Data Analytics Methods for Marketing
5 weeks of study, 5-6 hours/week
Grade Achieved: 86.18%
This course explores common analytics methods used by marketers. You’ll learn how to define a target audience using segmentation with K-means clustering. You’ll also explore how linear regression can help marketers plan and forecast. You’ll learn to evaluate the effectiveness of advertising using experiments as well as observational methods and you’ll explore methods to optimize your marketing mix; marketing mix modeling and attribution. Finally, you’ll learn to evaluate sales funnel shapes, visualize and optimize them.
By the end of this course you will be able to: • Describe when analytics is most commonly used in marketing • Understand your audience using analytics and variable descriptions • Segment a population into different audiences using cluster analysis • Use historical data to plan your marketing across different channels • Use linear regression to forecast marketing outcomes • Describe marketing mix modeling • Describe attribution modeling • Apply different attribution models • Evaluate advertising effectiveness and describe the shortcomings • Describe the use of experiments to evaluate advertising effectiveness • Explain how A/B testing works and how you can use it to optimize ads • Evaluate results of an experiment and assess the strength of the experiment • Evaluate and optimize your sales funnel This course is for people who want to learn how to plan and forecast marketing efforts as well as evaluate marketing methods and sales funnels for optimization.
WHAT YOU WILL LEARN
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How to plan and forecast your marketing efforts across different channels
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How to use marketing mix modeling and attribution to optimize your efforts
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How to evaluate and optimize your sales funnel
SKILLS YOU WILL GAIN
- Marketing
- Marketing Mix Modeling
- Data Analysis
- Linear Regression
- Marketing Plan