This group project analyzes Air France's international marketing campaigns and generates recommendations for effective search engine marketing.
The dataset is sources from the case study on Air France International Marketing by Kellog School of Business. The external libraries used are readxl, dplyr, plotly, ggplot2, tidyverse, rJava, qdap, tm, wordcloud, plotrix, dendextend, ggthemes, and RWeka.
The project employs visual and statistical tools in R and applies a strategy for missing values and outliers. Additionally, my team added important metrics for subsequent analysis, i.e. return on advertisement, revenue, cost of booking and booking probability.
Then, my team used descriptive analysis to identify the most effect marketing channel and generate a publiser strategy. We identified the effectiveness of campaigns, the best keyword match type and advertisement bid strategies by publisher.
Lastly, we shared our findings a 12 minute presentation in front of the masters of business analytics student body.