Embedded analytics lets end-users of your product get immediate data insights. For example, when you log into Instagram and see a dashboard showing how much time you spend in the app, this is an example of embedded analytics.
In this article, you’ll learn everything you need to know about embedded analytics and an alternative method for getting custom user-facing analytics into your app—without dedicating sprints of developer time to building and maintaining it yourself. You’ll also hear experts’ advice for creating user-facing analytics.
Build remarkable, fast, and fully bespoke customer-facing analytics experiences in 10% of the time. Get access to Embeddable today.
What is embedded analytics?
Embedded analytics refers to building dashboards and other analytics in a third-party tool and then rendering it inside your own application.
Often, the existing app’s primary function is something other than analytics—but the embedded charts provide the user with valuable insights to complement the core value proposition of the app.
Rather than building analytics capabilities into your app from scratch (a big time commitment), you’d pay for a third-party tool and use an iFrame or JS snippet to simply embed the component. For example, if your product is an e-commerce platform for independent sellers, you could embed an analytics feature that gives users real-time stats like profile views, revenue, and buyer location.
That’s just one example of user-facing analytics you could embed. There are plenty of use cases for SaaS applications that could bring value to the end user but don’t warrant the time and complexity of developing the whole analytics experience from scratch.
On Shopify, sellers can track metrics like total sales and average order value using the platform’s interactive user-facing analytics solution.
Top four benefits of embedded analytics
Using an embedded analytics solution rather than building the feature from scratch has one significant benefit for your dev team—time-saving. Whether embedded or not, user-facing analytics greatly benefit your business.
They can help you:
1. Communicate the value of your product
Giving makers visibility over metrics like page visits, revenue, and customer ratings makes it easy for them to see how the platform enhances the reach of their business. In many cases, embedding analytics will add value to your product.
In other cases, showcasing the product’s value is more important. “For me, it’s about giving the user confidence in your product,” says Shruti Bhat, Chief Product Officer & SVP of Marketing at Rockset, a search and analytics database
.Let’s go back to the indie maker’s e-commerce platform. An app like that gives creatives somewhere to sell their products, increase their visibility, and even handle payments. It’s an asset, but how well do makers understand its value? What keeps them returning to this platform instead of switching to another with similar features?
2. Increase engagement and retention
Like all helpful features, customer-facing analytics can keep users engaged with your app by giving them another reason to spend time on the platform.
The key is knowing whether analytics functionality is something they actually want from you and how you can deliver it in a way that helps solve their problems.
At Rockset, Shruti tells us, customers get access to real-time metrics showing activity and performance data, “Not only does the customer have more confidence in the product, but they’re also able to visualize the usage, understand it, analyze it, and make decisions to optimize it,” she explains.
These actionable insights encourage users to get more out of the platform and keep using it, boosting retention. That’s why customer-facing analytics makes it onto many product teams’ roadmaps and why many teams opt to use embedded analytics tools to help deliver value to the user.
3. Create shareable content
Businesses that know the value of user-generated content (UGC) definitely have a competitive advantage. People share UGC all over the internet and most consumers seem to trust it more than advertising.
Spotify taught us that you can nudge users to share content that feels user-generated just by giving them shareable, personalized visual assets (hello, Spotify’s annual stats showcase: Wrapped).
Spotify’s data visualizations are essentially personalized snapshots of user activity that can be used to celebrate milestones and achievements (or even music taste). So, if you’re looking to replicate their success, the more shareable, visually appealing, and customizable your data analytics are, the more reach it will give to your product.
Spotify Wrapped is a very successful example of using data analytics and UGC to deliver an engaging customer experience that raises brand visibility.
4. Create new revenue streams and boost your bottom line
It’s simple: Giving your customers more ways to engage with your product and use it to solve their problems will boost customer satisfaction, raise your reputation, and drive new revenue streams. But that’s not all.
You can also choose how much, if any, analytics are available to each tier of your pricing plan. Some SaaS companies monetize this feature by placing more advanced analytics behind a paywall. Bigger clients with more capital to spend on the right solution will happily pay more to access analytics that support their success, meaning increased revenue for your company.
