Success Through Marketing Evaluations: Analysis and Measurement Course

Lesson 1 • The Marketing Measurement Ecosystem

Maps the relationships among data sources, tools, and decision-makers. Shows how evaluation fits within broader organizational strategy.

Lesson 2 • What Marketing Evaluation Means

Defines marketing evaluation and distinguishes it from general reporting. Establishes shared vocabulary used throughout the course.

Lesson 3 • Setting Evaluation Objectives

Teaches how to translate business goals into measurable evaluation objectives. Anchors all subsequent measurement decisions to strategic intent.

Lesson 1 • Building a Data Collection Plan

Synthesizes collection methods into a structured plan aligned with evaluation objectives. Prepares students to operationalize data gathering before a campaign launches.

Lesson 2 • Digital Tracking and Tagging

Explains pixel tracking, UTM parameters, cookies, and event tagging. Connects digital data capture to accurate campaign attribution.

Lesson 3 • Primary Data Collection Techniques

Covers surveys, interviews, focus groups, and observational methods. Explains when each technique yields the most reliable marketing insights.

Lesson 4 • Secondary and Third-Party Data Sources

Identifies internal databases, syndicated research, and public data repositories. Teaches how to assess source credibility and relevance.

Lesson 1 • Root Cause and Diagnostic Analysis

Applies fishbone diagrams, five-whys, and contribution analysis to explain performance gaps. Moves evaluation from description to actionable diagnosis.

Lesson 2 • Cohort and Segmentation Analysis

Groups customers by shared characteristics or acquisition timing to reveal behavioral patterns. Enables more precise targeting and retention evaluation.

Lesson 3 • Comparative and Benchmarking Analysis

Teaches period-over-period, competitor, and industry benchmark comparisons. Contextualizes performance data so findings carry strategic meaning.

Lesson 4 • Descriptive Analysis Techniques

Covers frequency distributions, cross-tabulations, and trend analysis. Provides the baseline analytical layer before deeper interpretation begins.

Lesson 1 • Data-Driven and Algorithmic Attribution

Introduces Markov chains, Shapley values, and machine-learning attribution. Explains data requirements and trade-offs versus rule-based approaches.

Lesson 2 • Rule-Based Attribution Models

Covers first-touch, last-touch, linear, time-decay, and position-based models. Teaches when each rule-based model is appropriate and how to implement it.

Lesson 3 • Calculating Marketing ROI

Defines ROI, ROAS, and incremental revenue metrics with precise formulas. Connects attribution outputs to financial performance reporting.

Lesson 4 • Attribution Fundamentals

Defines attribution and explains why single-touch models often mislead. Establishes the conceptual basis for multi-touch and algorithmic approaches.

Lesson 1 • Defining Campaign KPIs

Connects campaign objectives to specific, measurable KPIs before launch. Prevents post-hoc metric selection that distorts evaluation outcomes.

Lesson 2 • Paid Media Performance Metrics

Covers impressions, CPM, CPC, CTR, conversion rate, and ROAS for paid channels. Teaches how to diagnose underperformance in paid search and display campaigns.

Lesson 3 • Cross-Channel Campaign Analysis

Integrates metrics across channels to assess total campaign effectiveness. Identifies synergies and conflicts between channel performances.

Lesson 4 • Post-Campaign Reporting and Insights

Structures a post-campaign report that moves from data to insight to recommendation. Teaches how to communicate findings to diverse stakeholder audiences.

Lesson 1 • Customer Lifetime Value Fundamentals

Defines CLV and explains its role in balancing acquisition cost against long-term revenue. Establishes CLV as the central metric for sustainable marketing investment.

Lesson 2 • Linking CLV to Marketing Investment

Uses CLV to set maximum allowable acquisition costs and retention budgets. Enables data-driven decisions about where to invest for maximum long-term return.

Lesson 3 • CLV Calculation Models

Walks through simple, discounted, and probabilistic CLV formulas with worked examples. Enables students to select the appropriate model for their data maturity level.

Lesson 4 • Net Promoter Score and Loyalty Metrics

Explains NPS methodology, customer satisfaction scores, and loyalty program metrics. Links attitudinal measures to behavioral retention outcomes.

Lesson 1 • Budget Optimization with MMM

Uses MMM elasticities to simulate budget reallocation scenarios and identify the optimal spend mix. Directly connects modeling outputs to actionable budget decisions.

Lesson 2 • Building a Basic MMM

Walks through regression-based MMM construction using sales and spend data. Teaches variable selection, adstock transformation, and model fitting.

Lesson 3 • Introduction to Marketing Mix Modeling

Explains the purpose, history, and structure of marketing mix models. Positions MMM as a complement to attribution for strategic budget planning.

Lesson 4 • Forecasting Marketing Performance

Applies time-series forecasting and MMM-based projection to predict future outcomes. Teaches how to build forecast ranges and communicate uncertainty to stakeholders.

Lesson 1 • Dashboard Design and Data Visualization

Applies data visualization principles to build dashboards that drive decisions, not just display data. Covers audience-specific dashboard design for executives and analysts.

Lesson 2 • Sustaining a Measurement Culture

Addresses organizational change management needed to embed evaluation as a standard practice. Equips students to champion data-driven decision-making across teams.

Lesson 3 • Testing and Experimentation Culture

Embeds controlled experimentation into the marketing evaluation cycle. Teaches how to design, run, and learn from A/B and multivariate tests at scale.

Lesson 4 • Building a Marketing Measurement Framework

Designs a tiered measurement framework linking activity metrics to business outcomes. Provides the governance structure needed to sustain evaluation over time.