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Embedded Analytics

6 Steps to Improve the UX of Your Embedded Analytics

By Michelle Gardner | November 27, 2018
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Application teams spend countless hours and thousands of dollars to perfect the user experience (UX) of their software products. But when it’s time to update the embedded analytics in their applications, they often rush through the design process to get new features out the door.

But if your dashboards and reports have a disappointing UX, user adoption and customer satisfaction can plummet. Fortunately, it really is never too late to improve your UX.

>> Related: UX Design for Embedded Analytics <<

Before your next release, use these best practices to create an analytics experience your users will love:

1. Form Your Personas

Creating a quality UX starts with understanding your end users. Start with a trusted group of existing customers—or, if you don’t have a product yet, tap into groups of prospective users in online communities.

Once you’re familiar with your target audience, break them down into personas. Each persona will be a percentage of your users who share common behaviors and activities. Start by looking at different company departments, teams, or people who share the same role. These may be your personas by default, but you might be surprised to find new groups when you look at the different ways people are using information.

2. Conduct Careful User Research

Continue laying the groundwork for an effective analytics UX by interviewing your personas. The only way to understand what your users need from your embedded analytics is to ask the right questions. This will help you decide what features and functionality will work for specific user segments, and you can then tailor the UX to these segments before a release (rather than having to make changes afterward).

These persona interviews will form the basis of your analytics design. Ask questions such as:

  • What does an average day or week on the job look like for you?
  • How do you currently use analytics and data in your work?
  • What metrics do you monitor? How do you measure performance?
  • In what situations will you be using embedded analytics in your application?
  • How do you prefer to absorb information?
  • What kinds of technical features are you comfortable using?

3. Focus on the Data Your Users Need—Not the Data That’s Available

One of the most common errors product teams make when designing their analytics experience is presenting the wrong data. This sometimes happens because application teams simply don’t know what data users want. Even more often, application teams default to presenting the data they already have on hand instead of finding out what data users need—regardless of whether it’s currently available or not.

The question about what data users need should be part of your user research. Find out early in the development process if you have that data on hand. If you don’t, start working now to gather and present that information.

4. Incorporate UX Design From the Start

Traditionally, design has been kept separate from the development and engineering processes and incorporated only near the end of the software lifecycle. But waiting until then to think about the user experience leads to analytics that is disparate from the rest of the application, impractical to use, or simply confuses your end users. By gathering user requirements and incorporating UX early in the product cycle, development teams are more likely to build dashboards and data visualizations that seamlessly match the rest of the application and are intuitive for end users.

5. Address the Whole User Experience—Not Just the Visuals

In a recent report, Augmenting Intelligence with Embedded Analytics, Nucleus Research predicts that by 2023, 90 percent of business users will interact with analytics at least once a day, but only 15 percent will realize it. That’s because the entire application experience— everything the user sees, including the embedded analytics—will not only look consistent, but also work together seamlessly. Users will receive information where they need it, when they need it. Their normal interactions with your application will extend into the embedded dashboards and reports without interrupting their workflows.

6. Choose an Analytics Platform That Puts You in Control

Many application teams turn to embedded analytics platforms to help them deliver cutting-edge dashboards and reports faster than they could build themselves. “But not all analytics platforms were built to be embedded,” writes Gartner in a new report. Some platforms restrict what application teams can build and what the end product looks like. That’s why it’s important to find a platform that gives you the ability to customize and white-label your analytics. This is essential to keeping users engaged and setting your application apart from the competition.

Get more design best practices in the ebook: UI for BI: Designing High-Impact Dashboards >

 

About the Author

Michelle Gardner is the Content Marketing Manager at Logi Analytics. She has over a decade of experience writing and editing content, with a specialty in software and technology.

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