Hands-On Marketing Analytics with Python
Hands-On Marketing Analytics with Python, available at $44.99, with 37 lectures, 10 quizzes, and has 6 subscribers.
You will learn about Master the fundamentals of marketing analytics using Python. Analyze and optimize pricing strategies using data-driven techniques. Perform product analytics to understand and improve product performance. Utilize customer analytics to segment customers and predict behavior. Apply retail analytics to enhance sales, inventory management, and customer experience. Gain hands-on experience with real-world datasets and build practical skills for marketing analytics. This course is ideal for individuals who are Marketing professionals looking to enhance their data analytics skills. or Data analysts and business analysts interested in specializing in marketing analytics. or Students and graduates in marketing, business, or related fields seeking practical experience. or Entrepreneurs and small business owners aiming to leverage data for better marketing decisions. or Anyone interested in learning how to use Python for comprehensive marketing analytics. It is particularly useful for Marketing professionals looking to enhance their data analytics skills. or Data analysts and business analysts interested in specializing in marketing analytics. or Students and graduates in marketing, business, or related fields seeking practical experience. or Entrepreneurs and small business owners aiming to leverage data for better marketing decisions. or Anyone interested in learning how to use Python for comprehensive marketing analytics.
Enroll now: Hands-On Marketing Analytics with Python
Summary
Title: Hands-On Marketing Analytics with Python
Price: $44.99
Number of Lectures: 37
Number of Quizzes: 10
Number of Published Lectures: 37
Number of Published Quizzes: 10
Number of Curriculum Items: 47
Number of Published Curriculum Objects: 47
Original Price: ₹3,099
Quality Status: approved
Status: Live
What You Will Learn
- Master the fundamentals of marketing analytics using Python.
- Analyze and optimize pricing strategies using data-driven techniques.
- Perform product analytics to understand and improve product performance.
- Utilize customer analytics to segment customers and predict behavior.
- Apply retail analytics to enhance sales, inventory management, and customer experience.
- Gain hands-on experience with real-world datasets and build practical skills for marketing analytics.
Who Should Attend
- Marketing professionals looking to enhance their data analytics skills.
- Data analysts and business analysts interested in specializing in marketing analytics.
- Students and graduates in marketing, business, or related fields seeking practical experience.
- Entrepreneurs and small business owners aiming to leverage data for better marketing decisions.
- Anyone interested in learning how to use Python for comprehensive marketing analytics.
Target Audiences
- Marketing professionals looking to enhance their data analytics skills.
- Data analysts and business analysts interested in specializing in marketing analytics.
- Students and graduates in marketing, business, or related fields seeking practical experience.
- Entrepreneurs and small business owners aiming to leverage data for better marketing decisions.
- Anyone interested in learning how to use Python for comprehensive marketing analytics.
Unlock the power of data to drive your marketing strategies with our comprehensive course, “Hands-On Marketing Analytics with Python: Learn Practical Pricing, Product, and Customer Analytics with Python through Real-World Projects” Designed for marketers, data enthusiasts, and business professionals, this course offers a deep dive into the essential and advanced techniques of marketing analytics using Python.
What You’ll Learn:
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Pricing Analytics: Understand how to set optimal prices to maximize revenue and market share.
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Product Analytics: Gain insights into product performance and customer preferences to inform development and marketing strategies.
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Customer Analytics: Analyze customer behavior and demographics to enhance targeting and personalization.
Advanced Topics:
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Conjoint Analysis: Discover how to evaluate consumer preferences and forecast market share for new products.
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A/B Testing: Learn to design and analyze experiments to make data-driven marketing decisions.
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Segmentation: Master the art of dividing your market into actionable segments for targeted marketing.
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Market Basket Analysis: Uncover relationships between products to improve cross-selling and upselling strategies.
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Customer Lifetime Value (CLV): Calculate and leverage CLV to optimize long-term customer relationships.
