Using reports

The Dashboard page is where you can create fully customisable dashboards containing all of the charts and visuals in the platform that are most useful or relevant to them for this dataset.

Dashboards are specific to the dataset itself. Each user has a default dashboard automatically created, and you can create new, delete existing and edit existing dashboards too (the titles of the dashboards can be renamed to suit your use case).

This page is particularly useful when you have a live integration set up for the source(s) in your dataset, and you can periodically check in to see how things have changed over time.

As a default, each dashboard has a few example visuals already added, however, users have complete control over what gets shown on each dashboard.

You can customize a dashboard by adding (or removing) charts with your choice of filters applied, or specific data visuals from the Dataset settings page. You can also edit the filters applied to charts in the dashboard from within the dashboard itself.

You can also rename the dashboard by simply clicking the title and typing.

As you can edit multiple dashboards, you first need to ensure that you have the intended dashboard selected.

To select the right dashboard, go to the Dashboard page, select the drop-down in the top right-hand corner of the page, and select the dashboard you want to update.

When you go to Reports to add charts or visuals, they are added to the dashboard you just selected on the Dashboard page.

To rename any dashboard, simply click on its title at the top of the page, and type in the new name. This will then be reflected in the drop-down menu too.

As a default, a dashboard contains the default visuals shown below. These can all be removed, as you can see in the next section.

When you add a chart to a dashboard, the platform will intuitively try to fit it in the most obvious space available. If there is space to accommodate the default chart size, the platform will add the chart as close to the top of the page as it can.

When you add a chart from Reports with filters applied, you will see the icon (as shown below). You can click it to reveal which filters are applied. The icon will change to look like this: (as shown below).

To add or remove dashboard cards, click on the icon from the top right corner of the page, then select from the check-boxes the cards that you want to display:

The Recent message card also has some additional options available in the dashboard.

By clicking the icon in the top right-hand corner of this card, you are able to:

For any chart that you’ve added to a dashboard from the Reports page, you can click the icon in the corner of the chart to be taken to a view of that chart (with its applied filters) in the Reports page.

From there you can download an image of the chart or the underlying data, or you can click through to the underlying messages in Explore.

After a dashboard has been created, users have the option to edit or add further filters to their dashboard, depending on what they would like to achieve. Users can apply a global filter to their dashboard, augmenting all existing dashboards cards with a new filter. They can also edit individual card filters if they would like to update the existing filter without having to create a new card from scratch in Reports.

To add a global filter, navigate to the icon in the top right side of the Dashboards page. You will find it next to the delete icon.

To edit the existing filter on a card, you will find a similar filtering symbol in the top right side of each card.

The charts and visuals you add to a dashboard can be rearranged by clicking the top of the chart and dragging and dropping them wherever you want on the page.

The Dashboard page layout is defined by a column system – between 1 and 6 columns wide depending on the size of your screen. A smaller laptop screen may only fit 3 columns, whilst a much larger screen or TV could fit 6.

This means that, depending on how you resize them, the width of any of your charts will snap to be any number between 1 and 6 columns wide. If your screen only accommodates 3 columns, you could have a chart that is 1 column wide side by side with a chart that is 2 columns wide, or 3 that are 1 column wide, and so on.

Vertically, the charts can be whatever height you want.

Please Note:

To actually change the size of your charts is really simple. Just click on the small arrow icon in the bottom right hand corner of any chart and drag it to the column width or any height that you want.

The area surrounding the chart will be highlighted blue until the chart is the size that you want, and you release the mouse.

The blue area indicates the width that the chart will snap to, based on the number of available columns on your screen. Remember, your dashboard will be between one and six columns wide, depending on the width of your screen.

The tree map is a way of visually showing your taxonomy hierarchy, while also displaying quantities for each label via the area size.

Each root label is assigned a rectangular area with their leaf labels (sub-labels) displayed as rectangles nested inside of it. When a label count is assigned to a label, its area is displayed in proportion to that label count number and to the other quantities within the same parent category.

If you hover over a label name, it will highlight the label count and the percentage of messages that are predicted to have this label. The count figure, however, is a sum of probabilities. This means that if there are two messages and they both have the ‘Reason’ label predicted with a 50% confidence (0.5), then summed together this counts as 1 message.

When you click on a label name it will take you down a level to the leaf labels that are nested within. To get back to the top level you click on the bar at the top with the root label name:

This chart shows as default the top 10 highest volume leaf labels over the whole dataset. This is also calculated on a sum of probabilities of the predicted labels.

