Data Analytics Methods for Marketing
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Data Analytics Methods for Marketing
This course is part of multiple programs.
Instructor: Anke Audenaert
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What you'll learn
How to plan and forecast your marketing efforts across different channels
How to use marketing mix modeling and attribution to optimize your efforts
How to evaluate and optimize your sales funnel
Skills you'll gain
- Customer Analysis
- Marketing Planning
- Marketing
- Target Audience
- Marketing Effectiveness
- Data Analysis
- Marketing Strategies
- Regression Analysis
- Marketing Analytics
- Persona Development
- Marketing Strategy and Techniques
- A/B Testing
- Model Evaluation
- Advertising Campaigns
- Conversion Funnel Analysis
- Descriptive Analytics
- Customer Insights
- Data-Driven Marketing
- Online Advertising
- Marketing Channel
Details to know
15 assignments
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There are 4 modules in this course
This course explores common analytics methods used by marketers such as audience segmentation, clustering and marketing mix modeling. . You'll explore how to use linear regression for marketing planning and forecasting, and how to assess advertising effectiveness through experiments.
By the end of this course you will be able to: β’ Understand your audience using analytics and variable descriptions β’ Define a target audience using segmentation with K-means clustering β’ Use historical data to plan your marketing across different channels β’ Use linear regression to forecast marketing outcomes β’ Describe marketing mix modeling and apply different attribution models β’ Assess advertising effectiveness β’ Explain how A/B testing works and how you can use it to optimize ads β’ Evaluate experiment results and assess the strength of the experiment β’ Optimize your sales funnel This course is for people who want to learn how to plan, forecast and optimize marketing efforts using marketing mix modeling, attribution models and A/B tests.
In the first week you will learn about the importance of segmentation in marketing and different methods to use segmentation to determine target audiences for your marketing.
What's included
17 videos5 readings4 assignments
17 videosβ’Total 70 minutes
- Introduction to the Programβ’6 minutes
- Introduction to Data Analytics Methods for Marketingβ’3 minutes
- Introduction to Anke Audenaertβ’2 minutes
- Careers in Marketing and Marketing Analyticsβ’4 minutes
- Introduction: Find Your Audience with Segmentationβ’1 minute
- The Importance of Segmentation in Marketingβ’3 minutes
- Examples of Segmenting Audiencesβ’6 minutes
- Programmatic Creative From Audience Segmentsβ’7 minutes
- Customer Data Platforms (CDP)β’2 minutes
- Segmentation Using Clusteringβ’6 minutes
- K-Means Clusteringβ’8 minutes
- Determining the Number of Clustersβ’4 minutes
- Describing Segmentsβ’4 minutes
- Example: Finding the Target Audience for Snackwallβ’3 minutes
- K-Means Clustering Approachβ’4 minutes
- Describing Segments (Application)β’8 minutes
- Weekly Summary: Find Your Audience with Segmentationβ’1 minute
5 readingsβ’Total 50 minutes
- Data Analytics Methods for Marketing Course Syllabusβ’10 minutes
- Join the Meta Marketing Analytics Community!β’10 minutes
- How to be Successful in this Programβ’10 minutes
- Community Guidelinesβ’10 minutes
- Different Approaches to Segmentationβ’10 minutes
4 assignmentsβ’Total 65 minutes
- Review Your Community Knowledgeβ’10 minutes
- Practice Quiz: Segmentation in Marketingβ’10 minutes
- Practice Quiz: Cluster Analysisβ’15 minutes
- Graded Quiz: Segmentationβ’30 minutes
This week you will get an overview of common descriptive metrics for marketing, including Return on Ad Spend and Return on Investment. You will be introduced to the importance of Customer Lifetime Value and how to forecast marketing outcomes using linear regression analysis.
