Best Practices for Customer-Facing Analytics Dashboards

Learn the best practices when designing your customer-facing analytics dashboards, as well as some common antipattern practices to avoid.

Abstract dashboard

Photo by Propel

An analytics dashboard is a visual tool to display metrics, insights, and key performance indicators (KPIs). It's designed answer questions by identifying trends from historical data sets, predicting outcomes, and shaping future decisions. For example, such a dashboard might display Google Analytics, ad spend per channel, revenue generated per channel, and total ad spend vs. ad sales.

Analytics dashboards aren't open-ended; they're designed to express an opinion about their subject, especially in customer-facing products. They enable customers to efficiently track data insights and performance, then share the results with your team. However, you must ensure your dashboard is designed properly so that it provides the insights and value you need in a way that all team members can easily understand.

This article will examine some best practices to follow when designing your product analytics dashboard, as well as some common antipattern practices to avoid.

Why Does Your Product Need an Analytics Dashboard?

Example Dashboard
Example Dashboard - Image courtesy of dribbble.com

With the vast and ever-increasing amounts of data available to users today, choosing what data to prioritize can be very challenging. That’s where user analytics data and dashboards come in. An analytics dashboard helps your users choose optimal options by providing them with relevant information.

An analytics dashboard should be able to:

  • Show users what they have achieved so far and proximity to their end goal: Users tend to have a goal or set of goals they want to achieve when using a product, an analytics dashboard should make tracking those goals easier. An example would be a car hailing app for riders, showing a metric like number of completed trips. This would be beneficial to the rider as they may have a set goal for the number of trips they want to complete.
  • Show useful information to users: The dashboard should display useful information beneficial to users. For example, a sleep tracking app should show useful information such as sleep duration, sleep quality, sleep quality etc. 
  • Communicate information effectively: Information displayed by a dashboard should be communicated effectively to users. For example, a bank app displaying the number of transactions should not only display the total but should also be able to display the number of transactions based on different time periods.

Effective analytics dashboard designs help your users become more engaged with your product. This greatly contributes to the success of your product since the end users are the final consumers and the more engaging your product is the more likely they'll continue to use it. Obtaining relevant metrics that are useful to your users is the end goal; it’s a continual process that should keep improving over time.

How to Design Your Customer-Facing Analytics Dashboard

Your analytics dashboard should be able to build a narrative around the data, answering the key questions your customers have, and delivering the key message in a clear and compelling way through insights and analysis. The following sections highlight some common best practices that can help you achieve these goals.

Consider Your Audience

First and foremost, know your audience and build with your audience in mind. Some points to consider might involve asking the following questions to guide your dashboard development:

  • How will the dashboard be used? Users may choose to take different actions to maintain or improve business performance based on the insights displayed on the dashboard.
  • What KPIs or other information do users need? For example, a KPI of total number of sales per month may be important for stakeholders to measure over time and should be displayed prominently on the dashboard.
  • How much detail do users need? You should be able to adjust the level of detail displayed depending on what end users require.

Consider The Question You Want to Answer For Your Customer

When deciding which features to include in a dashboard, there are many factors that need to be considered. Every industry has a different way of operating, so providing a standard set of guidelines that will be suitable for every dashboard is difficult. Regardless, you want to use your dashboard to show your customers what's most beneficial to them. So, you should start by considering the question you want to answer for your customer. For instance, if it’s a fitness app, you may want to consider answering questions like what are the users’ number of daily steps, calories consumed, calories burned etc. For banking apps, you may consider answering questions like what are the users’ total transactions over a time period, total amount debited, total amount credited etc. 

Create a Sketch

Before you start building your dashboard, you should have a sketch, either hand-drawn or software-generated, to provide a complete picture of the design pattern. Your sketch will ensure that you follow these principles:

  • Your dashboard should tell a story but shouldn't overwhelm users with too much information, clutter, or noise.
  • You should limit the content to fit entirely on one screen.
  • You should only display three to five key values, charts, or tables. If more detailed tables are necessary, place them on the bottom of the dashboard.
  • When building your dashboard, start from the upper bottom and create it in a "Z" field of vision, in which the most important metrics are placed on the top corners from left to right.

Choose Colors Intentionally

You shouldn't use multiple colors on each page. Not only is that poor design, but it can distract users. Each color you use should have a specific meaning. This way, users will automatically associate that color with the same or similar information at other places in the dashboard. Such a strategy offers better visibility, simpler navigation, and a more striking design.

Use Clear, Readable Wording

The fonts you choose should be easily readable and displayed in a large enough size that users can clearly read the text.

Change the Background

Choose a background theme that offers an appealing first impression to users. It should offer an eye-catching visual without overwhelming the text.

Choose Proper Visuals

To give proper context to the data analysis, be sure to display the data in the most appropriate way for your use case. For example, bar charts can compare multiple categories or values that change over time:

Bar Chart
Bar Chart

Line charts can present a graphical representation of data or display trends:

Line Chart
Line Chart

Keep Font and Type Sizes Consistent

To ensure a uniform look, use one font everywhere and maintain two standard font sizes across the dashboard page.

Align All Elements

Keep your layout and charts well aligned so that they're centered on the page and not distorted or scattered.

Use Icons and Images

Icons and images will also catch the user's eye and help explain the analytics. In the diagram below, the metric in the top right for the quantity of trucks used can be seen as more relatable when the truck icon is used to explain context:

Icons and Images
Icons and Images - Image courtesy of powerbiexperience.com

Good Example Dashboards

The following images created in Bootcamp demonstrate good dashboard design practices:

Example Dashboard
Example Dashboard - Image courtesy of powerbiexperience
Example Dashboard 2
Example Dashboard 2 - Designed and built by the author and cropped from Power BI

As you can see, these dashboards follow several good design principles:

  • The dashboards offer clean, appealing visuals.
  • The colors blend together well and stay consistent across the page.
  • The visual elements are carefully placed on the page and only a few fonts are used.
  • The most necessary KPIs are featured most prominently, using bold text and numbers.

Bad Example Dashboards

If you don't follow best practices for design, you could end up with an analytics dashboard that is unappealing and lacks coherence. Design antipatterns can reflect badly on your organization and increase confusion among your users. The examples below demonstrate dashboards created with bad design practices:

Bad dashboard 1
Bad dashboard 1 - Image courtesy of Matillion
Bad dashboard 2
Bad dashboard 2 - Image courtesy of Sisense

You should be able to identify a number of bad design practices and antipatterns:

  • Poor background quality
  • Inconsistent color scheme
  • Inconsistent alignment of visuals, leading to poor organization
  • Too many widgets, creating visual clutter

These dashboards could be improved by applying the following design principles:

  • Arrange the most important insights at the top of the dashboard. Any relevant trends can be spotlighted in the middle, with more details at the bottom. This makes it easier for the audience to quickly read through without struggle.
  • Avoid the clutter of too many visuals on the dashboard. As noted earlier, three to five items per page is ideal.
  • Improve visibility with vibrant background colors. This communicates confidence and control.

Conclusion 

A customer-facing analytics dashboard can provide key data insights for more informed decision-making, which better positions your organization for success. To maximize the effectiveness of your dashboard, though, you need to ensure that it's designed well.

By applying the best practices listed in this article, you'll help ensure that users will be able to quickly identify and act on vital information. This will enable you to find ways to further grow the user-base of your product.

To empower your customers to analyze and use your data most effectively, try Propel Data. Propel is an Analytics API that for product companies to build customer-facing analytics in record time. Propel works well with your existing data stack without having to build new data pipelines or aggregations. Join the waitlist to learn more.

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