What is Data Visualization?
Data visualization is a lot like architecture: it is a blend of creativity and science that has amazing practical benefits. At it’s most basic layer data visualization is an abstraction layer. As Scott Berinato of HBR writes, "Decision making increasingly relies on data, which comes just as with such overwhelming velocity, and in such volume, that we can't comprehend it without some layer of abstraction, such as a visual one.”
Berinato’s definition gives us exactly what data visualization is and why it is valuable to a sales organization: it is a layer of abstraction, i.e. it translates the hard data into a different, visual form, and in so doing it makes data which comes at high velocity and volume easier to understand.
In a modern sales organization this means that when data is coming at a high volume (lots of data), velocity (real-time, streaming data constantly being generated) and variety (data coming in both structured and unstructured formats from many different sources) there is no better way to quickly consume and act on that data than visualization.
How Can it Improve a Sales Organization?
Makes Patterns Visible
This benefit of data visualization is particularly beneficial to those sales organizations whose data is coming from more than one source. In the modern marketplace many sales teams are working under these conditions- you could have sales and customer data streaming in from Salesforce reports, with marketing data coming in from Grow or Hubspot, with performance data coming in from a motivation app like Ambition or Hoopla.
Trying to find the correlations between these different data sets can be a next to impossible task without the aid of data visualization. For example, Berinato recalls the managers of the Osprey aircraft at Boeing needed to improve the efficiency of takeoffs and landings. But there were so many sensors recording so much data that "without visualization, detecting the inefficiencies hidden in the patterns and anomalies of that data would be an impossible slog.”
While the Boeing corporation used data visualization to spot patterns between different sensors sales and marketing teams can use the same principle with their different sources. The crew at visual.ly, for example, combine data from different sources into a single visualization and see a 72% increase in traffic. You can use data visualization to see how a dip in marketing affects sales or customer service by combining these disparate data sources into a single sales performance platform or an add-on to Salesforce, allowing you to see every metric and KPI visually presented in a single tool. For more on which KPIs you should be visualizing for the most benefit to your bottom line, see our free eBook.
If you believe Dale Carnegie 90% of management errors come as a result of miscommunication. The reasons for that miscommunication can be various, but the solution to many of them is simple: have all of your teams working off of the same data visualization and analytics tool. This way you can make sure that your teams are working from the same source of information and, if your data visualization layer is intuitive enough, that they will have the same interpretation of that data.
But data visualization increases communication among your team in another way: coaching. According to Berinato, ”Visual communication is a must-have skill for all managers, because more and more often, it's the only way to make sense of what they do.” It can sometimes be difficult for a sales manager to talk to a sales rep about exactly where they are going wrong. But with data visualizations that are intuitive and easily understandable your sales managers can make their coaching more efficient.
This communication benefit works the other way in an organization as well. Executives want to know high-level information from the sales floor, and they often get that information in the form of Salesforce reports. The problem is that these reports are time consuming for the sales managers to produce and confusing for Executives to read. They can tell both parties that there is a problem, but do very little to discover the reasons why. When you bring data visualization into this equation your sales managers can communicate more clearly and accurately while the Executive can more easily look at a visualization than a complicated spreadsheet to try and find the best ways to improve.
What to look for in your data visualization?
While data visualization is always a good idea, there is a right and a wrong way to go about doing it. For example, if your data visualization only contains charts and graphs then you are missing out on many of the benefits of visualization. Research has shown that "attributes such as color and the inclusion of human-recognizable objects enhance memorability.” Therefore, in your data visualization solution you should look for creative uses of color and human-recognizable objects like pictures and symbols in order to enhance intuition and memorability among all your staff members.
Additionally, researchers J. Suda and Hampton-Smith undertook an extensive analysis of modern data visualization tools and used the following words in their description of the top 5 features that an effective data visualization should have. We put in our own examples to help you understand these features more fully.
- A responsive data visualization is easy to navigate no matter what platform you are on. You should be able to explore the data visualization as easily as you would a picture or painting- zooming in on certain aspects while also stepping back to see the big picture. How well the data communicates no matter what level you are looking at is a determination of its responsiveness.
- Real time
- One of the main benefits of an abstraction layer, as Berinato pointed out, was the ability to decipher information as fast as it appears. No one, other than the very highly trained, can do so with just a spreadsheet. It is therefore important, to get the most out of your visualization tool, that the data coming into it be as close to real time as possible.
- This is especially true when it comes to performance thresholds. The best visualizations will take a data point and automatically determine whether that data falls into a certain range called a performance threshold. If the data point falls within prescribed parameters then the visualization will reflect that in color or size. If the data point falls outside of that parameter the visualization should also automatically reflect that by a change in color or size. This way your staff’s attention will be automatically directed to those metrics that need their immediate attention.
- Fast data visualizations occur when the data can go into a visualization tool and the response is immediate and accurate. Visualizations that take even a minute to load lose their real-time efficacy. This is easier said than done- a fast tool is a powerful one that can combine data sources, analyze the data for performance thresholds and translate all of that information into a visual medium in the blink of an eye.
- Your staff should be able to not only look at the data that is being presented but they should be able to interact with it to explore the deeper relationships behind those data sets. Too often visualizations only present the outer layer without empowering users to delve deeper into that visualization and play with the data
Use these five rules as a guide for your data visualizations and you will be seeing data in a whole new light that will positively impact your bottom line through pattern recognition, clear communication, and real-time analysis. Or, try a free version of a data visualization tool like VisualCue and see the benefits for yourself.