Learn the best practices when visualizing Geosocial data for data analysis or in your own platform.
One question we are often asked is how to visualize our data. We've put together a short guide to help answer that question, which can be found here.
Below are some quick tips to help you effectively visualize Geosocial data.
Tip #1: Choose the right type of visualization. Heatmaps, bar charts, scatter plots, gauges, and histograms work well for visualizing Geosocial data. Pie charts do not because scores are based on a percentile of the nation, and not a percentage of the conversation.
Tip #2: Choose the right type of heatmap. In most cases, we suggest using block group shading heatmaps because it shows precise scores for specific areas. However, if you prefer to show more granularity, you can use a blended heatmap.
Block group shading Blended shading
Tip #3: When possible, visualize a single segment at a time. Only showing one segment on a map allows the user to clearly see where the behavior is strongest/ weakest. Visualizing multiple segments forces you to show only the most prevalent segment in each block group. While interesting, this can be confusing with many segments.
Tip #4: When visualizing single segments, use a monochromatic color scheme. Use a single hue and go light to dark in value. Avoid using multiple colors (i.e. Blue to Yellow) since this often creates confusion as to which color represents high and low scores.
Tip #5: When visualizing multiple segments, show as few segments as possible. A heatmap with 20 different segments is probably not going to be very valuable for discovering insights. Therefore, we recommend only displaying the dominant segment out of three or four that are relevant to your brand/ analysis.
Tip #6: Make clear distinctions between demographic correlations and data on the heatmap. Every Geosocial segment has demographic correlations to help provide additional understanding. If you choose to visualize this data, it is important to differentiate between the correlation and the actual data that is in the block group, as it can be easy to think the demographic correlations represent the data that are in a selected block group.
Tip #7: Make the data personal. 72 segments is a lot for a user to wrap their head around. You can simplify the experience for them by cutting down to only the segments most likely to matter. For example, relate Geosocial segments to sales or see which segments are already common around a brand's existing stores.
For the full-length Geosocial Visualization Guide, download our free ebook.