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Marketing Analytics with Python: Data-Driven Marketing
Rating: 4.4 out of 5(54 ratings)
571 students

Marketing Analytics with Python: Data-Driven Marketing

Master customer segmentation, RFM, CLV, A/B testing, attribution, pricing, churn, forecasting, campaigns and ROI with Py
Created byPius Dave
Last updated 11/2026
English
English [Auto],

What you'll learn

  • Analyze marketing data to understand customer behavior, campaign performance, revenue, and business growth.
  • Perform customer segmentation using RFM analysis and identify high-value customer groups.
  • Calculate and analyze Customer Lifetime Value (CLV) to support customer retention and marketing decisions.
  • Design and interpret A/B tests to evaluate marketing campaigns, offers, and business strategies.
  • Apply marketing mix, attribution, and pricing elasticity techniques to measure marketing effectiveness.
  • Analyze customer churn and retention to identify opportunities for improving customer engagement.
  • Use demand forecasting, recommendation systems, and market basket analysis for marketing decisions.
  • Measure digital campaign performance and analyze marketing ROI for better budget allocation.
  • Use Python, Pandas, visualization, and statistical techniques to transform marketing data into actionable insights.

Course content

5 sections • 81 lectures • 14h 55m total length

  • Introduction1:35

Requirements

  • No prior marketing analytics experience is required. The course starts with fundamental concepts and progresses to practical applications.
  • Basic understanding of marketing or business concepts is helpful but not mandatory.
  • No advanced programming experience is required. Python fundamentals are introduced as part of the course.
  • A computer with internet access and the ability to install Python or use a Python-based development environment.
  • An interest in using data, analytics, and Python to solve real-world marketing problems.

Description

Marketing Analytics with Python: Data-Driven Marketing

Turn marketing data into actionable business insights using Python and practical marketing analytics techniques.

This course takes you through the complete marketing analytics journey — from understanding customer behavior and segmentation to measuring campaigns, optimizing pricing, forecasting demand, and improving marketing ROI.

You will learn how to apply analytics to real-world marketing problems, including:

  • Customer Segmentation & RFM Analysis

  • Customer Lifetime Value (CLV)

  • A/B Testing and experimentation

  • Marketing Mix Modeling

  • Attribution Modeling

  • Pricing Elasticity

  • Customer Churn & Retention

  • Recommendation Systems & Market Basket Analysis

  • Demand Forecasting

  • Digital Campaign Analytics

  • Marketing ROI & Budget Optimization

Along the way, you will build your practical Python data analytics skills, working with data, Pandas, visualization libraries, statistical techniques, and analytical workflows.

What You'll Learn

By the end of this course, you will be able to:

  • Analyze customer behavior and identify valuable customer segments

  • Perform RFM-based customer segmentation

  • Estimate and analyze Customer Lifetime Value

  • Design and interpret A/B tests

  • Understand marketing mix and attribution analytics

  • Analyze pricing and customer response

  • Build analytical approaches for churn and retention

  • Apply recommendation and market basket techniques

  • Forecast marketing-related demand

  • Evaluate digital marketing campaigns

  • Measure marketing ROI and optimize budgets

  • Use Python to transform marketing data into meaningful insights

Who Is This Course For?

This course is suitable for marketing professionals, business analysts, data analysts, aspiring data scientists, MBA/BBA students, entrepreneurs, and professionals who want to use data and Python for marketing decision-making.

You don't need to be an advanced programmer. The course progressively introduces the Python and analytics concepts required to work with marketing data.

Learn marketing analytics from a business perspective and use Python to turn data into decisions.

Who this course is for:

  • Marketing professionals who want to use data analytics to improve customer, campaign, and marketing decisions.
  • Business and data analysts interested in applying analytics and Python to marketing problems.
  • MBA, BBA, commerce, finance, and business students interested in Marketing Analytics and data-driven decision-making.
  • Digital marketing professionals who want to measure campaign performance, attribution, customer behavior, and ROI.
  • Aspiring data scientists and Python learners who want to build practical skills through marketing-focused applications.

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