Data Science

Python for Marketing Analytics: Unlocking Insights with Data

9 Lessons Easy

About this course

This course is designed for marketers, data analysts, and business owners who want to leverage the power of Python to improve their marketing strategy. The course covers three key concepts: ideal customer profiles, marketing mix models, and clustering. You will learn how to use Python to analyze customer data and create effective marketing campaigns based on customer insights.

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Course Structure

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Ideal Customer Profile (Similarity Analysis) 2 Lessons

Ideal Customer Profile with Similarity Analysis

In this lesson, we will similiary analysis, ideal customer profile and Euclidean distance to prospect for candiates for bank loans using Python
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Clustering and Segmentation 2 Lessons

How Much Do You Know About Clustering and Segmentation

Test your knowledge of clustering and segmentation

Effective Customer Segmentation and Clustering

Use Python programming language and libraries to analyze customer data, identify segments based on demographics and behavior, cluster customers into groups, and optimize marketing campaigns
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Marketing Mix Model 5 Lessons

How Much Do You Know About Marketing Mix Models

Lets test your knowledge of marketing mix fundamentals.

Marketing Mix Model Part 1

Learn to code a marketing mix model in Python,. The steps will be to gather and preprocess data, use statistical analysis techniques, build a regression model and optimize your marketing inputs.

Marketing Mix Model Part 2

In this section we will be focusing on building and interpreting our marketing mix models.

Marketing Model Interpretation Quiz

Lest interpret the results from the original model and our model with synergy metrics

Marketing Spend Thresholds

We will use a decision tree regressor to get more information on our marketing mix model.
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