5 Reasons Why Your Media Company Needs to Create a Custom Data Visualization Tool

Written by Katie Han
Published on Sep. 20, 2017
5 Reasons Why Your Media Company Needs to Create a Custom Data Visualization Tool

Some say that content is king. However, we think data is the real king. You hear the term “big data” a lot in the tech world but what does it mean? Well, simply put, big data is primarily large volumes of data that is used to reveal patterns and trends that businesses analyze to help make more informed decisions.

In the digital age, there is a plethora of data to analyze, and media companies are trying to figure out the best way to leverage their data to enhance customer experiences and increase engagement. There is so much information to analyze, anything from what device a user is on, to what type of content their user is engaged with most (music, tv, movies, etc.) to how much does social media play into their daily interactions.

65% of the population are visual learners—meaning pictures, colors, and shapes help them organize and remember information—and the brain processes images 60,000 times faster than text. Visuals are more powerful than simple textual information as it’s processed quicker and able to be recalled more readily.

With the endless amount of big data available to media companies, various tools are required to understand it, including data visualization tools. However, the question is, are these tools the right fit for EVERY media company or should you create a custom visualization tools for your media company specifically?

Here are 5 reasons why your media company needs to create a custom data visualization tool.

1. Manage the Sheer Volume of Data

Because of technology, we are afforded a lot of information and the computational power to process that information. Having hundreds of spreadsheets with thousands of rows sitting in your company’s database is a chore to access and keep track of. A data visualization tool will aggregate all of the data from multiple sources into one platform so it can be conveniently housed and easily accessed.

Social media is a huge source of data, revealing what content people are liking, what profiles people are following, and whose posts they are commenting on. Facebook generates 4.6 billion “likes” daily. Instagram sees 95 million photos and videos shared daily. Social media companies collect data on billions of daily interactions, and creating data visualizations provides a way to quantify the interactions. Media companies with profiles on multiple social media platforms need a tool to view all of their interactions on one data platform—instead of jumping from Facebook, Instagram, Google, etc. to view each report.

More traditional media, like TV, also amass large amounts of data. In addition to their live broadcasting, other data sources for TV networks can include their online streaming and on-demand services. Or the “new normal” is non-traditional entertainment streaming services such as iTunes, Netflix, Hulu, and Amazon. All of these media companies have multiple data sources, and a custom data visualization tool will combine all of the collected data into one place.

2. Identify Consumer Patterns and Emerging Insights

Media companies want to place their content in niches, or communities where many people are connected to each other because that’s where conversation happens. Tight-knit communities can be identified by creating visualizations such as network graphs with the data. This will help media companies see how their audience is connected on social media platforms and reveal insights on where to deliver the content so it has the best chance of organically spreading with the end goal of going viral.

News media companies can track data to analyze how their subscribers interact with the content. At first, although the move from printed newspapers to online news hurt how news organizations generated revenue (since most online readers expected free content,) online news provided the organization with much more audience data. Which posts perform best with what age group or location? They have data such as who clicked on which article, what device they used to access the article, and how long they stayed on the article which can help them better target content and place ads.

3. Improve Strategic Decision Making

Data visualization is meant to take complex information, simplify it, and make it understandable. Visualizations turn raw data into a graphical representation that can support an informed decision. Because they are based on credible data, visualizations serve to help media companies make important decisions.

Launching a new television series is not easy, nor affordable. Conventionally, TV shows create a pilot episode, which TV networks use to evaluate the viability of a show and decide if they should invest to further develop the series. TV pilots create data when the audience gives feedback, which the network can use to make decisions. Although pilots reveal insights on the next hit show, they are extremely expensive to make (the pilot for ABC’s Lost cost $14 million to produce) and some companies are looking for alternatives to pilots.

Netflix argues against gathering data from pilot episodes and instead gathers data from audience viewing behaviors. Since Netflix releases all episodes of the series at once, they do not need to worry about capturing the audience’s full attention in one episode. They have data on when viewers got “hooked” onto a series, which is determined by 70% of viewers go on to complete the season after a specific episode. Through their data, they know that it only takes some shows two episodes to hook people and other shows take many more. With this data, they can create original content, knowing what type of events and plot line the audience can relate to, find entertainment in, and “hook” onto.

4. Provide Real-Time Data Visualization

Data visualizations can be engaging and interactive. Creating your own data visualization tool can allow your company to track any post or campaign as it goes live and generates visualizations such as charts and maps using real-time analytics.

One example of a real-time data visualization is Tweetping which shows real-time Twitter activity. Companies can track who is talking about their company brand or event right as the tweets are being published.

Analytics help media companies track how they can meet their goals, and being able to see the interaction visually and in real-time puts the data into perspective. Companies can see who the interaction is coming from and where it is coming from at the exact time that it is happening. These interactions are no longer just numbers on a spreadsheet, comments in a database, or locations on a map, but real users in real-time.

5. Analyze Behavior to Offer Personalized Content

Humans now have an attention span of eight seconds, which is shorter than the attention span of a goldfish at nine seconds. One main goal for media companies is to capture people’s attention by creating the best content for their audience. Data can help predict audience behavior for new content.

Spotify is a music streaming company driven by big data. By gathering data such as who the listeners are, where they are, and how they listen to music, Spotify can recommend new music and playlists to each user to make the app as successful as it is today because they know what each user likes to listen to.

In addition to analyzing data to enhance customer experience, Spotify uses it to better target ads and create revenue. For example, if a user is listening to the “Summer Backyard BBQ” playlist and the user does not have a premium ad-free account, the targeted ads will likely include summer or BBQ products. Spotify is one company who leverages their big data to tailor content to each user.

Bringing it All Together

Dom & Tom knows a thing or two about data visualization tools because this past year we created a data visualization platform for our long-standing client. The platform is a real-time social analytics tool that helps marketers better monetize social conversations. The social distribution tool takes proprietary data, analyzes it, and creates valuable insights. The client can identify groups of like-minded viewers and see what topics they care about and share allowing them to create branded content that resonates with their target audience. The platform is not only interactive but also tells a visual story that is easy to understand.

Having tools to analyze data and reveal insights have proven to be beneficial for media companies who are looking to create or buy better content, tailor content to their audience, and better connect with their audience across all platforms.

If your business is looking to create a custom tool to turn your data into an interactive experience, let’s talk!

Hiring Now
OCC
Big Data • Cloud • Fintech • Information Technology • Financial Services