What is Embedded Analytics?

Embedded Analytics
Feb 7, 2024
What is Embedded Analytics?

About 328 million terabytes of data are created each day. SaaS contributes a good chunk to this number. But what is the purpose of all that data if you don’t use it for greater good? Embedded analytics helps you turn the data you already have into valuable insights for your customers.

But why embedded analytics and how can this benefit your SaaS business? Let’s find out.

What is embedded analytics?

Embedded analytics is the seamless integration of analytics features into any business application: a software platform, web app, employee portal, or a public website. Product builders use embedded analytics tools to add customer-facing, real-time analytics to their digital products.

Embedded analytics tools bring your product data to life with visually appealing charts. Because the information is visual, your customers can digest and understand it in seconds.  With embedded analytics, exporting data tables to Excel for analysis is a relic of the past.

Customers love this embedded business intelligence evolution as it allows them to make more informed decisions about their product usage. 

Smart insights quickly become part of their daily workflows. Insights are no longer locked away in separate data platforms. Data is finally accessible, and its impact is enormous. With only a 10% increase in data accessibility, a typical Fortune 1000 company could see up to $65 million in net new income with data storytelling.

For SaaS products, IoT providers, and other cloud technology providers, this is a game-changer. Powerful insights are a strategic differentiator for their product. The more value your customers get, the more they will rely on and use your product, as they can do ad hoc data analysis and save time and money.

By giving your end users access to their data, you unlock new use cases for your app and help them become more data-driven in the process.

Benefits of embedded analytics

Before adding analytics capabilities to your app, you probably want to make sure that this is the right choice. The pricing for embedded analytics tools can be steep, and if you build in-house, you need developers who are anything but cheap. Here are some of the most important benefits of embedded analytics to consider before adding this feature to your app.

Generate new revenue streams

An analytics functionality can be incredibly useful for your end users. So much so that they will end up paying more for your product, either through an add-on or through a more expensive pricing plan. The bottom line is the same - you can monetize your app in new ways and quickly earn back the money spent on an analytics platform.

Here are some ways how adding analytics features to your tool can entice your customers to pay more for your app.

For example, your analytics feature can allow benchmarking so that they can compare sales results for different days, weeks, or quarters.

Another way you’re adding value that customers may want to pay for is by showing how your app impacts your end users. For example, if you have an electronic signature app, an embedded analytics dashboard can show your customers how many of their documents get signed and when. Having this feature will make it even easier for your sales team to convince prospects to sign and pay.

Competitive advantage

Adding embedded dashboards can improve the customer experience and give your product users the data insights they may be missing in their day-to-day workflows. Many times, your competitors don’t have features such as interactive reports, and adding these capabilities could help you steal some customers from your competition.

Shorter product cycles

Developing embedded analytics from scratch takes a lot of time and work. And perhaps worst of all, when developers are working on creating dashboards, they are not working on the main portion of your product.

But if you get an embedded analytics tool such as Luzmo, you get off-the-shelf analytics that you can just plug into your existing product. This can streamline the development process as developers can add dashboards to your app in days and not weeks or months. They can then spend their time working on the core features of your software application.

Increased platform usage

When you give users real-time data about how they use your app and how it benefits them, this can lead to even more platform usage.

Let’s say you offer an app for video streaming and your users can create and upload videos to the platform. An analytics dashboard can show them data such as:

  • Which videos get the most views
  • What the best time is for uploading
  • Where the attention of the video viewers first drops off
  • And much more

In short, all of these data points allow the platform user to optimize the way they interact with your app and get even better results. They can make data-driven decisions about how to use your app better, for uses such as forecasting, or monetizing the way they use your app in a better way.

Another example would be having a hosted PBX platform, where you could see which users made the most calls in a specific time period.

Embedded analytics vs traditional BI

Like traditional business intelligence, embedded analytics makes raw data insightful. However, there are some crucial differences in data analytics. Traditional BI approaches have a few major drawbacks:

  • Traditional business intelligence is managed by a data analyst, data engineer, or the IT team. It’s too complex for business users who can’t do data modeling or wrangle large datasets.
  • It separates data analysis from the existing business processes. When users have to switch between applications, the experience is clunky.
  • It is built to power conversations, not for direct and immediate actions
  • It lacks integration with other tools & business processes. As a result, data analysis is not accessible to most people.

Traditional BI has one core problem. It’s built to serve the C-suite, not business users. The core focus of BI is often to show the correlation of activity between business departments. Not necessarily to provide deeper insight into the activity they are doing.

If you want to get to these deeper, department-level insights with traditional BI, the typical process looks like this.  Data analysts work with a team of business users and collect their requirements. 

They don’t have the business expertise to get the right visualization quickly, so there is a lot of trial and error and a protracted revision process. 

Business users have little control over this process, other than giving feedback and waiting for the next revision. Overall, it’s a frustrating experience.

Unlike a traditional BI tool, an embedded analytics platform gives more control to your product user.

  • Dashboards are firmly embedded into the core workflows of the user.
  • Analysis & decision-making go hand-in-hand. It all happens in the same interface.
  • It unlocks information on a tactical level. Any business user can immediately take action on the data.
Embedded analytics vs traditional BI comparison grid

Why the embedded analytics market is growing

Traditional BI dominated the market for a long time. But today, product users need easier, self-service BI alternatives. Embedded analytics is bridging that gap. So it’s no wonder the embedded analytics market is predicted to grow between 10-15% CAGR in the coming years.

