BI Trends

5 Risks of Bad Embedded BI

By Michelle Gardner
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The question of embedding analytics in an application has moved from “Whether to?” to “How to?”—and pressure is mounting for application teams.

From the top down, CEOs are realizing the competitive edge they can gain by offering embedded analytics in their applications. At the same time, product managers are responding to user demands for sophisticated analytics capabilities and a seamless user experience between the application and the analytics embedded in it. And development teams are looking for solutions that let them customize the end result—with the added bonus of reducing the number of ad hoc requests they receive from users for analytics reports and dashboard enhancements.

>> Related: Get a Blueprint to Modern Analytics <<

To meet these demands, it’s no longer enough to simply embed analytics in your application. That’s become standard: In fact, 93 percent of applications currently have some form of embedded analytics. With so many applications offering embedded BI, no one stands out.

That’s why many application teams are recognizing that they need to update their embedded analytics or risk falling behind. Even companies that implemented a cutting-edge embedded BI solution a few years ago may now be realizing their once-great tool is no longer cutting it.


What Constitutes Bad Embedded BI?

If your application’s embedded analytics is making any of these BI mistakes, you might have bad BI in your product:

Inconsistent Branding: Delivering a consistent, familiar, and branded user experience means your customers will stay engaged in the application. If your embedded BI feels completely different than the rest of your application, it disrupts the overall experience and makes users feel like they’re in two totally unique applications.

Dumb-Pipe Syndrome: Analytics should not just show data—they should drive action. Many embedded BI instances act as a one-way street, gathering information and distributing it to end users. But they fail to let people take action on that information then and there by starting a new workflow or process, sharing insights with teammates, or updating the source database with new information without leaving the analytics interface.

Failure to Empower End Users: Application users don’t want to go back to your IT team with every new data question or visualization request—just like your IT team doesn’t want to handle every ad-hoc issue as they come up. Embedded BI should empower end users to ask new questions of their data, connect to new sources, and create new visualizations to extend the application so it fits their unique needs.


What Could Bad Embedded BI Cost You?

Regardless of whether you built your original embedded analytics in house or used a third-party vendor, many BI solutions inevitably become antiquated. Continuing to let an insufficient BI solution languish in your application puts your application at risk of the following:

1. Frustrated Users: 84 percent of end users want analytics within the applications they’re already using—but 66 percent say they have to switch from their usual business applications to separate tools to get the data or analysis they need. This “swivel chair effect” wastes up to two hours of productivity per worker each week and aggravates end users.

2. Frustrated Developers: Embedded BI isn’t just about pleasing your application’s end users. By adding sophisticated features such as embedded self-service analytics, 64 percent of companies were able reduce the number of ad hoc requests that clogged their developers’ backlogs.

3. Dismal User Engagement: Over 80 percent of application teams say they were able to increase the time spent in their applications just by adding or improving the embedded analytics in their applications.

4. Missed Revenue: Embedding sophisticated analytics capabilities (not just basic dashboards and reporting) means companies are 84 percent more likely to charge more for the analytics in their applications.

5. Lost Ground to the Competition: 78 percent of software vendors with a paid commercial application charge more for their embedded analytics. For companies that don’t charge for analytics, 55 percent said they can’t because their competition has a stronghold and they need analytics either to keep up or catch up.


Fortunately, you can mitigate these risks by thinking carefully about what analytics features can add value to your application. Learn more in this ebook: Beyond Embedded Analytics: 3 Sophisticated Features to Set Your Application Apart >


Originally published October 20, 2017; updated on May 31st, 2018

About the Author

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