How to improve your video content creation using data analytics

When we think of content, we often imagine it as the result of a heroic creative act that escapes the prosaic nature of everyday reality, an unrepeatable and inexplicable impulse with which a person expresses his or her own, indomitable talent. The truth is that, especially today, excellent content always stems from a mix of creativity and data, from a solid knowledge of context that allows the individual to unfold its full expressive power.

Data, in the context of content marketing and video content creation in particular, contributes, when properly processed, to raising the quality level of the creative act. Today, content creators have the ability to incorporate the informational potential of data into both individual content (blog post, infographic, video, etc.) and their content strategies. In this post, we will understand how to improve content creation through the value of data.

To improve video content creation using data, we must first focus on two different analysis needs, which focus on two different metrics buckets:

• Metrics that measure the effectiveness of content once it has been distributed;
• Metrics that inform content creation itself 

The first group of metrics helps determine whether, and to what extent, content connects with the target audience. 

The second group guides the creative process: it provides useful guidance for modifying different aspects of content so that they become more effective. In both cases, data plays an increasingly important role in content design.

Now, we can see why data analytics is indispensable for monitoring and guiding video content creation. But what are the main data sets that creators use?  There are many metrics and KPIs involved in companies’ marketing strategies. Video creators, however, may choose to focus on only a few. Let’s see which ones.

Metrics that offer particularly interesting insights for video content creators fall into three categories: reach, engagement, and audience. We talked about these and other metrics when we explained why video marketing analytics is the only way to fully leverage a video.

Here, we will mention the metrics that are most frequently used to measure video performance and to direct the creative process:

• Impressions: the number of times content is viewed, regardless of whether it is clicked on or not.
• Views: the total number of people who look at the content.
• Cost per thousand (CPM): a marketing term used to indicate the price of 1,000 advertising impressions on a web page.
• Click-through rate: the ratio of the number of times a specific link or call-to-action was clicked on to the number of times viewers activated that link or CTA.
• Viewing time: the amount of time spent watching the video.
• # of Subscribers: the number of viewers following the creator’s channel. 

Now, let’s broaden our point of view to encompass the entire journey of an “ideal” consumer in terms of content-user-spectator. Let’s try to look at the viewer’s perspective as they scroll through the feed on his favorite digital channels, spending a non-negligible amount of time watching a streaming video or reading an online post. Then, let’s accompany him up to the moment when he interacts with the content, even if only with a simple “Like.”

If we keep the purchase path in the background, focusing on the upper part of the funnel—which is crucial to the commercial crowning of the brand-customer relationship—and try to test the way the analytics work against our video, we will most likely come across a number of interesting pieces of evidence.

• Reach metrics will give us a pretty good idea of how many people, thanks to our video, might be converted from potential viewers to leads. They will then help us understand whether our video captures our audience’s attention and helps keep it.
• Engagement metrics, which identify the moments when users interact with our content (and record the intensity), will give us an idea of the degree of engagement. These are numbers that allow us to evaluate the overall quality of videos according to more objective parameters and can identify, even with high granularity, the different aspects within the video that produce better performance. These are extremely useful data analytics from which creators derive the suggestions they need to improve their creative process, adapting it in real time based on user interactions.
• Finally, audience metrics allow us to better know our target audience and to understand the community logic that influences their behavior. This will help us decide which topics to cover in our next videos and the technical features and functionality these videos should have.  

Of course, there are other metrics, including much more advanced ones, but the metrics we have briefly identified provide fairly detailed informational coverage of the content and its performance.

In all three cases, the metrics should be associated with a monetization system that succeeds in giving them economic value as well.

• Which features of our video generated higher monetization? (Length of the video? Locations of users? Topics?)
• Which users converted the most? Where are they located? What do we know about their demographics?

These are just some of the questions that data analytics can answer. Questions that are becoming more pressing every day as competition in the video content creation industry increases. 

Digital technologies come to the rescue. The use of video platforms can facilitate more careful monetization of video content: data processed in the platform produce insights that can guide creators in building videos that can, in turn, generate more revenue, for example through targeted video advertising actions.

Within video platforms there are even more advanced solutions for automatically creating interactive videos, where data is imported directly into the video. These video automation tools can easily unlock the potential of digital communication, all without any technical expertise! In just a few simple steps, content creators will be able to make full use of the data at their disposal to create thousands of compelling, personalized videos in which they can insert immediately clickable interactive calls to action, thus shortening the distance between content enjoyment and conversion.

Video content contributes greatly to building a relationship with the viewer. 

In addition, leveraging the data collected makes it possible for content creators to take the proverbial leap: to value—even economically, as we have seen—the insights that can be gained from performance analysis, to find inspiration to create new content, and thus to improve their digital reputation.  Also in the case of video content creation, as is the case in business marketing, you need proper data analytics to get the most out of data. This allows you to be able to extract meaningful information, make informed decisions, and generate new content ideas. Data analysis can prove decisive in finding original topics, understanding audience needs, distributing videos at the right time and place, and revealing the “secrets” of viewer interactions.

• Finding original topics: Data analysis helps to understand the need of the moment within a certain field and to identify, even keeping track of the activity of other creators, what people most frequently ask about a specific topic. It may happen that previously neglected topics emerge, highlighted, perhaps, by unexpected associations between context, experience, contingencies, and value orientations. 

• Understanding the needs of the audience: Using data to understand your audience’s needs means, first and foremost, being able to avoid crowding your editorial calendar with generic content. To work, video content creation must trigger a mechanism of empathy, it must resonate with the target audience, and it must cover concrete and relevant situations. Only then can it contribute to building a digital presence that viewers perceive as relevant.

• Distribute videos to the right place at the right time: Content creation is obviously essential, but distribution is equally important. Content creators may also have more than one specific target audience, and his target users may be in different (albeit rather circumscribed) geographic areas. His content will then need to be delivered at the right time and in the right place, geographically and virtually. To reach his viewers and to get the most out of his videos, a content creator has various data analysis tools at his disposal with which to determine the most appropriate time and channel.

• Unlocking the “secrets” of interactions with viewers: Data analytics can play a considerable role in understanding content performance. Today, there are numerous tools that help measure not only clicks on videos, but also how long the viewing lasts. Some can even track cursor movement. If viewers quit watching after a few seconds without reaching the end and without having interacted in any way, content creators realize they need to change or improve something. The difficulty in the interactions between viewer and content, and even more so the lack of them, unveil the small behind-the-scenes issues that have the power to determine the success or failure of the communication, the glitch in the system that, if not discovered in a timely manner, can prevent a successful strategy.

It’s clear: data and video content creation are closely connected. Let’s go into even more detail and see what data analytics tools are used for in video production, not only in terms of assessing the performance of a piece of content but also in terms of new possibilities for data visualization.

If we’re talking about data visualization, this is something we have all experienced: a situation where graphs and infographics offer so much visual stimuli that the user feels overwhelmed. This information overload occurs all the more if the subject matter is particularly broad or articulate. Videos avoid this danger by inserting tables, histograms, and pie charts enhanced by animation into the flow of the narrative by images, which are therefore, thanks to movement, more immediate and comprehensible. 

In addition, the possibility of choosing between different styles allows the tone-of-voice and visuals to be adapted to trends and developed in very different areas. From expense reports to investment management, from visualization of operating results to an overview of a campaign’s performance: any topic that needs to be accompanied by quantitative data in order to show the dimension and trend of a phenomenon finds  the perfect partner in video. Each graph, positioned within the video sequences, communicates with a clarity and completeness that cannot be achieved with other types of content.

Every day, content creators deal with huge amounts of data that they can use to enrich their videos with meaning: from political polls to weather reports, from economic growth data to demographic statistics. It’s a constant stream that needs to be simplified and communicated to viewers to convey a message that is clear and understandable. Data visualization is an exceptionally effective way to make even very dense data understandable and to translate it into visual knowledge. Data visualization was created to provide all the information needed to describe a given phenomenon or process through visual support. 

Video takes this mode of communication to a previously inconceivable level: it integrates data into narrative structures, projects them into stories, and “humanizes” them by enriching them with emotional nuance. Video content creation, thanks to data visualization, gains precision and authority.

The most advanced outcome of this process of articulating all the ways that data can be visualized, and made possible by data analytics applications, is personalized video. Combining data visualization with video, personalization makes it possible to use data to tailor the narrative to viewers’ preferences and needs, thus unlocking new possibilities for capturing their attention and engaging them. 

As we already mentioned, to improve content creation, content creators can use video to visualize data. However, this does not mean that the end result is something dry or boring. Instead, video can tell the story that lies within those numbers and convey the values around which the story is structured. This is the “miracle” of visual storytelling, a set of tactics that introduces the viewer to a world full of possibilities. Telling a story through video is an increasingly popular way to create valuable relationships with your customers.
Using data analytics, video content creation is able to establish a connection with viewers, which is all the more powerful when the stories told draw on a shared experience, and use it to convey emotion.