Gener8’s Pageview and Demographic datasets enable deep analysis of YouTube video consumption behaviour
According to data from Uswitch, the average person in the UK spends 23 minutes on YouTube per day. Whatsmore, those aged 15–24 dedicate much more time to the platform, averaging 48 minutes per day. This makes YouTube a crucial source for content discovery and presents media and marketing professionals with an opportunity to gain profound insights into audience content preferences.
By connecting the Gener8 Pageviews dataset to the YouTube API, we are able to delve even deeper into YouTube consumption patterns among our extensive panel of users.
So, what are the potential use cases?
By analysing user video consumption and comparing it to our demographics dataset, we can observe how preferences vary across different generations. This information becomes particularly valuable when seeking to understand video consumption patterns and demographics at a broader, macro level, especially within specific video categories.
For example, we can observe that gaming category content indexes higher amongst younger generations whilst Auto & Vehicles category is most popular amongst Gen X.
But we can also zoom into the micro level and understand the consumption demographics of specific channels.
In this example, we see that Beard Meets Food, a channel focused on eating challenge videos, indexes highly among Millennials and Gen X but drops off entirely with Baby Boomers. As expected, it also has a significantly higher engagement among men, indexing at 122.
We can also look at broad topic behaviours by filtering by specific trigger keywords within the video title, description or tags. By searching for Call of Duty Black Ops 6-related content, a popular instalment of a video game franchise that comes out this week, we can easily find all videos talking about the upcoming game.
By doing this, we can quickly learn that Black Ops 6-related content indexes highly with younger generations.
However, when looking at Black Ops 6-related video consumption, we can find that Millennials actually watch more content than the average of 4.7 videos per user.
If you're working for a brand or agency, comparing the frequency of YouTube views across various project-related topics can provide valuable direction for shaping your content calendar. Additionally, you could segment your audience into cohorts of low, medium, and high-engagement content consumers to refine data analysis and uncover deeper insights.
By taking a broad view of a topic, you can identify the top-performing channels related to it, such as those focusing on Call of Duty: Black Ops 6.
This allows for the quick identification of leading content creators and an analysis of the types of content they produce. For example, MrDalekJD specialises in Call of Duty Zombies content, while the official Call of Duty channel has been highlighting the storyline of the upcoming game.
Additionally, examining the channel views per user can help determine audience loyalty to a specific channel and identify video strategies that may be contributing to higher view counts. In the case of CodeNamePizza’s content, it appears that his shorter videos, typically lasting 2-3 minutes, are the primary factor behind his impressive average of 11.5 views per user.
By tracking the videos a user has watched, we can determine their exposure to YouTube ads. Filtering for 'unlisted' videos is an effective method to identify these hidden videos.
When looking at the Amazon.co.uk YouTube channel, we can quickly identify both promotional and recruitment videos.
Although most video views came from Amazon's Daily Deals campaign, about 2% of total channel views were attributed to Amazon’s apprenticeships and career growth initiatives.
We can take a closer look at the individual videos to pinpoint differences in targeting strategies. From our analysis, it appears that the Amazon Daily Deals content was aimed at the broader UK audience, while the Amazon Apprenticeships video was specifically targeted toward individuals with low income.
This analysis could be extremely beneficial for individuals at brands and agencies looking to perform competitor audits or monitor advertising trends on the platform.
Additionally, by integrating other Gener8 datasets such as eReceipts and App Usage, we could determine whether the group of users exposed to a brand's advertising on YouTube was more or less likely to make a purchase from the brand or engage with its app.
We utilised Gener8's Pageview and Demographic datasets alongside the YouTube API to uncover insights behind YouTube browsing behaviour. Gener8 Labs’ complete data and insights solution empowers media and marketing businesses to find actionable consumer and market insights, using our unique, consented, first party panel data sets that are all connected around one user ID.
Discover how you can power your decisions and gain a competitive edge from our behavioural truth set by contacting us today!