Exploring ad targeting
As part of our second example, we will explore the same logfiles with another job for the purpose of generating personalized ads. Let's assume that the company we are working for provides news articles with associated videos to users. For the purpose of the example, we will assume that four categories of news are presented: sports, technology, culture, and travel.
|
Category |
Subcategories | ||||
|---|---|---|---|---|---|
|
Sports |
Football |
Rugby |
Tennis |
F1 |
Cycling |
|
Tech |
Games |
Mobile |
Gadget |
Apps |
Internet |
|
Culture |
Books |
Film |
Music |
Art |
Theatre |
|
Travel |
Hotels |
Skiing |
Family |
Budget |
Breaks |
Analyzing and understanding the data deeply, requires lots of exploration. Fortunately, a Data Scientist validates and calculates some assumptions that result in the following conclusions:
- Our users spend time reading articles and spend more than 20 seconds if they are slightly interested and more than 60 seconds if they are really interested.
- Users who also view the video accompanying each article...