“If the user is happy, they use more of the product. We’re always looking to make sure the user is happy because happy users recommend your product to other users.”—Shruti Bhat, Chief Product Officer & SVP Marketing at Rockset.
The best embedded analytics tools and applications to consider in 2025
Traditional business intelligence tools such as Power BI and Tableau have made their attempts to build analytics dashboards that can be easily embedded into just about anything. However, many great embedded analytics software options do a much better job.
We'll give you a rundown of both so you can make an educated choice, but if you want to get a more detailed overview, check out our list of the best embedded analytics tools.
Embeddable
Embeddable is a developer-first embedded analytics tool for building lightning-fast customer-facing dashboards. It is headless by design, which gives you complete control over your user experience, and a performant data service to ensure that it loads fast, too.
Embeddable is an excellent choice if you need…
- Dashboards that load lightning fast
- A fully customizable look and feel that matches the rest of your product and website
- You want to be able to scale your analytics experience as your product grows
- A vast choice of chart types, compared to just about any BI tool in the market
- Easy embedding without using iframes
- Row-level security, multi-tenant support, built-in semantic later, configurable cache, React SDK, end-user self-serve
In short, you get a tool that was built with embedded analytics in mind first, unlike platforms that are BI tools with an embedded option as an afterthought.
Sign up and get access to Embeddable today.
Looker
Looker, now part of Google Cloud, is a business intelligence platform that enables embedded analytics and data exploration. Its unique modeling layer ensures consistent data metrics across applications. Looker integrates with various databases and cloud data warehouses, offering real-time insights and interactive dashboards.
With an API-first approach, it’s highly flexible for developers who want to embed analytics into their products. It’s ideal for businesses that need scalable, data-driven experiences. However, note that this embedded analytics solution can be expensive, especially for a large number of business users.
Power BI
Microsoft’s Power BI is a leading business intelligence tool with strong embedded analytics capabilities. With Power BI Embedded, companies can add interactive reports and dashboards to their applications. It connects seamlessly with Microsoft products and supports real-time data analysis.
AI-powered actionable insights, natural language queries, and customizable visualizations make it a powerful tool. While it offers deep analytics, it may require technical expertise to set up and manage. The embedded BI portion of this tool may call for a few seasoned developers to pull it off well.
Tableau
Tableau is a well-known analytics platform that specializes in data visualization. Its embedded analytics feature allows businesses to integrate interactive dashboards into their applications, giving users self-service analytics.
Tableau connects to various data sources, offers AI-driven insights, and provides extensive filtering and customization options. It’s a great choice for companies that prioritize beautiful, interactive visualizations and want to give customers access to real-time data.
Sisense
Sisense is an embedded analytics platform built for developers and data teams who need advanced analytics within their applications. It provides white-labeled dashboards, AI-powered insights, and real-time reporting. Sisense’s in-chip technology ensures fast performance, even with large datasets.
With its API-driven approach, businesses can customize analytics to fit seamlessly into their software, making it a great option for companies that want deep, embedded data capabilities.
RevealBI
RevealBI, created by Infragistics, is a user-friendly embedded analytics platform. It allows businesses to add real-time data visualizations, interactive dashboards, and reports to their applications. With support for multiple data sources and strong customization options, RevealBI helps businesses provide customers with self-service analytics.
It’s designed for both technical and non-technical users, making it a solid choice for companies looking for an easy-to-implement analytics solution.
Explo
Explo is a lightweight embedded analytics platform designed for fast and simple integration. It offers pre-built dashboards, easy customization, and a straightforward API for embedding reports. Unlike traditional BI tools, Explo is designed to be developer-friendly, allowing teams to quickly launch analytics features without complex infrastructure.
With built-in data transformations and access controls, Explo is perfect for startups and SaaS companies looking for a hassle-free way to add analytics to their products.
Embedded analytics examples to learn from
For a more detailed rundown, explore our article on user-facing analytics examples. However, here are a few short illustrations on how the right embedded analytics solution can work for you.
- Stripe – Stripe’s dashboard gives businesses a quick look at their payments, showing total revenue, net earnings, and trends over time. This helps users analyze data and stay on top of their finances without extra effort.
