Elo, a prominent payment brand in Brazil, revolutionizes the dining experience by offering personalized restaurant recommendations and exclusive discounts based on users' credit card provider and restaurant preferences. Through strategic collaborations with various brands, Elo facilitates promotions and discounts from diverse merchants to enrich the customer experience.
The primary focus of this project is to evaluate the effectiveness and benefits of these promotions for both merchants and customers. By examining the actual utilization of these offers, we aim to understand whether customers actively engage with the provided promotions and discounts. To achieve this, we will employ predictive modeling techniques to estimate a crucial metric known as the customer loyalty score, which serves as our target variable.
The customer loyalty score is a key indicator of how frequently users avail themselves of the promotions and discounts extended to them. By accurately predicting these scores, we can identify and prioritize the most loyal customers within Elo's customer base. This enables Elo to concentrate their marketing efforts on nurturing relationships with these highly loyal individuals, ultimately driving enhanced customer retention rates.
Additionally, the predicted loyalty scores allow Elo to optimize their marketing campaigns by reducing unwanted promotions directed towards customers who are anticipated to have low customer loyalty. By channeling their resources more efficiently, Elo can tailor their marketing strategies and offers to target specific customer segments more effectively, leading to improved customer satisfaction and engagement.
To support this project, a comprehensive dataset has been provided, encompassing a wide range of data such as historical transaction records, merchant details, credit card features, and anonymized customer information. This dataset offers participants the opportunity to employ diverse data preprocessing techniques, advanced feature engineering methodologies, and cutting-edge machine learning algorithms to build accurate predictive models.
Participating in this project not only provides a chance to contribute to the optimization of promotions and customer loyalty in the industry but also offers valuable hands-on experience with real-world data from Elo, a leading player in the payment domain. The insights gained from this project have the potential to shape future promotional strategies, improve customer satisfaction, and drive overall business success.
Join us on this transformative journey as we explore the effectiveness of promotions and discounts, predict customer loyalty scores, and unlock the full potential of personalized marketing efforts. Let's leverage data-driven insights to revolutionize the way merchants and customers connect, enhancing the dining experience and fostering long-term customer relationships.
Data Source: https://www.kaggle.com/c/elo-merchant-category-recommendation/data