Using Data to Drive Storytelling
How brands can analyze data to make more informed decisions mid-campaign
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Every killer piece of content is driven by a great idea. However, in today's social economy of engagement and ROI, it's important to understand how data is slowly but surely becoming the leading factor in generating quality content. As the pendulum shifts from art to science, learning how to leverage audience insights and behavior is a critical part of driving maximum performance of branded content.
Using Data to Inform the Campaign
Understanding what is important to the brand versus the consumer and what is currently working versus not working have been basic marketing needs for as long as business operations have existed. In today's data-rich environment, marketers have more opportunities than ever before to tap into the numbers as a solution for their needs. The trick is first identifying metrics that matter and knowing where to find them.
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Why learning how to leverage audience insights and behaviors is Job One for CMOs and marketers. 
There are so many points of data, often from multiple sources, that consolidating and organizing them can be quite a challenge, let alone deriving any meaningful insights.
To put this into context, consider a scenario in which a video game maker is asking its agency to develop an original 12-episode YouTube series geared at 13- to 30-year-old male gamers with the goal of driving pre-order sales. The brand also wants additional support for post-launch hard copy and digital-download sales through the holiday season.
With access to platform data from the brand's owned and operated channels, the agency can develop hundreds of ideas for the video series. But differentiating a good idea from a bad one — regardless of how subjectively intriguing or avant-garde the video may be — comes from crunching the data.
Agencies need to better understand what is currently working for the brand. This involves conducting a deep content audit and identifying assets that have common themes, drawing a comparative analysis against content found on competitor channels, and tracking ongoing platform trends most applicable to the target audience.
Knowing what type of content performs best on the brand's channel can immediately inform additional marketing decisions.
Data Sparks Learning, Which Leads to Action
After conducting a detailed audit of the brand's existing content and its competitors' channels the agency arrived at two key conclusions: The existing audience enjoys commentary-based content and the target audience on the platform prefers challenge-based content. However, the brand's managers argued that they've tried the challenge approach and the content underperformed.
FIGURE 1
Gaming Challenges Are Strong Bets, But Face Heavy Competition
What types of challenge-based videos perform well on the platform?
source: 2018 Q1–Q2 2018 Tubular data; internal Fullscreen data
If the audience exists and the content failed to gain traction, then it's likely execution fell short. The problem is the content hasn't differentiated itself enough to penetrate through the colossal volume of both gaming and fad-based challenges.
Rather, the brand needs to tap into what works for the existing audience, which is commentary-based content. If the brand can adapt elements from commentaries into challenges, it's possible it can transition existing viewers to the new format. Should the audience respond well to the change, YouTube's algorithm will kick in and handle organic distribution.
FIGURE 2
Appealing to Subscribers Early Leads to a Video's Long-term Success
There is a strong correlation between subscriber watch-time early in a video's life cycle and how discoverable the video is for nonsubscribers later on
Understanding the correlation between time spent watching the video and discoverability is key to informing the creative strategy in a way that fully satisfies what subscribers want from the brand's channel; in this case, a prerequisite to building awareness of a new video game.
Make Room for Testing
With all of the above incorporated into the strategy and the 12-episode video game awareness campaign on YouTube launched, it's time to collect the data and learn how it enables flexibility to adjust creative.
In reviewing the content post-launch, the data indicates that viewer retention is lower than expected, opening the door to numerous questions about whether the video introduction is too long, if viewers are confused by the rules of the challenge, and if there is too much commentary and too little gameplay in the beginning of the video.
The agency determines that the data from several episodes shows that the reason for the low retention is a combination of a lengthy introduction and too few gameplay elements. Assuming other conditions are consistent (same host, same video length, etc.), the next scheduled episode can be fine-tuned in post-production, shortening the introduction for the challenge, and adding more gaming footage.
Perhaps the next test reveals that it's the specific types of gameplay footage that really helped retain the audience. Or perhaps it's the opening commentary that intrigued viewers enough to convince them to stay. As more data points are collected and patterns are identified, each subsequent creative choice can be made with more confidence.
These near real-time optimizations allow the brand to maximize every piece of content. And whether the YouTube series ultimately outperforms, meets, or underperforms against the brand's KPIs, the resulting data is invaluable in informing future content ideas that can impact the brand's business objectives.
Marketers and brands that struggle to understand the performance and impact of their online content, especially video, need to delve into the numbers to inform their every step. While easier said than done, this approach leads to success — both satisfying business objectives and audience expectations.
Jeff Hwang is a senior strategist at Fullscreen.