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Data Analytics Methods for Marketing
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:
• Understand your audience using analytics and variable descriptions
• Define a target audience using segmentation with K-means clustering
• Use historical data to plan your marketing across different channels
• Use linear regression to forecast marketing outcomes
• Describe marketing mix modeling and apply different attribution models
• Assess advertising effectiveness
• Explain how A/B testing works and how you can use it to optimize ads
• Evaluate experiment results and assess the strength of the experiment
• 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.
Duration
7 Months
Institution
Meta
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into Meta.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$191
Total Est. Investment
$191
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the Data Analytics Methods for Marketing program at Meta are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.