Retention analysis becomes more valuable when it reveals the behaviors that predict long-term customer success. In this module, you will analyze cohort behavior to identify early engagement patterns linked to retention, churn reduction, and higher lifetime value. You will compare segmented cohorts, evaluate behavioral signals associated with successful customers, and assess how acquisition sources influence long-term outcomes. Through practical analysis activities, you will connect cohort insights to actionable retention strategies, including onboarding and lifecycle communication improvements. By the end of this module, you will be able to identify meaningful success indicators within cohort data and recommend retention strategies that support stronger long-term customer value.

Learners will master the foundational skills for activating and comparing user segments in analytics platforms to uncover behavioral patterns that inform marketing strategy.

Learners will master advanced engagement rate analysis techniques and develop professional documentation skills for communicating segment insights to stakeholders in marketing organizations.

Marketing conversions rarely result from a single interaction, yet many reporting workflows still assign all credit to the final click. In this module, you will evaluate how different attribution models distribute conversion value across the customer journey and how those differences influence marketing decisions. You will explore last-click, first-click, linear, time-decay, and data-driven attribution models while comparing how each interprets channel contribution. Through guided analysis and hands-on modeling activities, you will apply attribution weighting methods to real conversion paths and assess their business implications. By the end of this module, you will be able to evaluate attribution models and determine how channels contribute to conversions across multi-touch journeys.

Attribution analysis becomes valuable only when it informs better budget and investment decisions across marketing channels. In this module, you will apply attribution insights to refine ROAS calculations, evaluate channel incrementality, and support cross-channel budget planning. You will examine how multi-touch attribution changes the perceived value of different channels and why some high-impact channels appear underperforming in last-click reporting models. Through practical analysis and budgeting activities, you will learn how to translate attribution findings into business recommendations that stakeholders can understand and act on. By the end of this module, you will be able to use attribution insights to make more informed channel-level budget decisions.

When bookings flatline, the instinct is to spend more on acquisition — but more spend on a broken funnel only accelerates the drop-off that was always going to happen. This project module places learners in the role of Lead Analyst for VoyageApp, a travel booking platform where repeat bookings have stalled and leadership needs a data-backed explanation before the next planning cycle. The task is not to pull more reports — it is to read three data sources together as a single diagnostic: cohort retention tables that reveal when customers leave, behavioral segment profiles that reveal who is leaving and how their journey differs, and attribution data that challenges whether the channels credited with driving conversions are actually the ones building long-term customer relationships. The culminating deliverable connects all three layers into a Customer Journey and Value Map with three targeted interventions, each traceable to a specific finding rather than a general marketing instinct. By the end of this module, you will be able to identify retention inflection points from cohort data, surface meaningful behavioral differences between customer segments, evaluate attribution model bias for top-of-funnel channels, and translate those integrated findings into a specific, actionable plan for reducing drop-off between first and second booking.