For SaaS products, it’s attractive because of the fast go-to-market. With global developer shortages, cloud vendors lack the resources to build data visualizations in-house. As a result, software execs are stepping away from the build-it-yourself model. Instead, they use off-the-shelf solutions because they are cheaper and more scalable.

Gartner quote about the importance of no-code and low-code tools for business intelligence

The 5 key features of good embedded analytics tools

Embedded analytics is an alternative to building analytics in-house from scratch. But there are many embedded analytics solutions out there, and not all are equal. Before you start evaluating the right solution for you, here are 5 areas to assess.

Seamless integration

A good embedded analytics tool seamlessly integrates with your product’s architecture. You won’t get the CTO or developers on board without a proper technical fit.

A couple of factors to assess:

  • Flexibility. Powerful embedded analytics building blocks are API-first. They allow for custom data connections, key features, or other customizations to cope with changing business needs.
  • Low-code. It should be easy to set up analytics inside existing workflows with limited code. Think of generating dashboard exports, executing queries, managing alerts, monitoring logs, etc.
  • Security. Leverage existing authentication and security mechanisms for your embedded dashboards. This keeps you in full control of security features and reduces strain on your developers.
  • Scalability & Performance with automation. Automated personalization on a mass scale. Especially when serving thousands of users while balancing performance.
  • Technology-agnostic. An embedded analytics component should be embeddable in any technology. No matter which development frameworks (Angular, Vue, React, etc.), data sources, or hosting services you use.
  • Responsiveness. The best dashboards are viewable on any device. Whether that’s on mobile, desktop, tablet, or a large monitor.
Illustration of embedding a dashboard into any software platform

Actionable insights

Your customers want more than insights. They want to take action, no matter if they run a CRM software or a branding agency. Analytics dashboards are most powerful when connected to a workflow. High-performance embedded analytics communicate with the core functions of your SaaS product.

Here are a few examples of what that might look like:

  • Action triggering. Customers trigger actions right from within a chart. For example, you’ve selected filters in your dashboard to show all products with an inventory below 10%, and you can immediately put in an order to stock up with one click on the dashboard.
  • Automated alerting. Send customers notifications when the data meets a certain threshold. For example, when occupancy of an event space hits 90%, you want to get alerted immediately to start doing crowd control.
  • Collaboration. Customers share and discuss insights with team members.
Illustration of embedded dashboards that immediately drive action

Smooth and easy user experience

Even if analytics is an add-on offering, it shouldn’t feel that way for customers. Offer everything – analytical insights included – in a single client-facing application for the best user experience. Playful, modern visualizations will create a wow factor and an increased engagement.

A good user experience means:

  • Single source of truth: Insight and action in one place. No separate portal for analytics or sending users to Excel to analyze data.
  • White-label analytics. Dashboards feel native to the platform they’re embedded in. They mirror your brand’s look & feel.
  • Contextual enrichment. Offer dashboards within the right context in the parent application. Help customers find the information they need faster, e.g. by adding a dashboard to your CRM tool.

Illustration of good analytics user experience

Fast, lightweight deployment

Embedded analytics tools speed up development. They help developers focus on their core tasks. Delight developers with:

  • Out-of-the-box data connectors with popular data sources or applications.
  • A low-code or no-code building block. You don’t need engineers to write complex code to add advanced analytical features to your application.
  • A plug-and-play setup. Drop analytics into existing applications with a few lines of code. With an API-first approach, developers can easily integrate analytics within any existing workflow.
  • A cloud-based environment. Deploying to the cloud with web-based analytics is more scalable and secure than on-premise deployment. Connect your dashboard directly to an app or a data warehouse for lightning-fast data access.

Embedded analytics tools shorten development cycles and will crush any delays related to analytics. And a faster deployment means faster ROI.

Illustration of fast analytics deployment


Customers don’t like complex interfaces. The best customer analytics experience is self-serve, with intuitive built-in capabilities:

  • Easy user interface for designers. Dashboards should be easy to create with drag-and-drop features in minutes. No need for advanced knowledge of data science or machine learning.
  • Intuitive interface for viewers. Dashboards should look appealing, and be interactive. With interactive dashboards, you can adapt to the device, language, and timezone of your customer.
  • Personalized insights. Customize dashboards based on your user role. Or even let them create their own dashboard variants with the metrics they need.

A self-service analytics interface lowers onboarding efforts and costs and increases customer adoption.

Illustration of an intuitive, self-service dashboard interface

Faster insights for everyone

Embedded analytics is all about creating a quicker time to insight and an engaging analytics experience. In changing times, everyone can benefit from more insight. 

Citizen data scientists are ready to take charge of their own data, but they need the tools to do so. With embedded analytics, your customers get the power to analyze data the way they want.

This situation is a win-win. As a SaaS provider, you have a lot to gain as well.  By delivering a better analytics experience and more insight, customers engage deeper with your product. Your software becomes a trusted advisor that customers return to again and again.

Are you ready to empower the success of your customers and your internal teams? Get in touch with our product experts for a free consultation or product tour.

Mieke Houbrechts

Mieke Houbrechts

Content Marketing Manager

Mieke Houbrechts is a long-time blog contributor and content marketing expert at Luzmo. Covering anything from embedded analytics trends, AI and tips and tricks for building stunning customer-facing visualizations, Mieke leans on her background in copywriting, digital marketing, and 7 years of industry knowledge in the business intelligence space.

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