Audience & Attribution Analytics

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

7 weeks, 1 hour a week
Sessions

Self-Paced
Level

Beginner
Subtitles

English

Found in

Overview

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Understand how audiences behave across the customer journey and learn how to measure the impact of marketing touchpoints more accurately. In this course, you’ll use cohort analysis, segmentation techniques, and attribution models to uncover patterns in user behavior and evaluate marketing effectiveness across channels. You’ll learn how to build and interpret cohort analyses to measure retention, churn, and lifetime value over time. You’ll also compare audience segments using behavioral, demographic, and acquisition data to identify high-value customer groups and conversion opportunities. In addition, you’ll evaluate multiple attribution models—including first-click, last-click, linear, and data-driven attribution—to understand how channels contribute to conversions throughout the customer journey. By the end of the course, you’ll be able to analyze audience behavior, improve reporting accuracy, and make smarter budget allocation decisions using attribution insights.

Syllabus

Cohorts: Measure Retention and Churn

Customer growth depends not only on acquisition but also on how effectively users continue to engage over time. In this module, you will use cohort analysis to measure retention, churn, and lifetime value across different marketing segments. You will learn how to interpret cohort tables, identify retention patterns, and recognize signals such as steep churn drops, gradual decline, and high-performing cohorts. The module emphasizes practical interpretation and decision-making rather than manual report construction, reflecting how modern analytics tools generate cohort views automatically. By the end of this module, you will be able to analyze cohort retention patterns and identify opportunities to improve customer retention and long-term value.

Analysis: Identify Success Indicators

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.

Compare User Behavior with Segments: Apply Built-In Segments for Metric Comparison

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

Compare User Behavior with Segments: Analyze Behavioral Differences and Document Insights

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

Models: Evaluate Channel Contribution

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.

Insights: Refine Budget Decisions

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.

Project Module: Audience Journey Mapping

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.