It seems like businesses in recent years are under constant pressure to make everything more data-driven. Even the simplest of apps now have analytics capabilities and you can get a dashboard showing how many calories you saved in a day by opting for a healthy meal. But there are many pitfalls and dangers that come with using an embedded analytics solution.
Today, we'll show you everything to watch out for when deciding whether you need an embedded analytics tool or not. And if you're in the market for purchasing embedded analytics software, you'll want to take notes and learn what to avoid.
1. Lack of proper data visualization options
The core of embedded analytics is showing interactive dashboards to internal or external users. Depending on the data set you're working with and the data insights you want to get, you'll choose a different type of visualization. Naturally, you want the option that helps you build customizable dashboards: one that has a huge selection of visualizations.
Traditional business intelligence tools such as Power BI, Looker, and Tableau do an alright job here. You'll find a sizable selection of charts and visualizations that will help your team and end users visualize data to get the right actionable insights - however, you will be limited in your ability to make them feel like a true part of your application as you can often only change fonts and colours, and will have to embed as an iframe
On the other hand, most embedded-first tools such as Sisense, GoodData, ThoughtSpot and similar but are more limited in their choice of visualizations.
How to solve it: choose an embedded analytics solution that offers the ability to plug in your favorite charting libraries. This lets you choose the kinds of visualizations you need to provide a great user experience, regardless of what your end-users need to visualize.
2. Complex embedding
You can choose between traditional BI tools that offer embedded analytics as a feature and embedded analytics tools built specifically for this use case. Your choice will influence how difficult it is to embed a finished dashboard.
Let's step back.
Building advanced analytics dashboards is one thing, and most data engineers can do that. With the right preparation and onboarding, even non-technical users can build their own interactive dashboards in a no-code builder.
However, embedding dashboards requires technical know-how that only developers can provide. If you don't have an in-house team of developers, you might have to outsource them just for the embedding. And here's a secret they won't tell you: most traditional BI tools are unnecessarily complex, and provide a sub-par user experience when it comes to embedding.
They typically use iframes, which means that the dashboards are loaded as separate layers on a web page or app. It's difficult to customize the dashboards and make them look and feel like they belong in your product.
Embedded analytics tools that are embedded by design come with APIs and SDKs allowing your developers to provide a superb user experience, all the while saving you time and money.
How to solve this: look for dedicated embedded analytics tools that have flexible embedding options,including the ability to embed as a web component so that you don’t need iframes. Before committing to anything, ask to see examples of interactive dashboards built with the platform you want to purchase, and ask to see the dashboards in their native setting.
3. Secretive and complicated pricing models
When you compare different embedded analytics platforms, you'll notice that very few of them have straightforward pricing. You might expect to see a flat price or the price per user per month, but unfortunately, it's a lot more complex than that.
Most business intelligence tools charge a certain fee per user, but there are different types of users: admins, analysts, viewers, and end-users with access to self-service analytics, and each has a different pricing range.
Then there are the costs for the end users, depending on how they analyze data and get to actionable insights. They can be priced per user (e.g. Metabase) or per amount of data (e.g. Stock Keeping Units in Power BI). The former is simpler, but you can often expect a mix of both.
Then there is the elephant in the room: the cost of technical expertise. Implementing embedded analytics requires having some development talent on board. Sometimes, it's as simple as being familiar with SQL, and other times, you'll need devs with highly specialized knowledge, such as LookML to work in Looker.
To ensure operational efficiency, you'll also need ongoing support and maintenance, which costs a pretty penny too.
Since the pricing is so complicated, it's very common for embedded analytics systems providers to hide it. There are a lot of moving parts, and therefore companies often need to quote on a case-by-case basis
How to solve it: before choosing the best embedded analytics solution for your needs, document precisely what you need and who you need it for. What you expect to achieve, who your customers are, what talent you have in-house, and how you expect your embedded systems to scale in the future.
With this information, you can get a more precise quote from different analytics tool vendors for easy comparison.
4. Performance issues
When using traditional BI tools, performance is not critical. It's expected that, e.g,. doing advanced predictive analytics is going to take a while, especially with large data sets. But when you embed in a customer-facing application, you don't have the luxury of waiting a minute for a dashboard to load.
End-users expect the dashboard to load lightning fast like the rest of the product. The right embedded analytics solution will let you do this by handling large data sets and visualizing them in seconds based on real-time queries, letting your end-users become more data driven while increasing the value of your product.
How to solve this: Use caching where possible, pre-aggregate data to reduce load, and consider using a database that can query large volumes of data at speed. Many analytics platforms offer performance tuning tools. Leverage these to minimize response times. Also consider lazy-loading dashboards or loading them only on demand.
5. Data security problems
The embedded analytics solution handles your company's and your customers' sensitive data. In either case, you need to be certain that you are the only entity with data access. Most business intelligence tools have a pretty good handle on this, but it’s always good to check their security protocols.
