High-quality market research reports and data visualizations deliver rich insights using minimal space.  To obtain insights needed to make more informed and faster decisions, researchers must ensure users can parse through data seamlessly and efficiently with the limited real estate on computer screens and phones.  We generally utilize data visualization plots that allow our clients to find clusters, identify outliers, and visualize trends quickly.  The heatmap is one of the most useful (yet challenging to create) plots.

Heatmaps provide a powerful method of displaying quantitative data, using color to identify areas of interest.  To create a heatmap, start with two categorical vital attributes (for example, brand and product feature), then color code each cell based on a quantitative value attribute (such as rating from 1 to 5).  Humans can process vast amounts of visual information by color-coding at the preconscious level. The heatmap utilizes this pre-processing, allowing users to discern insights quickly through a visual glance.  Sophisticated heatmaps can display hundreds of categorical attributes and can color-code each cell on 3 to 12 quantitative attributes, resulting in up to one million data points.  Very few data visualization techniques have the visual insight capability of the heatmap, making it one of the more popular tools for market researchers.

Below is a screenshot from an example heatmap in our HVAC Brand Awareness dashboard (with brands redacted).  As can be seen, this interactive heatmap gives users the ability to filter on any demographic (such as generation, company size, or revenue level) and quickly discern the leader in any set of product features.  The color-coding of a heatmap, combined with the matrix-type view, utilizes the visual pre-processing power of the human brain.

The heatmap is one of the most straightforward views of a matrix; each cell is color-coded with a single quantitative variable. Memory and attention are finite resources, and visualizations that give users a simple, reliable, and relatable view of multivariate analysis tend to outperform data visualizations. While heatmaps can be a struggle to set up correctly, they can convey a wealth of information gleaned from the minimal real estate of a phone or computer.