An analysis of a marketing campaign and its various delivery channels, as well as total sales and new users, to achieve greater efficiency when investing in advertising.
In this project, our client, an online store, conducted a week-long multichannel marketing campaign designed to evaluate the effectiveness of the messaging and customer response to a range of featured products.
The campaign included two versions of the messages:
The client used three marketing channels:
Website banner
“Which campaign and channel combination should we focus on to increase sales to new customers, and why?”
The Marketing_Campaign_Data.csv file contains records of weekly campaign marketing interactions; these records will be used to analyze the effectiveness of different campaigns and channels.
Below is a detailed breakdown of the dataset's structure and content:
The dataset consists of 7 columns:
Interaction ID: A unique identifier for each customer interaction.
Campaign Type: A categorical variable with two groups, likely representing an A/B test.
Channel: The marketing platform used for the interaction.
Customer Type: Customer classification.
Converted (1=yes, 0=no): A binary indicator showing whether the interaction resulted in a conversion.
Time on site (seconds): The duration the user spent on the site.
Sales ($): The revenue generated by the interaction.
The analytics were performed using Python libraries and Jupyter Notebooks.
The analysis of marketing campaigns A and B and their different delivery channels, aimed at determining the best option for advertising investment, concluded that campaign B via email is the best option for attracting new users, followed by campaign A via email, campaign B via Instagram, and campaign B via web banner.
The analysis revealed total sales from new users of $988,529 and a total of 42,597 new users with a purchase rate of 47.86%.
Campaign B via email acquired 9,700 new users and generated sales of $225,285.52, making it the most effective campaign in terms of new user acquisition and sales conversion.
This could be due to the more formal and personalized communication offered by email, and the more sober and corporate tone of campaign B. This builds trust with consumers and a sense of status and exclusivity, encouraging them to visit the website and make purchases.