You might be required to host your data in a certain region, which is called ‘data sovereignty’, which might mean that a cloud-based provider can’t meet your requirements. In this case, ask upfront where the data is stored, and explore a self-hosted/ on-premise deployment option if the data can’t be ring-fenced in the location you require.
How to solve this: Look for embedded analytics platforms with role-based access control (RBAC), audit trails, and encryption. Make sure that the platform is compliant with SOC-2 and GDPR and has any other relevant certifications. Explore a self-hosted option if you have strict data sovereignty requirements or cannot let the data leave your ecosystem.
6. Lack of proper maintenance
While it’s a massive time-saving vs. a custom build, Embedded analytics is not a one-time cost. It's an ongoing investment into a core functionality of your product and you need to have people in-house to manage data analytics business processes. Dashboards need updating, data models need maintenance, and UX needs evolve.
If you don't have someone dedicated on your team just for embedded analytics, make sure your chosen vendor can support you.
This comes down to the choice between building your embedded analytics setup yourself or purchasing an off-the-shelf OEM analytics product. If you build your customer-facing analytics solution on your own, you're also the one to maintain it. Purchasing OEM analytics tools means that the maintenance is the burden of the analytics vendor.
How to solve it: dedicate at least one team member to maintain and update your embedded analytics. This person should ensure a seamless integration with data sources, proper white-labeling, and a good data flow. Alternatively, choose an OEM analytics tool such as Embeddable that has a dedicated support team to help you when you get stuck.
Is embedded analytics worth it?
There’s a huge cost to building your own dashboards and analytics in house, and making that single architectural decision means that the burden of all changes and fixes you ever make will rely on your product and engineering teams. So unless you’re keeping it simple, and don’t ever expect to change your dashboards, it’s often a good idea to use an embedded analytics tool.
Embedded analytics is not a fad. It's a tried and tested way to give business users data driven insights, but you’ll want to know that you’re using the right tool for your needs so you should carefully consider the options before investing thousands (sometimes hundreds of thousands) of dollars per year on this endeavor.
✅ When embedded analytics is worth it:
1. You're building a data-driven product or SaaS platform
If your users rely on insights to make decisions, like tracking KPIs, behavior, financials, or usage, then offering analytics directly inside your app can make your product much more valuable.
2. You want to increase user engagement and retention
When users can see results, trends, or ROI without exporting data or switching tools, they can see the value that your tool is delivering for them, and they’re more likely to stay engaged. Embedded analytics can help make your app a must-have for them.
3. You're trying to monetize analytics or create upsell opportunities
You can offer advanced reporting as a premium feature. Many SaaS companies use analytics as a way to differentiate plans and generate additional revenue. This can help you to unlock new revenue opportunities.
4. You need to reduce support requests
Self-service dashboards mean fewer data-related questions going to your support team. That’s a win if your team is stretched thin.
5. You’re aiming to stay competitive
If your competitors offer in-app reporting, not having it may become a weakness. Embedded analytics can help level the playing field—or give you a competitive advantage.
❌ When embedded analytics may not be worth it:
1. Your users don’t need insights inside the product
If your users rarely ask for reports or data visualization, or if they prefer exporting data to Excel/BI tools, embedded analytics might be overkill.
2. Your dev resources are tight
Unless you choose a low-code solution, embedded analytics requires dev time for setup and ongoing maintenance. If your roadmap is packed, it could become a distraction.
3. You’re early-stage and not yet focused on data features
Startups sometimes try to ship everything too soon. If analytics isn’t a core value prop right now, it might be smarter to postpone it until your users start asking for it.
Wrapping up
All of the disadvantages of embedded analytics can be solved fairly easily IF you know what you're looking for in your chosen platform and you have the time and resources to see it through. The reality is that you can solve most of the problems with embedded analytics by choosing a reliable OEM software provider that has your back at all times.
We built Embeddable to be perfect for product and engineering teams to deliver truly remarkable embedded analytics for their customers, taking into account the pitfalls outlined in this article. That means:
- It feels like part of your product - you have complete control over the user experience and interface, in code, and it renders as a native part of your application (no clunky iframes!)
- It can be extended indefinitely - use the SDK to modify or extend the code of any chart, or import charts from any React charting library.
- It loads with lightning speed - supported by a performant data service and two levels of configurable cache.
- It provides an intuitive developer experience - embed with a secure and lightweight web component and apply logical row-level-security.
- The pricing is designed for embedded analytics via a fixed-cost monthly subscription that gives you certainty on what you’ll pay, no matter how much your user base grows.
- It provides intuitive self service analytics features- with built-in features that give your end users the power to customize their own views of your dashboards.
Join other leading companies and get access to Embeddable to find out how we can help you to deliver your customer-facing analytics project.