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When we speak to developers and product teams with a user-facing analytics epic on the backlog, they often say the same thing: It’ll have loads of benefits for our customers but we just have other things we need to prioritize. Either that or they’ve already started developing something and say the project is taking forever. That’s what prompts many teams to consider embedded analytics.
Most embedding tools will ask you to ‘buy instead of build’ user-facing analytics for your app. But what they don’t tell you is that embedded analytics are usually pretty limited. While embedding analytics tools could reduce time-to-market and be cheaper than developing the solution from scratch, the end result isn’t very customizable and might not really serve your customers’ needs.
In this article, you’ll find out everything you need to know about embedded analytics, as well as an alternative method for getting custom user-facing analytics into your app—without dedicating sprints of developer hours 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. Find out more.
What is embedded analytics?
Embedded analytics is the practice of building analytics in a third-party tool and rendering it inside your existing 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 (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 ecommerce platform for independent makers, 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.
4 Benefits of embedded analytics
Using an embedded analytics solution, rather than building the feature from scratch, has one significant benefit for your dev team—and that’s the time-saving. Whether embedded or not, user-facing analytics have a few other pretty awesome benefits for your business.
They can help you:
1. Communicate the value of your product
Let’s go back to the indie maker’s ecommerce platform. An app like that gives creatives somewhere to sell their products, increase their visibility, and even handle payments. It’s clearly an asset, but how well do makers understand its value? What keeps them coming back to this platform over switching to another with similar features?
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 some cases, embedding analytics will add value to your product. In other cases, it’s more important that it showcases the product’s existing value. “For me, it’s about giving the user confidence in your product,” says Shruti Bhat, Chief Product Officer & SVP Marketing at Rockset, a search and analytics database.
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, which in turn boosts retention. That’s the reason customer-facing analytics makes it onto a lot of 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.
One thing Spotify taught us is 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.
4. Increase revenue
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 sales. 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 opt to 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.
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, building analytics into your app (and maintaining it into the future) can take up sprints of developer time—which can be a blocker when you have other features to prioritize. On top of the initial build, you’ll need to consider factors like performance and security. It’ll be a complex project that eats up a lot of your dev team’s time and could end up costing a fortune.
An embeddable solution is typically much faster to deploy and can be cheaper, depending on which solution you choose. The problem is, 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 Javascript SDK that combines a front-end toolkit, backend engine, and no-code builder (so your customer-facing team can use it without dev support).
Sounds complicated? It’s actually quite simple:
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 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. 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. Learn more.
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.
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.