When optimizing ad spend, it is equally good to know where your money is working and where it isn’t. The aim of this project was to optimize demographic targeting for a financial product, the main question being: What features define those who convert the least?
The data was extracted from Everflow, which doesn’t provide customer-level data. Analysis was therefore done on a per-click basis. The clicks were classified as:
Converted: 993 clicks
Not converted: 8,920 clicks
Unique: 9,320 (10.16% CVR)
Not unique: 593 (7.76% CVR)
Total clicks: 9,913
Other data provided were city, phone model, source websites, type of credit card, housing payments, and monthly income.
The most pivotal of all the features proved to be monthly income. The majority of clicks were coming from those who earned a lower income. However, this high engagement rarely resulted in conversions.
Madrileña from Manila 