Embedded Analytics

How to Successfully White Label Analytics

By Ellis Carroll
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If you’re embedding analytics into existing software, white labeling is arguably one of the top requirements. Anything that strays from the established brand, no matter how small, can cause users to question the value of your product. Your goal is to create one cohesive brand experience. “The look and feel of the embedded analytics solution can directly impact the impression of the overall enterprise application and customer experience,” writes Gartner in the report, 5 Best Practices for Choosing an Embedded Analytics Platform Provider.

What is White Label Analytics?

White label analytics allows your software team to match your application’s fonts, colors, and branded design theme. It gives you the ability to make embedded analytics look like your application and not someone else’s. When done correctly, end users should not even realize they are interacting with a product designed by a different company. Your team should be able to adjust every aspect of the embedded analytics without worrying about a disjointed user experience.

3 Critical Elements of Successful White Labeling

Creating a cohesive experience means all of your elements need to follow existing branding, and those elements fall into three key areas:

  1. Styling. Our eyes react strongly to colors, and most of us can identify well-known brands just by the colors they use in their logos and platforms. If your customer’s brand color palette uses primary colors, you don’t want to create a dashboard entirely in pastels or neons. By sticking to your customer’s established palette, you ensure their users get a seamless—and familiar—experience.
  2. Fonts and language. Just as we associate colors and shades with branding, we also connect particular fonts and voice. Any change in font—be it the font itself, the size, or the styling—can be jarring for a user familiar with an established brand. Voice (a.k.a. the style of writing and vocabulary you use), should also be consistent. Your product should be indistinguishable from the vendor powering your analytics.
  3. Cross-platform consistency. Your design QA should involve checking your mobile and desktop experiences, and comparing to make sure they match. You don’t want to spend time ensuring you have brand consistency within a desktop platform, only to have your mobile experience be completely different. Your users should see the same branded colors, fonts, sizing, and templates on all platforms—not just one.

Creating a Seamless User Experience

A dashboard’s style is a visual cue to your users that what they’re using is an intentional part of an overall brand experience. Good white labeling means users can focus on the value of the dashboard, software, and analytics instead of getting distracted by the differences.

Key Takeaways

  • Brand consistency is important for successful white labeling.
  • Check language, design, style, and responsiveness to different platforms.
  • Users should not be confused about what brand they’re using.
  • A cohesive user experience leads to a higher adoption and usage rate.

Originally published February 19, 2020

About the Author

Ellis Carroll is a Customer Success Engineer at Logi Analytics. He is passionate about driving innovation and crafting meaningful experiences through modern technology and visual design.