There are nine chart types to provide you with flexible ways of visualizing your data, including: KPI, column, bar, donut, line, combo, area, heatmap, and table.

KPIs are the perfect way to get a quick summary without the need for a detailed breakdown of your data. This chart will show an average calculation of the data for the period select.

With a simple column chart, you can break down the data by conversation data attributes, user data or other metrics & properties in Intercom.

With a column chart, segmenting the data lets you visualize it in two dimensions. In this example you can see the columns are grouped by "Week", and segmented by the “Team currently assigned”:

Bar charts simplify the comparison of data across different categories, making it easy to evaluate relative performance and trends.

A donut chart is a visual representation that shows parts of a whole by dividing a into segments. This chart is excellent for comparing the relationship among multiple attributes for a single metric, offering a clear and concise visual representation.

A donut chart cannot be segmented down further and can only show one view by layer. Donut charts also do not support the following chart options:

Line charts offer the same options to view and segment your data, but are better suited to showing trends over time.

A combo chart is great for comparing two metrics with different Y axis.

The first metric selected will use a Column chart and use the left Y axis, and the second metric selected will use a Line chart and the right Y axis.

An area chart enables you to observe the cumulative effect of data points over time. By filling in the area between lines with colors and shading, it offers an enhanced perspective on the volume or total of the data points, making it easier to comprehend the overall impact.

Heatmaps visualize the distribution of data across a spectrum, allowing you to quickly identify trends and anomalies in large datasets.

A table gives you a sortable list of values broken down by the dimensions you choose, for example this shows "New conversations" by week, segmented by "Teammate currently assigned".

The Options tab contains more settings which allow you to customize certain elements of a chart.

The 4 available options are:

Not all options appear on every chart type. Use the table below to see which options are available in each chart type:

There are multiple aggregation methods available on time based metrics and ratio metrics.

Average: The total of all values divided by the number of values. For example, if you have five response times of 1, 3, 4, 5 and 6 minutes, your average response time is all of them added together (1 + 3 + 4 + 5 + 6) divided by the number of responses (5) which equals 3.8 minutes.

Median: The middle value in all of your response times. The middle value is what separates the higher half from the lower half of your total response times. For example, if you have five response times of 1, 3, 4, 5 and 6 minutes, your median response time is 4 minutes (the middle value).

Percentile: Existing options like the minimum (1st percentile) show the lowest value, the maximum (100th percentile) the highest, and the median (50th percentile) the middle value of a dataset; now, with the new feature, customers can choose any percentile between 1 and 100. Custom percentiles offer a more nuanced view of your data. While the median gives a good sense of the middle, and the min/max provide the range, custom percentiles allow you to analyze specific segments of your data distribution, tailoring your insights to your specific needs or goals.

Minimum: The smallest value from the time period. For example, if you have five response times of 1, 3, 4, 5 and 6 minutes, the minimum value is 1 minutes.

Maximum: The largest value from the time period. For example, if you have five response times of 1, 3, 4, 5 and 6 minutes, the maximum value is 6 minutes.

Sum: The main function of the sum aggregation is to calculate the total of numerical values. This operation is executed on one or more attribute columns within a dataset, that are used in defining metrics. It's only applicable to numeric data types, such as integers and decimals. During this process, the sum operation iteratively adds the value from each row of the specified column(s), accumulating a running total.

"Compare to previous period" enables you to visually compare a metric across two different time periods.

For example, if you're analyzing the First response rime (FRT) over the last 12 weeks and select the option "Compare to previous period", the chart will display both the data for the most recent 12 weeks and the data for the 12 weeks preceding them.

You can set and compare your metrics against manually inserted targets in selected chart types. This feature adds an extra layer of analysis, allowing for goal-oriented evaluation and tracking.

You can compare your metrics to a manually inserted target in the below chart types:

The table chart type employs a conditional color scheme depending on the chosen metric. For example, with a metric like "closed conversations" and a target of 500, values below 500 are displayed in red, while those above 500 appear in green. Conversely, for metrics where lower values are preferable, such as first response time, values falling below the target are shown in green, and those exceeding the target are highlighted in red.

The relative chart option feature in stacked area or column charts enables users to visualize each attribute's proportional contribution to the overall total, offering a clear comparison of individual elements within the context of one data point.

Customers can add an additional “summary” row to a table via a chart option. The summary row shows the aggregated value for each column of a table.