On Clarisights, a visualization is called a 'widget', and each of the different types of widgets available is useful for a specific purpose. Here, we explain them with examples, sample use-cases and the constraints they carry. Data exploration features that almost all these visualizations support are filters, sorting and date override. You have the option to transform a widget from one type to another as well (currently in beta). Clarisights will prompt any missing metric or dimension requirements when transforming a widget. You can also limit the number of items to display on any widget by clicking the downward arrow at the top-right corner of the widget to make your visualization look clean and crisp.
Table is one of the most commonly used widgets in Clarisights. You can use the table widget to display data in rows and columns. It supports any number of metrics, dimensions and breakdowns. A number of data enhancements such as breakdowns, trends, aggregate, %-share and comparison are also supported in tables. Note that if you have added more than one dimension, then you wouldn't be able to add breakdowns in a table. You have a few style options as well such as changing the size of rows and alternating color of rows. Tables are best to see a snapshot of a large volume of data at once.
Pro Tip: You can enable trends in any column with the downward arrow on the column header to view a sparkline in each cell
The pivot table is used to visualise a summary of your data, so you can report on and explore trends based on your information. Pivot tables are particularly useful if you have long rows or columns that hold values you need to track the sums of and easily compare to one another. Style options let you adjust number of columns, row size, and alternate row colors. You also have more options to enable/disable trendlines, row and column aggregates and comparison.
A column chart displays data in the form of vertical bars. The dimensions you have chosen are represented on the horizontal axis while metrics are on vertical axes. Multiple metrics are supported, and you can visualize them with various style options like different colors for each metric, show or hide labels and move metrics into separate axes. Note that if you have added more than one dimension, then each combination of the multiple dimensions will be a separate value in the horizontal axis on the column chart. Breakdowns are not supported in column charts. Column charts are great when you want to visualize overall trends in aggregate metrics.
Area charts help you visualize data as the area covered below lines. Dimensions and metrics work the same way as a column chart. Breakdowns are not supported in area charts. Area charts are recommended when you want to compare the values of one metric with another over time - for example, cost v/s revenue. Multiple metrics are supported, and you can visualize them with various style options.
A horizontal chart is similar to a column chart with the difference that positions of dimensions and metrics swap - i.e. dimensions are on the vertical axis, while metrics are on the horizontal. Like a column chart, you can style metrics into different colors and axes. Breakdowns are not supported in a horizontal chart either.
Combo charts enable you to visualize lines, areas, and columns in the same widget. Style options include changing the axes, type of visualization (line, area, column) and colors. Dimensions and metrics work the same way as a column chart and breakdowns are not supported. Combo charts are best when you want to include dissimilar metrics in the same graph and look for correlations, for e.g. a ratio metric like CPC and a cumulative metric like Spend or Clicks.
If you'd like to visualize metrics over time, then timeline charts are recommended. It removes the hassle of adding/removing dimensions, and allows you to quickly switch between daily, weekly, monthly views etc. You can add metrics, filters, and style the metrics in the same way as a combo chart. Note that you can't change the sorting of a timeline chart, it's always sorted by ascending order of the chosen time dimension.
Breakdown charts are used to break-down a metric for different values of a dimension, and visualize these values over another dimension. You need to add only one dimension, one metric and one breakdown for this visualization. Filters are supported, but styling and sorting are not. A common example of a breakdown chart is CTR broken down by Channel, over Weeks, Countries or Product Categories etc.
Stacked charts are very similar to breakdown charts, in the sense that they help you visualize the value of a metric broken down across a dimension. You can also add a second metric to visualize it as a line graph across the dimension. Each breakdown value can be distinguished by the color of its section in the stack. Filters are supported but sorting is not. You can limit the number of stacks and enable 100% column view to visualize the percentage share of each stack with style options. All additional stacks are clubbed under "Others" keeping your visualization clean. Stacked charts are useful in cases like breaking down orders/leads by channel across time.
Pro Tip: Use 100% column view to compare percentage share of each stack in the chart across the main dimension.
Tiles help you look at aggregate values of KPIs at a glance. You can add filters and comparisons, but dimensions and breakdowns are not supported. They work best when you want to look at the overview performance of a channel or campaign type (web v/s app, brand v/s non-brand etc) quickly. You can also enable trends in more options of the tile widget to enable a sparkline in each tile that shows the values of the metric over days, weeks or months.
Pie charts are the classic way to show split of a metric across multiple dimension values. You can add one metric and one dimension in a pie chart, and filter out data that you don't deem useful. The slices are sorted by the metric by default. These are recommended as a quick visual way to show distribution of spend, conversions, revenue etc. across segments like channel, city, device etc. You can change the number of slices to be viewed in style options. All other slices are clubbed under "others".
A heat map visualizes a metric with differing color intensities to represent its values. You can create a heat map by adding two dimensions and one metric. The scale adjacent to the chart helps understand the correlation between the color darkness and the metric's value. Filtering data is supported, but sorting and breakdowns aren't. Heatmaps are most commonly used to visualize data when you want to understand the highs and lows of a metric across two dimensions. Learn more here.
A bubble chart is used to represent 3 elements in a chart. Here one bubble represents one dimension which is plotted corresponding to the values of selected two or three metrics (represented by two axes and the bubble radius). By default the first two metrics in order are the horizontal and vertical axes respectively and the last metric is represented by the bubble radius. Each bubble is a dimension value.
To learn more about its uses and application Click here
The funnel widget type is used to visualise the progressive reduction of data as it passes from one phase to another. You can use one dimension and any number of metrics of the same type (number, currency, etc)
The drop of vertical values here represent the percentage reduction in a dimension value as it passes to the next phase.
This type is used to enter a text as a widget in a report to include instructions on using a report, point out highlights or specific observations, etc. Learn more.