For companies just starting with a business intelligence platform, sometimes it’s a challenge to know where to start with their metrics. It is useful to become familiar with the widget options that come with your platform, in order to choose the most appropriate ones to display your KPIs. In this blog, we’re going to talk about heatmap widgets, including what they are and how to use them.
What is a heatmap?
A heatmap is a graphical display of data where the intensity of a color represents the value of a variable. The colors are arranged on a gradient, with darker shades depicting higher values and lighter shades depicting lower values, enabling viewers to swiftly identify trends within the data.
Benefits of using a heatmap in business performance
Heatmaps enables businesses to see the relationships in their data. Some of the benefits of heatmaps include the following.
Understanding user behavior
A heatmap visually represents data where the individual values contained in a matrix are represented as colors. This can, for example, help businesses understand how users interact with their website or product, which areas are attracting the most attention, and which areas are being ignored.
By providing a clear and easy-to-understand view of data, heatmaps, like any well-chosen widget, help firms make informed strategic decisions. They can identify trends and patterns, highlight problem areas, and determine where to focus their efforts.
Increase in sales
Heatmaps can assist sales professionals in identifying which products or services are most popular and which areas of their stores are most visited. This information is useful in optimizing product placement and marketing strategies, potentially leading to increased sales.
Time and cost efficiency
Heatmaps provide a quick overview of large amounts of data. This saves the stakeholders time and resources that would otherwise be spent analyzing and interpreting complex data sets. Moreover, the insights gained from heatmaps help businesses avoid costly mistakes and inefficiencies.
How to configure a heatmap in Bold BI
- Build a new dashboard or open an existing one.
- Drag and drop the heatmap widget from the toolbox into the design canvas.
- In the heatmap widget’s configuration panel, click the Assign Data tab.
- In the Value section, drag and drop the measure you want to display in the heatmap.
- In the Dimension section, drag and drop the dimension that you need to group the data in the heatmap.
- Customize other features of the heatmap like the color scheme, the title, and the labels.
- Save the heatmap and add it to your dashboard for easy access and analysis.
Check out our documentation for details on the configuration, to enable you to build the design of choice.
When to use a heatmap
A heatmap is useful:
- To visualize the distribution of data.
- To compare different sets of data.
- To visualize relationships between variables.
- To present large amounts of statistical data.
- To identify hotspots in the data.
- To interpret the magnitude of values within a data set.
When not to use Heatmap
You should not use a heatmap when:
- The data is not continuous.
- There are too many data points.
- The data is continuously changing.
- Dealing with discrete data.
- Handling sparse data
- Dealing with 3D data.
- Highlighting outliers.
Tips for using heatmaps
- Set realistic goals that can be achieved.
- Select the appropriate type of heatmap for your data and analysis goals.
- Use a color palette that is easy to understand.
- Ensure that the color scale on your heatmap is appropriate for your data.
- Provide clear labels for both the rows and columns of your heatmap to make it easier for viewers to interpret the data.
- Sort the rows and columns of your heatmap for clarity, placing related data points together for easier pattern identification.
- Create a clear and concise legend that explains the color scale used in the heatmap.
- Include a title and a brief description to provide context.
- Test the heatmap with users to gather feedback and improve its usability.
What type of analysis does a heatmap support?
- Distribution analysis: Heatmaps can be useful in visualizing the distribution of data like the frequency of words in a document or the number of customers in a region.
- Comparison analysis: Heatmaps are used to contrast data like the sales of different products or the performance of different teams, helping in detecting areas for improvement.
- Correlation analysis: Heatmaps can be used to visualize relationships between different variables, useful for understanding how the variables affect each other.
- Cluster analysis: Heatmaps can be used to detect clusters of data points that are related to each other, aiding in identifying categories of data that share common features.
Heatmap real-time use cases
Healthcare data analysis
The average visit length by department is a healthcare metric is used to display the distribution of average patient visit durations in a healthcare facility. It enables healthcare providers to identify areas where patient wait times might be excessive, enabling them to enhance resource allocation, streamline patient flow, and improve overall operational efficiency.
Sales analysts use heatmaps to represent the distribution of potential revenue across different stages of the sales pipeline and various lead sources. The heatmap color intensity assists sales departments in identifying revenue-generating stages and lead sources, prioritizing efforts, and improving plans for sales performance by recognizing potential areas for improvement.
The areas for improvement by age group metric is for survey analysis. Customers submit feedback forms and the heatmap visualizes the customers opinions on where the company can improve. It highlights areas where certain age groups are especially satisfied or dissatisfied. Businesses can prioritize improvements based on their target groups.
This heatmap provides insurance companies with an extensive view of premium performance trends for different kinds of policies. This visualization assists insurance companies in identifying patterns, high-growth areas, and potential risks. They can make data-driven decisions for which policies to promote and which to downplay.
This heatmap is used in agile development to showcase task distribution across types and priorities. Teams can quickly determine workload balance, spot potential gaps, and make informed decisions for resource allocation. Work is evenly distributed among different task departments, facilitating a more efficient and agile workflow.
HR can use this heatmap to show how much was spent on employee salaries across different departments. HR professionals can detect patterns, disparities, and potential outliers in compensation across departments.
In conclusion, heatmaps simplify large amounts of information, revealing patterns and correlations, leading to swift decision-making.