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.
Data Analytics Methods for Marketing
This course is part of multiple programs.
Instructor: Anke Audenaert
Sponsored by Southeastern University
24,796 already enrolled
(242 reviews)
Recommended experience
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
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There are 4 modules in this course
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 readings3 assignments
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
In week three, you’ll dig into using experiments to evaluate marketing effectiveness. You’ll also learn about A/B testing and how it can help you optimize your campaigns.
What's included
11 videos1 reading3 assignments
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. You’ll 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
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