ANLY482 AY2017-18T2 Group30 Youtube

From Analytics Practicum
Revision as of 12:20, 27 February 2018 by Shtang.2014 (talk | contribs)
Jump to navigation Jump to search
APex Logo.PNG


HOME ABOUT US PROJECT OVERVIEW EDA BUSINESS OBJECTIVES PROJECT MANAGEMENT DOCUMENTATION MAIN PAGE
Facebook Post Facebook Video Youtube Instagram Blog Post


Data Source

For data files from YouTube(Watch Time), the sponsor provided exported data for Watch Time, with different metric tabs in Excel format. The tabs included are:

  1. Video
  2. Geography
  3. Date
  4. Subscription Status
  5. Youtube Product
  6. Device Type
  7. Subtitles and CC
  8. Video Information Language


For data files from YouTube(Demographics), the sponsor provided exported data for watch time for different Demographic, with different metric tabs in Excel format. The tabs included are:

  1. Viewer Age
  2. Viewer Gender


For data files from YouTube(Traffic Sources), the sponsor provided exported data for watch time from different traffic source type

Data Preparation

No data preparation is required.

Exploratory Data Analysis

As seen in the chart below, majority of viewers (>70%) fall into the age category of 18-34. Slightly over 10% of viewers fall into the age categories of 13-17 and 35-44 each as well, with less than 5% of views who are above 54.

449 × 520px

Across all the age groups, there is always a larger percentage of female audience except for those 35 and older. The disparity is especially obvious in the 18-24 category, with almost twice as many female viewers.

589 × 548px

Despite differences in views for age and gender, there are no significant differences observed for the average duration (in minutes), which is around 4-5 minutes.

775 × 687px

All of the above findings are consistent with that of Facebook Videos.