In this file I did a through Data explatory analysis on marketing dataset from datacamp related to different marketing channels and their customers. In this code We'll practice translating common business questions into measurable outcomes, including "How did this campaign perform?", "Which channel is referring the most subscribers?", "Why is a particular channel underperforming?" and more using a fake marketing dataset based on the data of an online subscription business. This course will build on Python and pandas fundamentals, such as merging/slicing datasets, groupby(), correcting data types and visualizing results using matplotlib.
The dataset you provided seems to contain information related to a marketing campaign or a user engagement scenario. Here is a breakdown of the columns in your dataset:
user_id: Unique identifier for each user. date_served: Date when the user was served the marketing material. marketing_channel: The channel through which the marketing material was delivered. variant: Type of variant tested or used in the campaign. converted: Whether the user converted as a result of the marketing material (TRUE/FALSE). language_displayed: Language in which the marketing material was displayed. language_preferred: Preferred language of the user. age_group: Age group of the user. date_subscribed: Date when the user subscribed. date_canceled: Date when the user canceled their subscription (if applicable). subscribing_channel: Channel through which the user subscribed. is_retained: Whether the user was retained as a customer (TRUE/FALSE).