Marketing Campaigns Analysis¶

Problem Scenario: ‘Marketing mix’ is a popular concept used in implementing marketing strategies. A marketing mix includes multiple areas of focus as part of a comprehensive marketing plan. This all revolves around the four Ps of marketing - product, price, place, and promotion.

Problem Objective: As a data scientist, you should perform exploratory data analysis and hypothesis testing. The goal is to gain a better understanding of the various factors that contribute to customer acquisition.

Data Description:

The variables birth-year, education, income, and so on are related to the first 'P' or 'People' in the tabular data provided to the user. The amount spent on wine, fruits, gold, etc., is related to ‘Product’. The information pertinent to sales channels, like websites, stores, etc., is related to ‘Place’, and the fields which talk about promotions and results of different campaigns are related to ‘Promotion’. Table Of Content:

   1. Introduction
        1.1 Dataset Source
        1.2 About Marketing
   2. First Organization
        2.1 Loading Libraries
        2.2 Loading Dataset
   3. Exploring Dataset
        3.1 Understanding Variables
        3.2 Initial Exploration
        3.3 Statistical Summary
            3.3.1 Analysis Output
   4. Data Cleaning
        4.1 Marital Status Variable
        4.2 Income Variable
            4.2.1 Missing Values
        4.3 Dt_Customer Variable
   5. Exploratory Data Analysis
        5.1 Distributions
        5.2 Barplot for Categorical Variables
        5.3 Bi-Variate Analysis By Boxolot
        5.4 Average Number of Store Purchases by Marital Status
        5.5 Response Percentange
        5.6 Age Distribution By Education
        5.7 Boxplot of Numeric Features
        5.8 Scatter Plot
        5.9 Heatmap