In this article we’ll discuss the remaining report types, the charts:
• Line chart
• Area chart
• Stacked area chart
• Scatter chart
• Bubble chart
• Bar chart
• Waterfall chart
• Stacked bar chart
• Bullet chart
• Funnel chart
• Pie chart
• Donut chart
Each chart will be introduced in the pages ahead, including a brief description and an example.
Displaying a Report as a Chart
To display a report as a chart, from the Report Editor, select from the list of chart icons:
Whatever the chart you choose, your decision needn’t be final. You can view the same data visualized in different ways by selecting various chart types in turn. Each time you click a new chart icon, your report will automatically refresh to display your data in the form of the chart you have selected.
Choosing The Right Chart
The various chart types in the analytics platform are each useful for displaying different types of data in order to gather unique types of insights. The bar chart is designed to ease comparisons between discrete categories of data, scatter charts allow users to gauge correlations between two metrics, and the bullet chart is best suited for indicating progress toward an objective. With many other chart types to choose from, you have some decisions to make. The following sections introduce the chart types, provide typical examples of each chart, and drop pointers on how each chart may be used to help dashboard viewers draw meaningful conclusions from your data.
Line charts are best used to express changes in a metric across time, or progress across a series of stages.
The example below shows the number of activities that occurred each day, broken across various types of activities, between early December 2012 and early January 2013.
Like line charts, area charts can also be used for expressing changes in a metric across time. Unlike line charts, area charts shade the area beneath the lines that represent metric values so that you can more readily compare volumes of data.
The following area chart displays the total amount of money associated with deals in each stage of a sales pipeline – at the current time and at the start of the period. Notice how the shaded area to the left of the lines helps highlight the sideways orientation of the chart. Also note that while stage isn’t technically a time attribute, an area chart is appropriate here because a pipeline represents a linear progression of deals from one stage to the next until closure.
Stacked Area chart
The stacked area chart is an area chart that has been stratified into constituent layers through the introduction of some second attribute.
In the following example, the stacked area chart could serve as a standard area chart if you were just to focus on the top-most line, which signifies the total number of sales across all six products. But if you direct your gaze to the various layers beneath the top- most line, you can see that the total number of sales actually consist of the sales of six individual products aggregated together. Each product’s sales are displayed as its own layer. To be more exact, the magnitude of each product’s sales in a given week is represented by the product layer’s height directly above where that week appears along the x-axis.
Scatter charts are useful for analyzing trends between two metrics, or for simply tracking the magnitude of two metrics from the same chart. Scatter plots typically have a minimum of two metrics (one for each axis) and one attribute (which determines what each data point stands for).
The following scatter chart displays the relationship between two metrics: the age of individual account opportunities (along the x-axis) and that account opportunity’s score (along the y-axis).
Bubble charts are similar to scatter plots but offer an added functionality –the size of the plotted points can be set to change in proportion to the magnitude of a third metric.
In the following chart, the position of a bubble along the x-axis indicates one metric value, while its position up the y-axis indicates a second metric value. The bubble’s size indicates a third metric: the relationship of the Expected + Won value to the quota.
Bar charts allow you to visually compare discrete categories of data.
The following example allows a viewer to compare two metrics, actual revenue and potential revenue, across a number of different lead sources.
Waterfall charts show the net change in some amount between a starting point and end point. The net change is typically displayed as though broken down into constituent parts.
The waterfall chart below displays the net change in a sales pipeline during a given quarter. The first bar represents the starting point (total opportunity amount at the start of the quarter), while last bar represents the end point (total opportunity amount left at the end of the quarter).
Together, the two central bars in red represent the difference between the start point and end point.
Note that the unlike a typical bar chart, the waterfall chart below actually displays four metrics, rather than a single metric broken apart by one or more attributes.
Waterfall charts may require some extra steps to set up. To establish which bars will designate the start and end points, use the dropdown options associated with your charts Metric Values in the Configuration pane. Select the checkbox under Total for the start and end points of your waterfall:
Stacked Bar chart
Stacked Bar charts are similar to bar charts but offer a glimpse into the composite categories that make up each bar.
The following example displays the number of activities carried out by each sales rep but also breaks down each sales rep’s activities by activity type. This can be useful for getting a cursory understanding of which activities sales reps are resorting to. Still, notice that while comparing the number of emails sent by various sales reps in the chart below is fairly manageable, it becomes far more difficult to compare in person meetings, phone calls, or web meetings, due to the lack of a common baseline.
We’ve incorporated the bullet chart within the analytics platform for those cases where you need to display a single key measure compared to a static target, or quota. The bullet chart plays a similar role to the (often baffling) thermometer- or speedometer-like gauges on the BI dashboards of yesteryear, but displays information in a more intuitive manner.Bullet charts come in various forms. In the graphic below, you’ll find one coupled with a headline report on a sales dashboard. The headline report displays the total number of marketing qualified leads (MQL) on top. Beneath the headline, a bullet chart indicates the percent of MQLs achieved this quarter (represented by the skinny blue bar) with respect to the original goal (represented by the wider gray bar).
Other bullet charts can be more complex. In the chart below the thick gray solid bars represent predictions, the small turquoise vertical markers (aligned with values along the x-axis) represent goals, and the skinny turquoise horizontal bars represent actual progress achieved: