Customer Analytics for Beginners

A complete, practitioner-built path into customer analytics, covering the full beginner-to-advanced journey used at real companies. You'll learn the core metrics every customer analyst relies on (CAC, CLV, retention, churn, NRR), how to segment customers with RFM and behavioral analysis, how to run cohort and funnel analysis to diagnose what's actually driving results, how to read Voice-of-Customer data like NPS and CSAT, the basics of A/B testing and experimentation, and simple predictive techniques like churn risk scoring, all using two running example businesses (a subscription app and an e-commerce retailer) so every concept builds on the last.

Rutvik Acharya

Principal Data Scientist

Atlassian

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What You'll Learn

Calculate and interpret core metrics like CAC, CLV, retention, churn, and net revenue retention

Segment customers using RFM analysis and behavioral data to target the right people with the right message

Diagnose what's really driving churn and conversion drop-off using cohort and funnel analysis

Design simple A/B tests and read the results without fooling yourself

Who Should Attend

Aspiring or junior analysts who want a structured, practical path into customer analytics

Marketing, product, or customer success professionals who want to speak the language of data

Founders and small business owners who need to understand their own customer metrics

Anyone switching careers into data or analytics with no prior background required

CERTIFICATION

Certificate of Completion

10 Modules

9 Hours 30 Minutes

47 Lessons

47 Challenges

Language: English

FAQ

FREQUENTLY ASKED QUESTIONS

No. The course is designed for complete beginners and starts from first principles, defining basic terms and building up gradually. No background in data, statistics, or a specific industry is required.

You will be able to calculate core customer metrics like CAC, CLV, retention, and churn, segment customers using RFM and behavioral analysis, diagnose churn and funnel drop-off using cohort and funnel analysis, design a simple A/B test, build a basic churn risk score, and present findings clearly to stakeholders.

No prior software experience is required. The course teaches the relevant spreadsheet formulas and basic SQL queries as part of Module 9, starting from the fundamentals of each tool.

The course uses two running example businesses throughout, a subscription fitness app and an e-commerce retailer, so you see how the same techniques apply across both a recurring-revenue model and a transactional retail model. The underlying skills apply broadly to most customer-facing businesses.

The course totals approximately 9 hours and 30 minutes across 10 modules and 47 lessons, including two full portfolio projects. Pace is self-directed, so it can be completed faster or spread out over several weeks.

Yes. The two portfolio projects in Module 10 each include a downloadable dataset, specific business questions, and a complete worked solution, so you can practice the full analysis process rather than just reading about it.

The course introduces predictive analytics concepts in Module 8, including rule-based churn scoring and a conceptual overview of propensity scoring, but it does not require or teach advanced statistics or machine learning coding. It also covers how to recognize when a question needs a dedicated data scientist.

Yes. Marketing, product, and customer success professionals, as well as founders and small business owners, will find the metrics, segmentation, and reporting skills directly useful for understanding and managing their own customers, even without pursuing an analyst role.

Each of the 47 lessons includes a practice exercise applying that lesson's concept, and the course closes with two complete end-to-end portfolio projects with worked solutions, giving you both incremental practice and a full realistic project to apply everything together.

Yes, this is a free course covering the full beginner-to-advanced customer analytics curriculum, including the portfolio projects.

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