- Squarespace – The website builder includes built-in analytics so users can see how much traffic their site gets, where visitors are coming from, and which pages are performing best—all without needing Google Analytics.
- Spotify Wrapped – Every year, Spotify Wrapped gives users a fun breakdown of their listening habits, including their top songs and artists. It’s a perfect example of analytics used for engagement, as people love sharing their results.
- Mailchimp – Mailchimp provides detailed reports on email campaigns, showing open rates, click-through rates, and subscriber activity. This helps users see what’s working and adjust their marketing efforts accordingly.
- Intercom – Intercom’s customer support platform includes analytics on response times, user engagement, and conversation trends. Businesses can use this data to improve customer interactions and support efficiency.
- Shopify – Shopify’s dashboard gives store owners an easy way to track sales, customer behavior, and inventory trends. Instead of guessing, sellers can see what’s selling and what’s not, helping them make smarter business decisions.
How to add customer-facing analytics to your app
Until recently, there were only two options for getting customer-facing analytics into apps: building it yourself or embedding a third-party BI solution. But both have drawbacks.
Firstly, analytics are complex - and building them manually into your application takes time. The architectural decision to build in-house means every change you ever want to make, or that customers request, will have to go through product, dev and QA. That’s even more expensive when you factor in the opportunity cost of not developing other features.
On top of the initial build, you must consider factors like performance and data security. It’ll be a complex project that wastes your dev team’s time and could cost a fortune.
An embeddable solution is typically much faster to deploy and can be cheaper, depending on which solution you choose. The problem is that with most embedded analytics platforms, you only get access to very basic, non-customizable components. This will make your visualizations quite limited (think: very basic reports and graphs) and you won’t be able to create a powerful customer experience that’s unique to your brand.
We should know: Our other product, Trevor.io, works great for its intended purpose as a business intelligence tool. You can use it to embed interactive dashboards in your app, but it’s nowhere near as customizable as building them from scratch. That’s exactly what sparked the idea for Embeddable.
A toolkit for fast, custom embedded analytics
We know how complex it is to build customer-facing analytics as well as how limited traditional BI tools usually are for this use case. So, we wanted to give devs and product teams a way to create full-custom analytics dashboards and interactive reports—without the drain on resources.
That’s why we built Embeddable: To help teams like yours build highly customizable components with a shorter time-to-market than going completely DIY.
Embeddable is a developer-first embedded analytics tool that is highly extendable, customisable and scalable. It will save you the engineering time while allowing you the unlimited flexibility of a custom build, and removing the headaches of using a rigid BI tool.
You define data models (like ‘customers’ or ‘purchases’) and which charts they’ll be displayed on. Then, anyone on your team can easily use these charts to create dashboards for your customers—can be embedded into your app with a few lines of code. Meanwhile, all the most popular features, from drill-downs to sharing, are ready to go out of the box and can be toggled on in a click.
Build remarkable, fast, and fully bespoke customer-facing analytics experiences in 10% of the time. Learn more.
Best practices for creating remarkable user-analytics
If embedded analytics are on your new features roadmap, that’s great! Here are a few tips from Harry Marshall, Co-founder and COO at Embeddable, and Shruti Bhat, Chief Product Officer & SVP of Marketing at Rockset.
1. Understand the customer’s needs
“The first step is understanding what your customer’s needs are so you can build something that’s actually useful for them,” says Harry. This will save you from acting on a hunch and finding out your efforts were wasted.
You might already be getting requests for customer data, so ask your customer success or sales team if that’s something they get asked about as well. Alternatively, you can reach out to your customers directly to find out what value they see in your platform, and what data would be most helpful to them.
2. Prioritize a fast-loading tech stack
“Our advice is generally to find the right tech stack for the job,” says Shruti. “What do I mean by that? Use the right data sources and the right visualization tool.” With most embeddable solutions, caching is an afterthought (or worse, non-existent), which makes them slow to load.
So, if you’re using a BI tool for real-time data requests, you’ll probably find it struggles to provide accurate, fresh data. “Even if your database is very fast, your visualization tool can’t keep up because it’s not built for such real-time use cases,” says Shruti.
