final capstone connects the earlier work into one business case; it is included in the ten builds.
Marketing Measurement Plan
KPI definitions, event plan, conversion rules, UTMs and campaign naming.
Campaign Performance Workbook
Cleaned data, formulas, PivotTables and verified campaign comparisons.
GTM Tracking Implementation
Working events on a training website with Preview and Tag Assistant evidence.
GA4 Measurement Audit
Reproduce tracking faults and reconcile events with genuine CRM leads.
Cross-Channel Campaign Analysis
Compare paid and unpaid channels with consistent metrics and attribution notes.
Data Studio Marketing Dashboard
Interactive acquisition, campaign and landing-page reporting.
CRM/Funnel Analysis
Connect lead quality, demos, sales and revenue by channel.
Marketing SQL Mini Project
Queries, aggregations and checked joins across campaigns, leads and sales.
Power BI Marketing/Revenue Dashboard
Combined business model and decision-focused management reporting.
Final Marketing Analyst Capstone
A connected business case with source checks, dashboards and defended budget actions.
FINAL CAPSTONE
Twelve campaigns. One management decision.
Work with a simulated business across Google Ads, Meta, Organic, Direct and Referral. No confidential company data is promised or required.
₹10 lakhAd spend
12Campaigns
5,000Leads
1,000Qualified
300Demos
110Sales
₹42 lakhTotal revenue
Build the evidence
Clean data, validate measurement, identify tracking faults and analyse GA4 and campaigns. Query the records with SQL, combine CRM and marketing data, then build Data Studio and Power BI reports.
Explain the business
Calculate CPL, CPA, CAC and ROAS with stated definitions. Compare lead quality, find funnel leakage, review attribution and recommend budget changes. Use AI assistance, verify its findings and present your evidence to management.
Show your working
Submit source totals, tracking QA evidence, SQL queries, dashboard links, an AI verification log and a management presentation. Assessment checks accuracy, measurement reasoning, dashboard clarity and the evidence behind your recommendation.
ROAS check: Calculate paid-attributed revenue against matching ad spend. Do not label total revenue across all channels divided by ad spend as platform ROAS.
Download simulated training dataset ↓CAREER DIRECTIONS
Become the person who can explain the numbers.
Build toward entry and working-level marketing analytics responsibilities. Role suitability depends on your previous experience, demonstrated work and employer requirements.
WHO SHOULD JOIN
Career starters + working professionals
- Aspiring Marketing Analysts
- Digital Marketers and Performance Marketers
- Marketing Executives
- MBA/BBA Marketing students and marketing graduates
- Agency professionals
- CRM/reporting executives
- Growth teams
- Business owners
- Professionals moving from marketing into analytics
PREREQUISITES
Start without a coding background.
No coding background required. No Python, prior SQL, advanced statistics or data engineering needed. Basic marketing terminology, spreadsheet use and website/campaign familiarity are useful. SQL and tracking concepts are taught inside the program.
Instructor-led delivery
12 weeks · 36 live sessions · 3 sessions per week · 60–90 minutes each · approximately 36–54 instructor-led hours. Live demonstrations, guided labs, selected assignments, project feedback and a final presentation.
Live online and classroom options. Confirm current weekday/weekend timings and centre availability before enrolment; no unconfirmed start date is advertised here.
Certification
AI5 Academy course completion requires attendance, assignments and the final project. No external vendor certification or employment guarantee is implied.
AI THROUGHOUT THE PROGRAM
AI assists. The analyst verifies.
Use ChatGPT and Gemini for spreadsheet formulas, GA4 questions, GTM troubleshooting, SQL, campaign comparisons, CRM analysis, dashboard commentary, forecasting and reporting. Check calculations, joins, filters and source evidence before accepting a result.
Marketing Analytics in the Agentic AI Era
Week 12 connects AI-assisted and conversational analytics, automated reporting, anomaly detection, AI recommendations and autonomous marketing systems with human verification and measurement governance.
Your changing role
Move from manual report creation toward measurement ownership, analytical problem-solving, AI verification and business decision support. A generated recommendation still needs evidence and an accountable reviewer.
COURSE QUESTIONS
Know what you’re signing up for.
What does a Marketing Analyst do?
A Marketing Analyst measures campaign performance, checks tracking, analyses leads and sales, builds dashboards and recommends actions based on business evidence.
Is this course suitable for beginners?
Yes. Career starters and working marketing professionals can join. Basic marketing terminology, spreadsheets and website familiarity are useful; foundations are taught in the program.
Do I need coding knowledge?
No coding background, Python, prior SQL, advanced statistics or data engineering is required. Practical SQL and tracking concepts are taught inside the program.
Is SQL included?
Yes. Week 9 teaches filtering, aggregation, CASE WHEN, date grouping and basic joins with campaign, lead and sales tables.
