Project: Online Advertisement dataset analysis and Finding factors influencing Ad-click
Scenario: Given fictitious online ads dataset contains information about customers demographic attributes, behavioral features on the Internet, and characteristics of online Ads. Objective is to extract summary of attributes and insights from dataset and find factors influencing Ad-click.
Attribute information:
- Daily Time Spent on Site: consumer time on site in minutes
- Age: customer age in years
- Area Income: Avg. Income of geographical area of consumer
- Daily Internet Usage: Avg. minutes a day consumer is on the internet
- Ad Topic Line: Headline of the advertisement
- City: City of consumer
- Male: Whether or not consumer was male
- Country: Country of consumer
- Timestamp: Time at which consumer clicked on Ad or closed window
- Clicked on Ad: 0 or 1 indicated clicking on Ad
Observations:
- Daily Internet Usage and Daily Time Spent on Site are two very influencial predictors for Ad click. Influence chart shows likelihood to click an Advertisement is increased approx by 9 times and 8.4 times when average daily internet usage time is less than 48.07 minutes and daily time spent on site is less than 18.18 minutes respectively.
- Two groups of customers are evident from the scatterplot with very few overlapping regions as shown by point with two different colours. In orange colour group the daily internet usage is lower than the blue coloured group.
- Among the top 10 countries by daily internet usage the total daily internet usage is higher for those who did not click advertisement than who did, except for Liberia and South Africa from where most Ad clicks are generated.
- Among females more people have clicked on the Ad while among Males Most people did not click the Ad and also the number of total clicks is higher for females than the males.
- The daily time spent on site varies mostly between just under 50 to 100 throughout time period Early Feb to late July of 2016 irrespective of gender while some sudden surge observed at early Feb and between Feb and March while female a surge is observed at early May 2016.