Even the most skilled analyst has difficulty reading raw data because it's nothing more than a wall of text, numbers or data points. Looking at a long list of addresses and city locations, for example, doesn't really give you a clear understanding of the regions where most of your audience comes from. Sure, you can probably identify several cities or states, but that doesn't offer anything actionable.
To take collected, raw data and turn it into something useful or practical, you must utilize a process called data visualization. More importantly, data visualization allows you to present data to nearly everyone on a team, even those unfamiliar with the information or content in question. For example, you can make charts and diagrams to explain a particular demographic or data set to executives. With the right tools, you could even just send them the visualized data, and they'll be able to
Of course, none of this is possible with raw data.
One thing that is increasingly common these days, thanks to big data systems, is that the information we are collecting streams in endlessly. While not technically accurate, this notion is correct in the sense that you'll always have something new to process or analyze. The problem with raw data is that it may never reveal or even have inherent value. You may have a long list of telephone numbers or email addresses, for example, that give no clear indication of how or what to use them for.
Step one regarding data visualization is to discern how valuable the data you have in your hands is. This enables several things, the most obvious of which is the option to put that information to use internally. But it also tells you what data is most valuable, providing you with even more assets to sell or barter with. You could take the data you have, for instance, and sell it on a second or third party marketplace. Even though it may not directly help with your brand and processes, it can still be valuable to someone else — and help you by creating an additional revenue stream.
Visual content is a must if you want to capture the attention of your audience. But you would be none the wiser if you merely threw up some media on your brand's social profiles and then checked back every so often. You'd only be able to discern what was popular and what wasn't. You'd never be able to apply that information to future campaigns or posts. With data visualization systems in place, however, you can better understand which visual content works, how, why your audience likes it and even pinpoint exactly who likes it.
Whether you are at the top of a company as an executive or c-suite member or you're further down the ladder as a project or department manager, the information you need to make informed, accurate decisions is mostly the same. You need a clear, comprehensive picture of the steps you are going to take so that you can make accurate predictions and use this as a basis for your decisions.
In layman's terms, you can look at various conditions or scenarios and gauge how they're going to affect your business.
Data visualization processes allow you to see these connections, to make sense of what and why something is happening. For example, you can see how a particular decision affected your most recent shipments, and what that resulted in on the consumer side of the equation. This allows you to either change or optimize the process, ultimately, to boost that bottom line.
Simply put, you cannot make a decision or take action — at least not efficiently — without the proper insights. Data visualization is the act of taking all the data you have and making it practical or actionable so that you can extract insights.
AOL teamed up with a data analyst team at Dapresy to iron out a more actionable way to reach their audience with the data they were collecting. As a result, they were able to meet ballooning business objectives, unlock hidden insights and increase their customers' confidence in them.
The general market is continually shifting, and when you have an ever-changing audience, you have to stay on the bleeding edge. It's difficult though, especially when it comes to making accurate predictions about trends, to predict which way they're going to go. If you align your business objectives to match a growing trend, and it does the opposite and disappears, you're going to lose out on a lot of opportunities and waste a lot of resources.
Data visualization helps you take control of the situation and plan for the worst while optimizing for the best. It offers the insights and statistics to spot trends and opportunities early so that you can take full advantage of them.
More importantly, with the data compiled and processed, decision makers and managers have the information they need to assess customer behaviors and conditions. This enables them to take appropriate action and direct the rest of the organization as necessary.
This visualization of "daily routines of famous creative people" allows you to see what all key influencers have in common. You know that saying "great minds think alike," well this visualization proves otherwise. It also offers some other fascinating insights, so take a look when you have the time.
A data analyst or a data scientist is a professional that can look at various data sets and understand what it means and figure out what to use it for. That definition is a bit broad, but you get the gist of it. And there are many data analysts across a variety of industries, including marketing, retail, customer service and more.
Of course, it costs money to employ a data analyst, and it does no good to have them or a related team confined to a single department or area. The data they are viewing and processing, needs to be passed to other key leaders and team members. In fact, a data analyst may not even know how valuable a set of information is if they don't understand other processes, tasks or projects going on at their company.
Data visualization allows you to take data, which would otherwise be remarkably dull and confusing, and make it readable for everyone and anyone. It can then be passed on to other departments, getting more minds and team members involved. This opens up many new opportunities, especially if those looking over the visualizations can find a unique use for it.
IBM was able to determine cities with the most commuting woes, simply by reorganizing the data they collected during a 2010 survey. This allowed them to better understand and present the data to everyone, not just an internal group of analysts.
After launching a new product, you will eventually find out how it performs. You'll know if it sold well, how much money it made and maybe even what areas or stores had the most sales of the item. You could use that information to build a decent customer profile for future campaigns.
However, the insights you collect without looking at the actual data are shallow and basic. You can't make a more informed decision with them. It would be like grasping at straws. It's still considered a gamble in many cases, because you may not fully understand why a product even sold well or performed poorly.
By collecting loads of data and organizing it to be more viable through data visualization, you can improve the performance and sales of your brand. You can identify the product changes you made that improved or decreased sales as well as what future changes might correct any issues.
The point is that data visualization enables you to boost your company's performance and sales because you can make sense of the vast amounts of data coming in. You can also discover more actionable insights and turn those insights into strategies.
Look at what a difference a website redesign makes!