Embedded Analytics: Definition, Tools and Features (2023 Guide)

July 17, 2023

Mieke Houbrechts

What are embedded analytics tools? Help your SaaS users make better decisions faster with these 5 must-have capabilities.

We generate billions of data points every day. In 2020, people created 1.7 MB of data every second. Your SaaS product may be resting on a mile-high pile of data. And your customers need that data to make smarter decisions. But transforming raw data into useful insights takes time and resources.

Luckily, it doesn’t have to be so difficult. Read on to discover how you can turn your customers into superheroes with embedded analytics!

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 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. 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. And 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.

Illustration of embedded analytics tools

Embedded analytics software use cases

Data is everywhere and people want to make better decisions all the time. Not only at work but also in their personal life. Data is already rooted in our daily lives. Embedded analytics makes it accessible to anyone.

Typical use cases include:

  • B2B Software-as-a-Service (or SaaS) vendors offer intuitive reporting add-ons to their end users and customers.
  • Enterprises use dashboards as an internal information stream to collaborate between departments.
  • Direct-to-consumer organizations innovate interactions with their customers, members, employees, or followers.

Even if consumer apps aren’t the first thing on your mind, there are plenty of use cases:

Consumer insights in banking apps, educational apps, crowd management, health apps, and more.

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.
  • 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 for 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.

When they build for a department-level insight, it looks something like this. Data analysts deploy into a team of business users and collect 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 the process. 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

Top embedded analytics tools in 2023

There is quite a bit of demand for self-service BI tools with an embedded function. However, choosing the right one as a product manager can be a burden. Here are some of the top alternatives to consider.

Luzmo - built exclusively for embedded analytics in SaaS products. Instead of taking weeks or months to build an analytics dashboard, you can create one in Luzmo in hours and have it up and running for your customers. 

Sisense - a very capable business analytics tool that has a ton of options for dashboard customization, as well as a wide range of visualization types. The downside is that Sisense is not as easy to embed as most other competitors on the list.

Microsoft Power BI - a common choice for data analysts and data scientists working on-premises, but it also works in the cloud. It offers an immense number of features, from data modeling, predictive analytics, data analytics and more. However, much like Sisense, Power BI is difficult to embed and view for your users.

Tableau - a heavyweight in the BI world and one of the best embedded analytics offers out there. If you’re doing data analysis and visualizations, it’s a very capable tool that will meet 99% of your needs. However, the embedding requires custom formulas and calculations, which means you’ll need an extra set of hands in the development team.

Looker - Google’s own product is a business intelligence solution that is best suited for reporting and dashboards. For an embedded use case, the problem is the price (clocking in at around $33k per year) and the fact that you end up paying for each dashboard viewer, making this one of the costlier solutions out there. Also, single-sign-on is really not an option, despite the claims they make on their website.

Domo - a newcomer in the market, coming equipped with plenty of widgets and options for data visualization. Despite its great looks, Domo is not the most intuitive tool to use for embedded analytics, e.g. for embedding a dashboard or giving out permissions to customers to view it.

A growing embedded analytics market

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 demand for better customer experience

But the rising success of embedded analytics goes beyond easy deployment. Analytics is a crucial part of the customer experience too. Customers expect more data-driven insights than ever. With embedded analytics capabilities, they finally get access to relevant information in their daily workflow, in real-time.

This is an immense opportunity for technology vendors. They can deepen engagement with product users and in many cases, monetize data they were already collecting.

The rise of embedded analytics is a win-win situation. Both SaaS vendors and their customers can work more productively while generating new revenue.

The 5 key features of good embedded analytics tools

Embedded analytics is an alternative to building analytics in-house from scratch. But not all embedded analytics solutions are equal. Before you embark on the journey, 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 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.
  • Automated alerting. Send customers notifications when the data meets a certain threshold.
  • 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 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, light-weight 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.
  • 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 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.

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