Does the course teach Google Analytics 4?
Yes. GA4 architecture, acquisition, marketing analysis, Explorations and measurement QA are included in Weeks 3–5.
Is Google Tag Manager included?
Yes. Week 4 is dedicated to GTM implementation, followed by tracking debugging and validation in Week 5.
Will I learn Data Studio/Looker Studio?
Yes. Google Data Studio (formerly Looker Studio) is mandatory. You build interactive marketing dashboards in Week 7.
Is Power BI included?
Yes. Week 10 covers Power Query, relationships, basic modelling and combined marketing, CRM and revenue dashboards. Both Data Studio and Power BI are taught.
Will I work with Google Ads and Meta data?
Yes. You analyse realistic advertising exports, compare channels and recommend actions. This is analytics training rather than a full campaign-management course.
Is this a digital marketing course?
The focus is marketing measurement and analysis. AI for Digital Marketing teaches execution; AI Performance Marketing focuses on running and improving paid acquisition.
What is the difference between Marketing Analytics and Data Analytics?
Marketing Analytics focuses on campaigns, website tracking, leads, attribution and revenue. General Data Analytics covers a broader range of business datasets and may include Python.
Will I learn CRM analytics?
Yes. Week 8 connects lead qualification, demos, sales and revenue to marketing channels, with first-party data and offline conversion concepts.
How is AI used in marketing analytics?
ChatGPT and Gemini assist formulas, GA4 questions, GTM troubleshooting, SQL, campaign comparisons, dashboard commentary, CRM analysis and forecasting throughout the program. Learners verify outputs against source data.
Are there practical projects?
Yes. Guided labs, selected between-session assignments, project reviews and a final capstone use realistic simulated or approved anonymised datasets.
What portfolio will I build?
Ten portfolio builds cover measurement planning, spreadsheets, GTM, GA4 audit, cross-channel analysis, Data Studio, CRM, SQL, Power BI and the final capstone.
What career roles can I target?
Marketing Analyst, Digital Marketing Analyst, Marketing Data Analyst, Web Analytics Analyst, Campaign Analyst, Junior Growth Analyst, Performance Marketing Analyst and Marketing Reporting Analyst. Job outcomes depend on skills, prior experience and hiring requirements.
Is the program available live online?
Yes. Live online and classroom options are available. Confirm the centre, mode and current batch availability with an AI5 counsellor.
What is the weekly class schedule?
The program lasts 12 weeks with 36 live sessions: three sessions per week, 60–90 minutes each, approximately 36–54 instructor-led hours. Confirm weekday or weekend batch timings before enrolment.
Are paid tools or advertising budgets required?
Commercial advertising spend is not required for supplied training datasets. Confirm software accounts, Power BI setup, optional paid AI features, connector access and Make credits before enrolment.
Will I receive a certificate?
AI5 Academy course completion requires attendance, assignments and the final project. The program does not imply certification from Google, Meta or Microsoft.
CHOOSE YOUR AI5 ROUTE
Execution, paid acquisition or measurement?
AI for Digital Marketing
Run and execute digital marketing.
AI Performance Marketing
Run and optimise paid acquisition.
AI Marketing Analyst Professional Program
Measure, validate and analyse marketing performance with GA4, GTM, Data Studio, SQL, Power BI, CRM, attribution and AI.
For a broader cross-business analytics route, compare Data Analytics with AI.
LET’S PLAN YOUR NEXT STEP
Build a portfolio that answers business questions.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
COURSE PLANNING
AI Marketing Analyst Professional Program Course: syllabus, projects and admission details
Learn GA4, GTM, Google Data Studio, Power BI, SQL, CRM Analytics and AI to measure marketing from click to customer and revenue.
AI Marketing Analyst Professional Program Course syllabus
Week 1 · Marketing measurement foundations, Week 2 · Excel & Google Sheets for marketing analysis, Week 3 · Google Analytics 4. Read the full curriculum above for the complete learning sequence.
AI Marketing Analyst Professional Program Course projects
Marketing Measurement Plan; Campaign Performance Workbook; GTM Tracking Implementation. Check the project section for the work expected in this program.
AI Marketing Analyst Professional Program Course eligibility
Entry level: Beginner to Professional. Ask a counsellor to confirm whether your background meets the program prerequisites.
AI Marketing Analyst Professional Program Course duration
Program duration: 12 weeks. Confirm the next batch timetable before joining.
AI Marketing Analyst Professional Program Course tools
Google Analytics 4, Google Tag Manager, Google Data Studio (formerly Looker Studio), Microsoft Excel, Google Sheets, Power BI. Tool access and any paid accounts should be confirmed for your cohort.
AI Marketing Analyst Professional Program Course fees and batches
Training mode: Online + Offline. Request current fees, available batches and a suitable schedule.
Get course details →