The datasets consisted of Google ads performance, Microsoft ads performance and Meta ads performance data, with each dataframe containing features for date, campaign type (each channel could have multiple campaigns), cost of marketing, number of impressions generated, number of clicks and conversions.
Three features are engineered: Impression Rate (number of impressions / total cost), Click-Through Rate (CTR) (number of clicks / total impressions), and Conversion Rate (number of conversions / total clicks). There are some NaN and Inf values due to division by 0 in some cases – these are filled with 0.
This project was done for the individual hackathon NetElixirAIgnition conducted by the marketing agency NetElixir digital solutions.
The Platypus library's NSGAII algorithm is used for constrained multi-objective optimization. The Genetic Algorithm is run for generations number of generations.