Analytics provide a simplistic visualisation of your data that can help to quickly identify trends and get you on the front foot through simply interacting with and observing the charts present on the page. To aid the identification of insights and trends, chart insights are now also provided giving you a quick glance at key information about your data in the context of each chart; ensuring your time is spent proactively acting on these insights rather than simply analysing the data for the key figures.

## Using Chart Insights

**1.** Navigate to a column chart (i.e. Headcount, Attrition).

**2.** Hover over the **%** icon (visible on the right-hand side of the chart) to view the Chart Insights.

The Chart Insights represent statistical information and insights that **are relevant to the chart you are viewing** on the analytics page.

### Insights Displayed - Chart Stats

The **Chart Stats** section provides insights to help users effectively identify important groups (i.e. rows, slices or bars) of the chart in observation. For example, the row chart below represents the response counts for different survey responses. Specifically, the row labels in the chart represent the response values (in 0-10 rating scale) and are referred to as **"group identifiers"**, and the row values in the charts represent the number of responses received for each of the response values (i.e. "group identifiers") and are referred to as** "group values"**.

The **Chart Stats** section helps users identify the important groups presented in the chart (e.g. rows, bars or slices) by creating a **dataset** of **"group values"**, and from the dataset various stats are then calculated to help users gain an understanding of the chart groups.

For example, from the row chart above, the **dataset** is constructed with the following row values (i.e. group values): `0, 0, 0, 1, 2, 2, 6, 8, 4, 9, 5`

Each value within this **dataset** represents the count of a particular response value (i.e. group identifier). For example, the value `5`

in this dataset indicates there are `5`

responses received with the response value `10`

.

Next, stats summary and insights are extracted from the constructed **dataset.** The following shows an example of currently supported stats in the **Chart Stats** section.

As the **dataset **represents the **group values **of the target chart, the **Chart Stats **therefore mainly contains stats summary for the **group values**. For instance, the "Average" stats value 3.36 is computed based on the average of the **group values** (i.e. row values or response counts), and it could be potentially utilised to help users decide which chart groups (or rows) are below or above the average number of responses in different groups, and thereby allow more informed interpretation and observation of the insights present in the chart.

A list of currently supported **Chart Stats **items are detailed below:

**Minimum: **The minimum value in the dataset (i.e. lowest number of responses received).

**Group (minimum):** Is where the minimum value appears in the data set (i.e. Rating options 0, 1 and 2 received 0 responses which is the lowest value seen in the chart below).

**Maximum: **The maximum value in the data set (i.e. highest number of responses received).

**Group (maximum):** Is where the minimum value appears in the data set (i.e. Rating option 9 received 9 responses which is the highest value seen in the chart below).

**Average: **The average of the values (i.e. add the responses for rating option and divide by the number of months). For example, the calculation would look like: SUM (0, 0, 0, 1, 2, 2, 6, 8, 4, 9, 5)/ 18 = 3.36

**Median: **The median/middle value.

**Standard Deviation: **Standard deviation is the average distance of all data points from the mean of the data set. That is, a higher standard deviation represents a data set that is more spread out.

### Numeric Form Responses

The **Chart Stats** section depicted above is designed to support generalised insights that are applicable across different chart types, and it focuses on helping users to better observe and interpret the groups presented in the charts.

However, in certain circumstances, there are other interesting insights that can be further extracted. The **Numeric Form Response s**ection is one such example.

Taking the same form response count chart example listed in the above **Chart Stats** section, in addition to knowing the **average response count** for different response values as supported in the **Chart Stats** section, it has been identified by some of our customers that they are actually more interested in the **Average response value/rating** present in the chart.

The **Numeric Form Responses** is our initial support for such context specific chart insights. Users currently can get access to this additional enhanced chart insights if the chart they are viewing meets **all** of the following criteria:

- The chart is on the
**Form Data Analysis page or individual Form Analysis page** - The chart presents groups of numeric form responses. In particular, the form field that collects the responses needs to be a
**Rating**type. - The rating scale of the field must start at 0 or 1 and increment by a value of 1.

It can be observed from the row chart above that all of above-mentioned criteria are met, and the **Numeric Form Response** section should therefore be available as part of the chart insights.

The underlying **dataset** constructed for extracting the stats and insights in the **Numeric Form Response **section are different from the **Chart Stats **section. In particular, instead of constructing the **dataset **by collecting the **group values **(i.e. row values), the **dataset **used in the **Numeric Form Response **section is based on the actual underlying data values (i.e. individual response values) that are summarised by the groupings in the chart.

For example, from the row chart above, the **dataset** is constructed with the following data values: `3, 4, 4, 5, 5, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10`

Each value within this **dataset** represents a rating response submitted by a user. For example, 2 responses with ratings of '4' are represented as a `4, 4`

within the **dataset** since there are 2 users that submitted a rating of '4'.

Similar to the **Chart Stats** section, the stats summary and insights in the **Numeric Form Responses** section are then extracted from the constructed **dataset** depicted above**.** The following shows an example of currently supported stats insight in the **Numeric Form Responses** section.

The **Average** stats value `7.46`

listed above represents the average value of the response ratings collected, and it provides a good indication on if the received ratings are generally more toward the lower or higher end of the rating scale (i.e. 0 to 10). Additionally, users can utilise the insights supported in the **Chart Stats **section to better support the insights in the **Numeric Form Responses** section. For example, by combining the **Average** stats value `7.46`

in the **Numeric Form Responses** section and the **Average** stats value `3.36`

in the **Chart Stats** section, it potentially suggests the average rating value `7.46`

is strongly influenced by the rating responses received in `6, 7, 9`

rating value groups as the number of responses received in these ratings are significantly higher than the average number of responses received (i.e. `3.36`

) per rating value groups.

A list of currently supported **Numeric Form Responses** insight items are outlined below:

**Average:** The average of values in the **dataset**. Specifically, as described above, the values in the **dataset** are the underlying data values (i.e. individual rating responses collected) summarised in the charts.

For example, the average stats value `7.46`

listed above is calculated by `SUM (3, 4, 4, 5, 5, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10)/37 = 7.46`

**Standard Deviation: **Standard deviation is the average distance of all data points from the mean of the data set. That is, a higher standard deviation represents a data set that is more spread out.