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Funnel and Cohort Analysis: Understand user behavior and retention patterns through funnel analysis and cohort analysis, enabling targeted marketing strategies and customer retention initiatives.
Hands-On Experience:
Using Python, you’ll work with real data sets to apply these techniques and gain practical experience. Through step-by-step tutorials and interactive exercises, you’ll build a strong foundation in marketing analytics and learn to use powerful Python libraries like Pandas, NumPy, and Scikit-learn.
Course Features:
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Expert Instruction: Learn from industry professionals with extensive experience in marketing analytics and data science.
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Practical Projects: Apply your skills to real-world scenarios and projects that mimic actual business challenges.
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Comprehensive Resources: Access downloadable resources, including datasets, code snippets, and detailed documentation.
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Community Support: Join a vibrant community of learners to collaborate, share insights, and seek feedback.
Who Should Enroll:
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Marketing professionals looking to enhance their data analysis skills.
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Business analysts and data scientists seeking to specialize in marketing analytics.
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Entrepreneurs and business owners who want to leverage data for better decision-making.
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Students and career changers interested in entering the field of marketing analytics.
Prerequisites:
Basic knowledge of Python programming and fundamental marketing concepts is recommended but not required. This course is designed to take you from beginner to advanced levels in marketing analytics.
Join us in “Hands-On Marketing Analytics: Pricing, Product, and Customer Analytics with Python” and transform the way you approach marketing through the power of data. Enroll today and start making smarter, data-driven marketing decisions!
Course Curriculum
Chapter 1: Fundamentals of Python and Machine Learning
Lecture 1: Basic Python Programming
Lecture 2: Introduction to Numpy
Lecture 3: Introduction to Pandas
Lecture 4: Data Visualization with Matplotlib and Seaborn
Lecture 5: Introduction to Machine Learning With Scikit-Learn
Lecture 6: Optimization with Scipy
Lecture 7: Importance of Regression Analysis in Marketing
Lecture 8: Regression Analysis
Lecture 9: Cluster Analysis
Lecture 10: Classification
Chapter 2: Introduction to Marketing Analytics & Important tools and techniques
Lecture 1: Marketing Analytics: A Brief introduction
Lecture 2: Introduction to Probability Distributions
Lecture 3: Sampling & Sampling Distributions
Lecture 4: A discussion on Central Limit Theorem
Lecture 5: Introduction to Statistical Inferences
Lecture 6: Statistical Inference: Estimation for Single Population
Lecture 7: Hypothesis Tests
Chapter 3: Pricing Analytics
Lecture 1: Introduction to Pricing Analytics
Lecture 2: FreshBrew Coffee- Optimizing Pricing Strategy for Maximum Profit
Lecture 3: Pricing for Complementary Products
Lecture 4: Turning the Tide: How Complementary Product Pricing Rescued TechX Solutions
Lecture 5: Price Bundling
Lecture 6: A Case Study on Price bundling Strategies of an OTT StreamFlix
Lecture 7: Non-Linear Pricing Strategies
Lecture 8: Case Study: Transforming EcoClean Services with Non-Linear Pricing Strategies
Lecture 9: Case Study: Introducing Two-Part Tariffs at EcoClean Services
Chapter 4: Product Analytics
Lecture 1: Introduction to Product Analytics
Lecture 2: Cohort Analysis
Lecture 3: Funnel Analysis
Lecture 4: A/B Testing for Website
Chapter 5: Customer Analytics
Lecture 1: Introduction to Customer Analytics
Lecture 2: Response Analysis with Random Forest Classification
Lecture 3: Customer Life Time Value Calculations
Lecture 4: Conjoint Analysis
Lecture 5: Market Basket Analysis
Lecture 6: Product Recommendation System
Chapter 6: Key Takeaways
Lecture 1: Key Takeaways
Instructors
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Himanshu Bhardwaj
CEO, Founder and Consultant
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Frequently Asked Questions
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Can I take my courses with me wherever I go?
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