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Using Dashboard Design Patterns To Increase User Engagement

Defining and using consistent dashboard visualization Patterns will improve User understanding and engagement.  What do I mean by Patterns?  Simply put, Patterns are the layout (type and placement of widgets) on your dashboards.  Why do layout Patterns matter?  Consistent placement and sizing of widgets will help your users orient themselves more quickly when they open a dashboard.  As a result, they are more at ease and more likely to stay engaged with your dashboards.
 
There are no absolute rules for dashboard design patterns, but here are a few concepts that I have found to be helpful:
  - Develop a few different layout patterns and use them repeatedly unless there is a strong reason to do otherwise.  
  - Use indicators at the top of the dashboard to show summary data if appropriate.
  - Show your detailed data in the appropriate widget type below the indicators.  Widget-type selection is not in the scope of this post.  There are many resources available online to help you with this.  One I like that Sisense also recommends is by Dr. Andrew Abela.  
  - Use colors consistently across your dashboards.
  -  You should also strive for consistency (one or several Patterns) in your dashboard filters.  Present the same filters in the same order when practical.  With consistent filter choices, your users will know what to expect when they open the dashboard and how to use the filters presented.
-  It is worthwhile to consider Dependent vs. Independent filters when establishing your filter patterns.  Dependent filters have the advantage of only showing selections that are valid for the parent filter choices.  Their disadvantage is that the child filters are reset each time a parent's choice is changed.  This can sometimes be annoying enough to the user to obviate their use.  Dependent filters also cannot be configured as Background filters.
 
Some concepts for layout Patterns are shown in the four enhanced wireframes below.
      
#1 - A top row of relevant indicators with detailed analysis below.  Note that the indicators are summaries of each line series in the chart.
kb-1557a864-5063-49d1-8b60-45dfaa394de5.png
#2 - A top row with a metric summary indicator.  A second indicator row with sub-summary metrics.  Details of these sub-summary metrics are presented in the stacked bar chart below.

kb-d988ad91-8106-4925-83d6-3debacf5d08a.png

#3 - A top row with 2 indicators with further detail right.  A bottom row of related detailed analysis.

kb-672204ea-5ebe-4299-b417-d508287cb3b7.png

 

#4 - Stacked indicators on the left with related detailed analysis directly right.  Also shown is a dashboard filter pattern that was used consistently across this analytics system.

kb-35aabfd0-4143-4dd1-9f47-f585d9348f3d.png
Sisense demo dashboards are also a good reference for dashboard layout.  You will notice a good bit of Pattern consistency across them.  In addition, there is an archived Dashboard Design webinar you may view on the Sisense website. 
 
In a graphic design reference I used many years ago, the key principles for good graphic design (I think we can agree that dashboards improve with good graphic design) were presented as a mnemonic:  CRAP.  CRAP refers to consistency, repetition, alignment, and position.  Over time, while I'm not a graphic designer, these simple ideas have helped me with several different graphic design-related activities.  My adaption of the CRAP principle for dashboards is:
  - Consistency:  Use consistent patterns on and across dashboards.
  - Repetition:     Reuse the same layouts and widgets.
  - Alignment:     Widgets that align are easier on the eye.
  - Position:         Place similar widgets in the same position across dashboards.
The good news is that Sisense's dashboard layout tools inherently support this approach. 
 
Consistent dashboard Patterns will also help speed up the development of new dashboards.  Always start with one of your existing patterns and you'll quickly have something to show that looks familiar and engaging to your users.  If an existing Pattern doesn't work for a dashboard, it's time to create a new one.
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