Apply Marketing Analytics for Data-Driven Decisions
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What you'll learn
Analyze real marketing data using structured decision frameworks.
Build and interpret predictive models for customer targeting and retention.
Apply analytics insights to support data-driven marketing decisions.
Details to know
January 2026
8 assignments
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There are 2 modules in this course
By the end of this course, learners will be able to analyze real marketing data, apply structured decision frameworks, build and interpret predictive models, and evaluate customer targeting strategies using analytics-driven insights.
This course equips learners with practical marketing analytics skills required to make informed, data-driven marketing decisions in modern organizations. Learners will progress from understanding CRM and marketing decision frameworks to working with real-world marketing data, generating actionable insights, and applying predictive models such as logit models for retention and targeting. The course emphasizes how data analysis translates into meaningful marketing implicationsβfocusing on who to target, how to engage customers, and how to allocate resources effectively. Learners will benefit by developing analytical thinking, improving their ability to interpret marketing data, and gaining hands-on exposure to models widely used in industry. What makes this course unique is its strong integration of decision frameworks, real marketing datasets, and predictive modeling, ensuring learners not only understand analytics concepts but also know how to apply them in practical marketing contexts. This course is ideal for professionals and students seeking to strengthen their data-driven marketing decision-making capabilities.
This module introduces learners to the foundations of marketing analytics by explaining how customer data, analytical frameworks, and real-world datasets are used to structure marketing problems, generate insights, and support data-driven decision-making.
What's included
8 videos4 assignments
8 videosβ’Total 63 minutes
- Introduction to CRM and Marketing Analyticsβ’2 minutes
- Marketing Problems and CCMFβ’7 minutes
- Real Marketing Dataβ’7 minutes
- How CCM Decision Made Differentlyβ’10 minutes
- Log Linear Dataβ’7 minutes
- Data Analysisβ’8 minutes
- DSA-Initial Marketing Insightsβ’10 minutes
- Summary Outputβ’11 minutes
4 assignmentsβ’Total 60 minutes
- Foundations of Marketing Analytics & Data Thinkingβ’30 minutes
- Marketing Analytics & Decision Frameworksβ’10 minutes
- Working with Real Marketing Dataβ’10 minutes
- From Data to Initial Insightsβ’10 minutes
This module focuses on predictive modeling techniques used in marketing analytics, including logit models, utility theory, likelihood estimation, and targeting strategies to support retention analysis and high-impact marketing decisions.
What's included
8 videos4 assignments
8 videosβ’Total 64 minutes
- Marketing Implications How and Whomβ’7 minutes
- Logit Modelβ’10 minutes
- Estimating Binary Logit Model of Retentionβ’6 minutes
- How to Calculate the Utilityβ’6 minutes
- Value Actual Likelihoodβ’10 minutes
- Banking Balanceβ’10 minutes
- Targeting Questionsβ’8 minutes
- Predicted Valueβ’6 minutes
4 assignmentsβ’Total 60 minutes
- Modeling, Prediction & Targeted Marketingβ’30 minutes
- Marketing Models & Retention Analysisβ’10 minutes
- Utility, Likelihood & Financial Contextβ’10 minutes
- Targeting & Predictive Decision-Makingβ’10 minutes
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