A Heatmap is a two-dimensional representation of data in which values are represented by colors to demonstrate the distribution. For our Audience Heatmaps, "warmer" colors (red/orange) represent a higher concentration of devices, while "cooler" colors (green/blue) represent a lower concentration of devices in any given area.
NOTE: Heatmaps are available for Geoframe-based Audience types only. Read more here.
Create a Heatmap
Find the Geoframe-based Audience you want to use for the Heatmap, then click on the 3 dot "action" menu to the right of the Audience name
Click on Generate/Share Reports
Click on Prepare Heat Map button
When ready, just like the Insight Report, you will be able to see the data visualization in an interactive format and you will have a link you can share with others inside or outside of your organization.
There are 2 views available with Heatmaps: Heatmap and Cluster. Both show the same data, but is visualized differently. The data displayed contains the general Residence/Household or Workplace location/address of the devices seen within the Geoframe or radius (if generating a Heatmap for a Trade Area Audience.)
The Heatmap is more traditional and a style you are probably most familiar with. The deepest red color shows the highest concentration of where people live or work that visited the Geoframe(s) selected for in the Audience build.
The Cluster show the number of data points within a cluster of of where people live that visited that geoframed location..
Examples of each are below:
Residences vs. Workplaces
By default, the Heatmap is going to display the Residences/Households as either a cluster or Heatmap of the Devices observed in the Geoframe Audience. As you zoom in on the Cluster view, you will see numbers associated with the general area of Residences/Households. NOTE: we do not allow zooming into individual Residences/Households to comply with PII regulations.
You can toggle on Workplaces to get a similar visualization of where Devices observed in the Geoframe Audience work.
Observations
This visualization can be useful when Geoframing locations with a large footprint (think shopping centers/malls, venues, etc.) to understand where mobile device usage occurs at the location. For the majority of Geoframes, observations will be clustered fairly close together, however, for larger footprint locations, the observation view can provide insight on where people typically park, walk, or what stores people shop at the most.