Considering a Headless BI architecture? Find out what headless BI is and how it could benefit your business here.
3. Get user feedback and iterate
Even once you’ve scoped and launched your analytics dashboard, be prepared to keep iterating on it. “Don’t launch it and think of it as a finished feature,” advises Harry. “The queries will come flooding in. It’s great because you’re showcasing value and your customers are engaged—but it isn’t over. You’ll need to continue working on it.”
Keep listening to what your users are saying, whether that’s via support tickets or in-app feedback. It can be useful to categorize feedback according to priority. For example, bug fixes come first, followed by iterations based on common user requests.
That said, there’s no need to overlook the dream charts and data requests that could amaze your customers and put your solution ahead of the competition. When the time comes, get them in the workflow and schedule a brainstorming session with your design, engineering, and product teams to determine how to solve the request.
4. Internationalize your offering
“Most software companies have users in different places, using different number and date formats,” reminds Harry. “Certain things won’t make sense to everyone, such as using dots instead of commas or exclusively using West Coast time if you have a global audience.”
So, plan for localization work from the very first sprint (retrofitting it into an existing solution will be far more challenging). You can also use localization libraries to find tools to handle internationalization like data and time formatting, number formatting, and text translation.
Note: This comes out of the box with many embedded tools, and of course, with Embeddable too.
Give users the power to make data-driven decisions
Embedding analytics rather than building them from scratch into your app will be a huge time-saver for your team. But that’s not to say that most BI solutions are fit for the job of providing data driven insights. In most cases, they’re not flexible enough to deliver interactive, engaging analytics or a cohesive brand experience.
So, if customer-facing analytics are on your roadmap, there are two crucial steps to take:
- Find out what your customer wants. Not all apps require user-facing analytics. But if users are telling you that data will help them make informed decisions, get more out of your app, and achieve their goals, you’ll probably want to deliver it for them.
- Choose an embeddable solution that can deliver it. Most out-of-the-box embeddable dashboards won’t look and feel like the rest of your app and come with pretty basic visualizations. Depending on your user and their goals, embedding the wrong solution will harm their experience rather than enhance it.
Embeddable will help you build your own customer-facing analytics, exactly the way you want it, in 10% of the time. This Javascript SDK gives you more flexibility than any out-of-the-box solution could dream of—all while handling caching, authentication, permission, and maintenance for you.
Build remarkable, fast, and fully bespoke customer-facing analytics experiences in 10% of the time. Get access to Embeddable today.
Frequently asked questions about embedded analytics
What’s the difference between embedded analytics and customer-facing analytics?
Embedded analytics is a subset of customer-facing analytics. You can build customer-facing analytics directly into an app or you can build them in a third-party tool and render it in your app. Embedded analytics is the latter. It’s often faster than building your analytics from scratch, and it can be cheaper depending on the solution you choose.
How does embedded analytics work?
Embedded analytics works by adding data dashboards and visualizations directly into an app, so users can see insights without switching to another tool. This is usually done by integrating third-party analytics tools using iframes, APIs, or JavaScript, making the data feel like a natural part of the app.
What’s the difference between Embeddable and other embedded analytics platforms?
Embeddable is technically an embedded analytics solution, but it’s much more flexible than most. It’s a Javascript SDK that allows you to use charts from charting libraries, your existing components and those provided, giving you all the customization options of building yourself, but in fewer sprints.
While most embedded analytics platforms will give you a limited set of inflexible components to build a dashboard, with Embeddable, you can create pretty much any component your product team can imagine—and it’ll actually look and feel like the rest of your platform.
This makes Embeddable the right embedded analytics platform for any business looking for a fully custom setup at an affordable price point.
How much does embedded analytics cost?
It depends on the tool you choose, the number of business users on your platform, the level of customization, the complexity of your business processes and more. Traditional BI tools like Tableau, Looker or Power BI are notoriously expensive. On the other hand, a separate business intelligence tool such as Embeddable is more affordable and takes less of your devs' time, saving even more time and money.
In short, embedded analytics tools can cost anywhere from several hundred dollars to $100,000 per year and more. Visit our embedded analytics cost breakdown for more information.