This happened to me some time back last week when I was looking at a social media dashboard. It had a world map with visualized representation (showing social engagement) of the interest of people in playing computer games. I will spare the details and get to the point on what struck my mind.
For this, let's take the example of a game like Cricket. In India, it is a religion - over 83% of Indians are viewers of the game with the know-how of the top names in the game. As we move west, the viewership for the game reduces. It is definitely not a sport of choice in US. So, the social media data (in this case - the number of social comments or the social engagement) that is garnered from US about cricket may not give the relevant insight.
Now coming back to the point, how can we enhance data visualization in maps in such cases? Here are a few ways we can make data visualization more relevant and impactful -
- Add a context - A context metric in the same visualization like popularity index (viewers/population) can give more insights into the visualization. This can give relevant insight into where exactly to focus if planning to either grow or penetrate into the market. Lot of such metrics like per capita income, population density, propensity to save, etc are openly available to use in such cases.
- Use a different visualization if required - If only the number of comments is of essence to your decision from the widget, you can use a bar graph and sort it according to your need. This will help keep your focus in the right place and definitely save your time. It's a better option on mobile devices as well.
- Use a smaller section of the map - Maps are used best when the geography you are concentrating is a small section of the overall set. The smaller the geography, the better are the insights and the ensuing decisions. And of course, a strong context is imperative to this.
- Keep usability in mind - Do you want a pie on the map showing more info? Imagine the size of the pies if you are working on iPad or phone. You would practically need a needle to make the right touch. Usability is a big aspect of delivering data visualizations and needs to be looked at actively from the initial phases.
- Know your requirement - Are you looking for data on live tweets, likes and comments - To this, the question that we need to ask back is, do we want a monitoring tool or do we want analysis to be done on the data. If you want to monitor, there are far better options then Tableau, Qlik or MSTR (Analytics and BI tools). The likes of Java with D3 will address this need way better.
I have used the map example as a way to put out some of the best practices that we need to question while creating impactful visualizations in our data visualization tools.