Embedded Analytics

How Is Embedded Analytics Different From Traditional BI?

Last Updated:
November 16, 2022
How Is Embedded Analytics Different From Traditional BI?

Embedded analytics has received a lot of buzz over the past few years as organizations of all sizes and technical backgrounds are inundated with more data than ever before.  To understand how the trend is helping companies implement more accessible data strategies, it’s important to look at the ways in which embedded analytics differs from traditional business intelligence (BI) software. 

Traditional Business Intelligence

Business intelligence has provided organizations with the tools needed to make data-driven decisions for decades.  Traditionally, the systems that collect, store, and analyze company data have been primarily utilized by technical teams of data scientists and analysts who are well versed in the craft of extracting meaningful insights from disparate sources of information. 

This works well if analytics is your area of expertise, but it’s just as important to ask how BI can serve a broader audience, such as:

  • the average manager that needs to examine key performance indicators (KPIs)
  • individual contributors that lack visibility into whether or not their work meets critical standards
  • decision-makers that must understand return on investment (ROI) before making purchasing decisions 

Traditional BI frequently fails to provide timely answers to these and other important questions because it is often  inaccessible to nontechnical stakeholders. As our data-driven culture continues to grow, businesses need real-time visibility into information that is easily digestible by a larger percentage of the workforce and accessible without having to go through the data and BI teams.  Likewise, the data and BI teams cannot scale and level up their reporting strategy if they are constantly fielding common data requests.

As a result, many innovative organizations are implementing a solution that allows BI to have greater application in day-to-day operations: embedded analytics.

What is embedded analytics? 

Embedded analytics is the integration of analytical capabilities and data visualizations within another website, application, portal or workflow. Traditional business intelligence applications are often standalone solutions that require users to navigate away from their native product offerings in order to access the analytical dashboards that transform their backend data into crucial insights.

With embedded analytics, data visualizations can be rendered “within a user's natural workflow, without the need to toggle to another application.” (Gartner)  This provides organizations with access to pertinent information without disrupting existing business operations and processes. 

Examples of embedded analytics

Today, many SaaS (software as a service) providers offer some form of embedded analytics for their user base.  These are often so intuitively integrated within the platform that nontechnical users may not realize they are interacting with analytics.  For example, many email campaign platforms, such as MailChimp, offer visualizations that display an email’s open and click-rate conversion metrics—allowing marketing managers to quickly assess performance and make critical decisions on how to improve the success rate of these numbers. 

On a larger scale, many SaaS vendors partner with an embedded analytics provider to supply their users with reporting capabilities.  This eliminates the need to build an in-house analytics solution and makes for a stickier relationship if subscribers are able to gain valuable business insights that drive operational efficiency. 


Here’s a quick recap of what we’ve covered so far: 

Traditional Business Intelligence

  • Non-flexible
  • Inaccessible to many teams
  • Requires navigation between multiple applications

Embedded Analytics

  • Flexible
  • Accessible to non-technical stakeholders
  • Reports rendered in the applications/portals that users are already accustomed to using

To embed is to implant within something else so it becomes an ingrained or essential characteristic of it.  Embedded analytics offers an opportunity for data visualizations and reports to be rendered inside of the applications that teams use most often—making data analysis an accessible and inherent part of day-to-day business operations. 

This is part one of our embed series. Next month, we’ll take a look at why you should consider embedded analytics for your organization. 

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