When sentiment is applied the chart will show both positive and negative labels. The top 10 is a split between the top 5 positive labels, and the top 5 unique negative labels.

This means that if the top negative label is already included in the top 5 positive labels, then it takes the next highest one as the top negative label and so on. This way the chart is always showing 10 unique labels.

The top X highest volume leaf labels table shows the same as the chart but in table format, with each label and corresponding label count. It defaults to show 10 labels, but you can adjust it to show the top 5 or 20 labels if preferred.

This is also calculated on a sum of probabilities of the predicted labels.

When sentiment is applied the table shows a split of the top 10 positive labels and the top 10 unique negative labels.

You can adjust the time sequence (i.e. daily, weekly, monthly, annually) of the chart period using the dropdown at the top of the Reports page or filter the chart to a specific time series using the filter bar or by selecting an area on the chart. See instructions on how to do so here.

The label volume trends chart shows the trend of the top 6 highest volume labels over the whole dataset as a default. As with the tree map, the percentage numbers are calculated as a sum of probabilities of predicted labels.

You can also filter the time period on this chart by using the dropdown menu or selecting the time period in the chart.

If you want to plot specific labels on this or other label specific charts, you can select those labels via the 'Charted labels' dropdown at the top of the page.

If sentiment analysis is enabled on your dataset, there will also be a label sentiment trend over time chart available in Trends.

The label trends table shows you how the top 10 labels for a given time period perform compared to the previous period and their change in rank.

The time series in scope is set by the user in the filter bar, and the time sequencing of the chart (i.e. daily, weekly, etc.) in the top right dropdown menu.

For the time period selected, the table shows the top 10 labels based on the sum of probabilities of predicted labels. It also highlights how those labels have changed in rank from the previous period.

If sentiment analysis is enabled, it totals covering both positive and negative sentiment labels.

By adjusting the time sequence filter, this is a useful way of seeing if there were spikes or dips in volumes in a certain label, or group of labels, in a given period.

For each time sequence it will show the following period:

The Segments tab shows charts of label volumes split by message metadata category (also known as user properties), as well as a chart with the associated top 6 labels for each of those categories.

When data is uploaded to the platform it normally contains metadata attached to each message. Some examples for different types of data include:

If the metadata can be grouped into categories (e.g. distinct sender domains), then a chart can be created showing the volume of messages, split by category (each sender domain).

The platform will load certain charts as default, some are hidden and listed at the top of the page. Simply click them to unhide them (see this article for more details).

The chart will limit the categories on the chart to the top 20. To the right of this chart will show the top 6 labels for each of those categories.

The Label volume chart shows the top 6 labels for each user property (category). For each label in that category it shows the percentage messages in that category that the label is predicted for. This is also a sum of probabilities of predicted labels.

Under the Segments tab you can’t create a chart from a category that is number based, with the exception of NPS score. If the metadata has numbers that have been categorised, say feedback scores of 1 to 5 or years, then it can be uploaded as string values and this would be shown in the Segments charts.

Where there are numeric properties such as monetary amounts, percentages, number of participants or recipients of an email, etc., then a chart will not be created but these can be used as filters.

This can be done by using the left-hand filter, and when applied the charts in segment will be filtered on these criteria:

To understand more about the user property filters, see here. To find out about advanced prediction filters for labels, see here.

At the top of the filter bar, users can toggle between Messages and Threads. This allows you to apply analytics at the level of conversations, instead of individual messages.

The threads filter is applicable for longer-form conversations like email threads, phone calls and live chats. Once the Threads filter is selected, the fifth Threads tab will become available.

The platform will display the threaded volume by number of messages, as well as the top label volumes by number of messages.

The number of messages is calculated by taking a count of the number of messages that are part of the same thread.

The platform will display the thread volume by duration, as well as the top label volumes by duration.

The thread duration is the time between the first and the last message that was sent in the thread.

The platform will display the thread volume by number of participants, as well as the label volume by number of participants.

The number of participants is calculated by adding up all parties 'to', 'from', 'cc', and 'bcc' (if the mailbox(es) attached as sources have been copied in).

The platform will display the thread volume by response time, as well as the label volume by response time.

The thread response time is calculated by checking how long it takes for the original sender of the message to receive a response (from someone other than the original sender).