What's included
15 videos3 readings3 assignments
15 videosβ’Total 61 minutes
- Introduction: Analytics for Planning & Forecastingβ’1 minute
- The Sales Funnel & Descriptive Marketing Metricsβ’3 minutes
- Descriptive vs. Predictive Metricsβ’2 minutes
- Return on Ad Spend (ROAS) And Return on Investment (ROI)β’4 minutes
- Customer Profitβ’6 minutes
- KPIs, Reports and Dashboardsβ’7 minutes
- Customer Lifetime Value and Why it Mattersβ’3 minutes
- Calculating Customer Lifetime Valueβ’5 minutes
- Customer Lifetime Value: Exampleβ’5 minutes
- Introduction: Linear Regressionβ’4 minutes
- Linear Regressionβ’6 minutes
- Linear Regression Continuedβ’6 minutes
- Using Linear Regression to Forecast Marketing Outcomesβ’3 minutes
- Different Forms of Regression Analysisβ’5 minutes
- Weekly Summary: Analytics for Planning & Forecastingβ’1 minute
3 readingsβ’Total 35 minutes
- 3 Ways to Calculate Profit Marginsβ’15 minutes
- Different Approaches to Calculating CLTVβ’10 minutes
- Example: Using Linear Regression to Forecast a Marketing Outcomeβ’10 minutes
3 assignmentsβ’Total 80 minutes
- Practice Quiz: Descriptive Methodsβ’15 minutes
- Practice Quiz: Customer Lifetime Valueβ’15 minutes
- Graded Quiz: Planning and Forecastingβ’50 minutes
In week three, youβll dig into using experiments to evaluate marketing effectiveness. Youβll also learn about A/B testing and how it can help you optimize your campaigns.
What's included
11 videos1 reading3 assignments
11 videosβ’Total 48 minutes
- Introduction: Evaluating Advertising Effectivenessβ’1 minute
- Understanding Advertising Effectivenessβ’5 minutes
- Observational and Experimental Methods for Ad Effectiveness Evaluationβ’7 minutes
- Formulating a Hypothesisβ’7 minutes
- What is an Experiment?β’4 minutes
- Random Controlled Trialsβ’4 minutes
- Intention to Treatβ’3 minutes
- Interpreting Results of an Experimentβ’3 minutes
- A/B Testingβ’6 minutes
- Single Cell, Multi-Cell and Nested Testsβ’7 minutes
- Weekly Summary: Evaluating Advertising Effectivenessβ’2 minutes
1 readingβ’Total 10 minutes
- Deciding on the Use of Experimental or Observational Methodsβ’10 minutes
3 assignmentsβ’Total 50 minutes
- Practice Quiz: Ad Effectiveness Measurementβ’10 minutes
- Practice Quiz: Measuring Ad Effectiveness with Experimentsβ’10 minutes
- Graded Quiz: Evaluating Advertising Effectivenessβ’30 minutes
In the final week, you will be introduced to marketing mix modeling and different attribution models and how to use them to make marketing strategy recommendations. Youβll wrap up the week by learning how to visualize and analyze sales funnels and how to use them to recommend next steps in a marketing campaign.
What's included
14 videos4 readings5 assignments1 discussion prompt
14 videosβ’Total 72 minutes
- Introduction: Optimizing your Marketing Mixβ’2 minutes
- What are Marketing Mix Models?β’4 minutes
- How does Marketing Mix Modeling Work?β’10 minutes
- Making Recommendations Based on Marketing Mix Modelingβ’6 minutes
- What is Attribution?β’6 minutes
- Single Touch Attributionβ’6 minutes
- Multi-Touch Attributionβ’7 minutes
- Challenges When Measuring Across Channelsβ’6 minutes
- Introduction to Sales Funnel Analysisβ’2 minutes
- Dropoff in Sales Funnelsβ’9 minutes
- Sales Funnel Shapesβ’4 minutes
- Visualizing a Sales Funnel in Tableauβ’7 minutes
- Weekly Summary: Optimizing Your Marketing Mix & Sales Funnelβ’1 minute
- Course Summary & Congratulations!β’2 minutes
4 readingsβ’Total 45 minutes
- Evaluating Results of Marketing Mix Modeling β’10 minutes
- Attribution Models Reference Guideβ’10 minutes
- Sales Funnel Reference Sheetβ’10 minutes
- Visualizing a Sales Funnel in Tableau Summaryβ’15 minutes
5 assignmentsβ’Total 130 minutes
- Practice Quiz: Marketing Mix Modelingβ’15 minutes
- Practice Quiz: Attributionβ’15 minutes
- Practice Quiz: Sales Funnel Analysisβ’10 minutes
- Graded Quiz: Optimizationβ’30 minutes
- Data Analytics Methods for Marketing Final Quizβ’60 minutes
1 discussion promptβ’Total 10 minutes
- Share Your Thoughts!β’10 minutes
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Reviewed on Feb 12, 2025
Great overview of Marketing Analytics for Meta Ads Specialists
Reviewed on Mar 2, 2023
Great insight and overview of how to understand and calculate appropriately.
Reviewed on May 9, 2022
Gβreat to get an overall idea of what Marketing Analytics is about
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