Tubular’s Customer Stories blog series highlights unique ways that real customers are using Tubular to win in online video. Here, we share diverse stories of how Tubular fits into the workflows of the industry’s most innovative enterprises – from how brands can identify influencers to work with, to how media companies leverage Tubular data and insights to create powerful reporting, enable sales teams, inform content strategy and optimize media buying.
In this edition, we delve into how a major media company can leverage Tubular data to create impressive executive reporting. The data and insights from these reports can then be used to inform sales pitches or to strengthen existing brand partnerships, a process that we will explore further in our next blog post.
To give some context for this scenario, let’s assume that this media company operates a number of properties, including a top series in the late-night space. This company would like to pitch a branded content collaboration between one of their late night shows (let’s call them Awesome Late Night) and a potential advertiser in a month. This media company– we’ll refer to them as UMC (Unnamed Media Company) – can use Tubular to deliver data-driven, mission-critical reports that will impactfully prove their partnership value. The bonus is that Tubular drastically decreases the amount of time typically spent executing the competitive, growth, and trend analyses that we’ll be looking at today.
First Things First
UMC’s first order of priority should be to take a look at some of Awesome Late Night’s high-level metrics:
The Creator Snapshot provides noteworthy information about Awesome Late Night such as total cross-platform monthly views, average first 30-day views (V30), and an intuitive 30-day engagement rating (ER30). Furthermore, by clicking on “Unnamed Media Company (UMC),” they can also navigate to the property-level, which can reveal where Awesome Late Night stands in comparison to every other show or network that UMC owns and operates in regards to online video.
Next, UMC should gain an acute understanding of Awesome Late Night’s digital audience–who are the fans that follow and view Awesome Late Night’s video content online?
To do this, we start out by building a custom channel list that includes all cross-platform video content from Awesome Late Night in 2016. Then, we send the list to the Track Dashboard, which populates with trends data and top-performing videos along with key audience demographics:
Audience Insights highlight that among those who engage with Awesome Late Night’s YouTube channel, the majority are males between the ages of 18-34 and are predominantly located in the United States.
One compelling report UMC can keep track of through Tubular is competitive analysis, providing a comprehensive overview of the late-night landscape.
To do so, search for popular late-night shows in Creator Intelligence and add them to a custom list, which will look like this:
Within the list in Creator Intelligence, UMC will find high-level insights for both the industry in general, as well as specific late-night hosts. UMC will also be able to sort the late-night properties by a number of metrics including total cross-platform views from June, first 30-day views (V30), and a first 30-day engagement rating (ER30).
For example, while Awesome Late Night ranks below Jimmy Fallon, James Corden, and Jimmy Kimmel, it turns out that its engagement rating is higher than Jimmy Fallon’s and Jimmy Kimmel’s and is equal to James Corden’s.
From here, UMC would push both the overall list of late-night properties, as well as individual segments into the Track Dashboard as “saved searches.” Doing so will enable access to very powerful insights.
For one, in Tubular’s Track Dashboard, UMC has the capability to compare late-night properties:
Here, for clarity, we compared only four properties: Awesome Late Night, Seth Meyers, Stephen Colbert, and James Corden. In a single module, UMC can track views, engagements, and uploads over time (daily, weekly, or monthly) of their key competitors. UMC also has the option of exporting this data into a CSV for further analysis.
To dig deeper, UMC can easily click on a competitor’s content spikes (in this case, James Corden) to see precisely which videos are propelling growth. This way, UMC can pulse check competitors’ most popular content.
Similar to competitive analysis, UMC is also able to track Awesome Late Night’s growth. Extending the timeframe to the last 365 days produces an overview of Awesome Late Night’s performance over the last year, as well as current high-level, cross-platform video metrics:
As shown, UMC can choose to measure growth by views, engagements, or uploads in addition to choosing a daily, weekly, or monthly scale. Again, export functionality enables UMC to perform further analysis with raw data.
At this point, UMC has a clear understanding of the progression of Awesome Late Night’s performance. UMC knows how Awesome Late Night compares to competitors and can pinpoint Awesome Late Night’s share of voice in the industry. They also know the rate at which Awesome Late Night has grown historically.
The next step is to understand how Awesome Late Night content has progressed, and similarly, how its competitors have performed so well.
If the user at UMC clicks on any day in the trends graph, they can pull-up a list of most-viewed videos (overall or by a specific platform).
From this, UMC will be able to glean insights about the content that resonates the most with viewers, and moving forward, can cater content to audience tastes. UMC can see on a macro-level which platforms serve the viewing patterns of late-night audiences (YouTube for longer segments, Facebook for shorter clips) and distinguish game-changing content insights.
The idea is to run competitive, growth, and trends analyses regularly, on a weekly basis. This way, when the time comes to put together a deck for the sales team to pitch to a potential advertiser, UMC will have at their fingertips the most compelling and winning stats with which to do so. Next week, we’ll dive deeper into this next phase.