Dark Data can be viewed as one of the biggest opportunities for success and one of the biggest opportunities for failure. This is now different in the social media space and more specifically in the video content creation space. We’ve all heard stories of influencers making it big in social media through various means, marketing, viral videos, affiliations, product sales, the list goes on. Something that we haven’t heard much about is the stories of failures and more importantly the stories of people who failed, learned and then became successful. In those stories we are better positioned to extract value from their lessons and use the Dark Data that they were not aware of for our benefit.
The value-focused definition of Dark Data is found here. Youtube and other video streaming platforms can be valuable sources of information for the consumer and valuable streams of income for the creator. In recent years, video marketing on YouTube has become an increasingly popular way for businesses to reach their target audiences. With over two billion active monthly users, YouTube is one of the largest social media platforms in the world, making it an attractive avenue for businesses to promote their products or services. However, despite its popularity, many businesses have struggled to achieve their desired results through YouTube video marketing. One of the main reasons for this is dark data. In this article, we will explore how dark data can lead to YouTube video marketing failures and what businesses can do to avoid them.
Dark data can be a significant barrier to success in YouTube video marketing because it often represents a significant portion of the data collected. According to a study by Splunk, dark data makes up 55% of an organization’s data on average. This means that businesses could be missing out on valuable insights that could help them optimize their YouTube video marketing strategies.
One way that dark data can lead to YouTube video marketing failures is by preventing businesses from understanding their target audience. YouTube provides a wealth of data on the demographics and interests of viewers who watch a business’s videos. However, if a business fails to analyze this data, they may be missing out on crucial insights about their audience’s preferences and behaviors. For example, a business may be targeting the wrong age group or promoting content that is not resonating with their audience’s interests.
Another way that dark data can hinder success in YouTube video marketing is by preventing businesses from tracking their return on investment (ROI). Businesses must track their ROI to ensure that their YouTube video marketing efforts are generating a positive return. However, if they fail to analyze their data, they may not know which videos are generating the most views, engagement, and conversions. This means they may be investing time and resources into videos that are not providing a positive ROI.
Finally, dark data can prevent businesses from identifying and addressing issues with their YouTube video marketing strategies. Without analyzing their data, businesses may not realize that their videos are too long, too boring, or too promotional. They may also fail to spot technical issues such as slow loading times or poor video quality, which can cause viewers to lose interest and click away.
To avoid the pitfalls of dark data, businesses must make a concerted effort to analyze all the data they collect from their YouTube video marketing campaigns. This includes data on viewer demographics, watch time, engagement, and conversions. By analyzing this data, businesses can gain valuable insights into their audience’s preferences and behaviors, track their ROI, and identify and address issues with their YouTube video marketing strategies.
The three primary fail points of YouTube channels that are caused by, dark data are:
- Inefficient resource allocation: Without a comprehensive understanding of their audience and content performance, YouTubers may allocate their resources inefficiently. They may spend time and money creating content or marketing to an audience that is not engaged or interested in their content, which can limit their overall success on the platform.
- Limited Insights (Incomplete data picture): Dark data can limit the insights that YouTubers can gain about their audience and content performance. By not analyzing all the data that is collected, YouTubers may miss out on valuable insights that could inform their content creation and audience engagement strategies. Furthermore, Not being aware of data that can be captured for analysis but not is external Dark Data that cause bigger issues for content creators. When YouTubers don’t analyze the internal and external Dark Data in conjunction with their current processes, they are left with an incomplete picture of their content’s performance, their audience’s behaviors, and the trends that may be affecting their channel’s success.
- Missed trends and patterns (Missed opportunities): Dark data can also result in missed opportunities for YouTubers to monetize their content or grow their audience. For example, if a YouTuber is not analyzing the data about the sources of their traffic, they may miss out on opportunities to optimize their SEO or partner with other creators or brands. When YouTubers don’t analyze all the data they collect, they can miss trends and patterns that would otherwise be visible. Another example is that a YouTuber may miss an opportunity to create content around a topic that their audience is engaging with but not explicitly mentioning in comments, this is referred to as a non-obvious relationships. this is data, or a topic that is not explicitly stated or clearly related to a topic but is connected or supportive of it. To analyze such relationships we need to perform a non-obvious relationship analysis. This type of analysis will enable us to better understand what external factors are impacting us or can impact us.
- Inability to make data-driven decisions: Without a comprehensive understanding of their data, YouTubers may not be able to make data-driven decisions about their content creation or audience engagement strategies. This can lead to inefficient resource allocation, missed opportunities for growth, and other negative impacts on their channel’s success.
Youtubers can make better data-driven decisions by following these steps:
- Set clear goals: Before collecting and analyzing data, YouTubers should set clear goals for their channel. These goals should be specific, measurable, achievable, relevant, and time-bound (SMART). By setting goals, YouTubers can better align their data analysis with their desired outcomes and make more informed decisions.
- Collect and analyze data: YouTubers should collect and analyze data from various sources, including YouTube Analytics, social media platforms, and third-party analytics tools. By regularly analyzing data, YouTubers can gain insights into their content performance, audience behaviors, and trends that may be affecting their channel’s success.
- Use data to inform decisions: YouTubers should use the insights they gain from their data analysis to inform their decisions about content creation, audience engagement, and growth strategies. For example, if a YouTuber finds that their audience is engaging with a certain type of content more than others, they may choose to create more content in that genre.
- Test and iterate: After making data-driven decisions, YouTubers should test and iterate their strategies to see what works best for their channel. By using A/B testing, for example, YouTubers can compare the performance of different strategies and refine their approach over time.
- Stay up-to-date on industry trends: Finally, YouTubers should stay up-to-date on industry trends and changes to the YouTube algorithm. By doing so, they can adjust their strategies accordingly and remain competitive on the platform.
YouTubers can make better data-driven decisions by setting clear goals, collecting and analyzing data, using data to inform decisions, testing and iterating their strategies, and staying up-to-date on industry trends.
