This simple guide will walk you through each type of data widget available in the NinjaCat Template builder, and, complete with examples and use cases will enable you to decide which type of data widget best tells your data story.
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Table Widgets
The most versatile of the data widgets, and tables allow you to drill down into your data in great detail. Dimension & metric combination limits aside, there are almost infinite ways you can choose to display your data in tables. If using a dashboard, you don't need to think about results limits, as all results within your data range will be available to view, so think about offering your readers a greater range of data for them to witness trends through time. Table widgets are a great way to include metrics split out by Dimensions. They give you the best opportunity to segment your data and present a high level of granular information. They are a great way to present a specific chapter in your data story, by sorting the data, for example, to highlight the best campaign performance by impressions, or impressions over the course of a week/month.
You can segment the data by a huge variety of dimensions, depending on the data source(s) you use.
Requirements
- Minimum 1 data source
- Minimum 1 dimension
- Minimum 1 metric
Specific Features
- 1 or more data sources can be used
- 1 or more dimensions can be included: network-specific, aggregate, custom, or a combination of all.
- 1 or more metrics can be included: network-specific, aggregate, custom, global, or a combination of all.
- Rows can be shown as totaled or not
- Tables can be run over multiple report pages.
Pivot Table Widgets
Because of the way data is presented in pivot tables, you may only use one dimension. Consider using a custom dimension if your chosen dimension isn't available in the aggregate list when using more than one data source. Pivot Tables are a great way to include metrics split out by a single Dimension. They are a great way to present trending data, for example, a 6-month overview of performance.
Requirements
- Minimum 1 data source
- Must contain only 1 dimension
- Minimum 1 metric
Specific Features
- 1 or more data sources can be used.
- Only 1 Dimension can be used. This is used to segment the data into columns.
- 1 or more Metrics can be included: network-specific, aggregate, custom, global, or a combination of all. Each metric will represent a line in your pivot table.
Scorecard Widgets
Scorecards are the simplest of data widgets. They can still be filtered to drill down into data sets. Use the comparison feature available to take advantage of a bird's eye view of the performance of a handful of key metrics. Scorecard widgets are a great way to include metric-only data. Scorecards are typically used for headline data which may then be drilled down into tables or charts. They are a great way to shout out specific metrics.
Values included can be displayed in groups either horizontally or vertically, customizing the number of metrics per row, or, individually.
Requirements
- Minimum 1 data source
- Minimum 1 metric
Specific Features
- 1 or more data sources can be used
- 1 or more metrics can be included: network-specific, aggregate, custom, global, or a combination of all.
- No dimensions required
Chart Widget Overview
Chart Widgets are a great way to present data in a more visual way. They give you a fabulous opportunity to display one or more metrics, usually segmented by no more than 2 Dimensions. They are great for helping clients visualize data and fantastic for displaying trending data.
You can segment the data by a huge variety of dimensions, depending on the data source(s) you use.
Requirements
- Minimum 1 data source
- Minimum 1 dimension
- Minimum 1 metric
Common Chart Features
- 1 or more data sources can be used
- 1 or more dimensions can be included, network-specific, aggregate, custom, or a combination of all. (The best practice is not to use too many, and this is dependent on the chart type you choose)
- 1 or more metrics can be included, network-specific, aggregate, custom, global, or a combination of all.
- Comparison data can be included, this works best with line, scatter, bar, and column charts.
- Chart types are fluid - if you begin building in one type, and then realize there may be a better alternative, you can change it with one click rather than rebuilding the widget.
Below are some simple examples of each chart type to help you choose which might help tell your data story the best.
Column Chart
NinjaNote: If using more than one metric, consider using multiple Y-axis in your charts to present your data story more clearly - as an example, it would be challenging for a viewer to identify the number of clicks when on the same axis as the number of impressions.
Bar Chart
NinjaNote: If using the Date Dimension, be sure to check out the date consolidation options in the Inspector. This allows you to choose to consolidate data by days, weeks, months, or even years, depending on which is the most relevant to your data story.
Line Chart
NinjaNote: Consider using this graph type if you like the simplistic aesthetic of the scatter plot chart but want to include more metrics as linked points are easier to interpret if the graph is noisier than single plot points and easier to differentiate between than on something like one of the area chart types.
Spline Chart
NinjaNote: Consider using this graph type if you like the simplistic aesthetic of the line graph, but want a more fluid curved line than a point-to-point.
Area Chart
NinjaNote: Consider using this graph type if you're comparing a couple of metrics. If you're unable to see one because it is obscured by another, consider re-ordering the metrics in the list in the widget inspector. For example, always select Impressions before Clicks, as there are likely to be far more Impressions than Clicks. By ordering Impressions first, the Impressions area block will be the furthest back on the graph, and Clicks with lower values will appear at the front rather than being obscured.
Spline Area Chart
NinjaNote: Consider using this graph type if you like the aesthetic of the spline graph, but want a more fluid curved filled-in area than a simple line.
Scatter Plot Chart
NinjaNote: Ensure the colors you're using are easy to identify and link to your legend. These are set up at either the widget level or global settings. Consider using no more than 4 metrics (or 2 if you're using comparisons) to eliminate noise on the graph and keep your audience engaged in your data story.
Pie Chart
NinjaNote: Donut Charts are achievable by selecting a Pie Chart and then adjusting the "Donut Width" option in the widget properties
NinjaNote: Although you can combine many data sources, stick to one dimension and one metric only. The simplest of the graph types in some ways, and a great one to combine with other data widgets. Consider using the donut feature on this graph type to create a space in the middle where you could use a scorecard to highlight a specific figure from the data set.
Cluster Map
NinjaNote: The Cluster Map widget pulls results from multiple location-centric dimensions. The "Country" and "City" dimensions pull data by text matching for the names of locations. Because many different locations share text groupings and full names results may vary unexpectedly. We suggest that this widget only be used with data sources that use more specific location dimensions. (e.g. "Zip Code", "Lattitude", "Longitude")
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