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Embedded analytics is no longer a nice-to-have. It's becoming a key part of the products and websites of businesses that want to enable data-driven decisions with their customers. Up until a few years ago, you didn't have much choice. You were stuck with traditional business intelligence tools like Power BI and their embedded counterparts, which were lackluster, to say the least.
Then came embedded analytics tools, built specifically for embedding in SaaS products. One of the latest newcomers is Embeddable, a developer-friendly tool that gives your team the ability to fully customize the look and feel of embedded dashboards.
But is it really that good? Let's find out what Embeddable reviews say.
You'll find a few accounts of developers and product managers who are thrilled with Embeddable, and it's easy to see why. It doesn't force you to use iframes for embedding, which opens up a world of possibilities.
You can make the embedded dashboard feel native to the product by writing custom code. The downside is that your developers really have to know what they're doing, and ideally, they have previous experience building dashboard setups.
Initial setup often involves SDK integration, auth wiring, and environment config before anything is visible. For nontechnical teams, that can feel slow compared to tools where you log in and click a few buttons to get a dashboard. And since Embeddable doesn't come with many templates out of the box, that leads to the next problem.
The time to first dashboard can be longer compared to similar platforms. Your entire team depends on developers to wire up data sources, models, and embedding logic first. Until that groundwork is done, there is nothing to explore, which can make early buy-in harder.
And once everything is set up, you're reliant on developers for just about everything. Want to change the background color of a dashboard element? Add a new data source or integration? You're going to need help from a dev.
In general, you have fewer plug-and-play features compared to more established tools. There are no ready-made solutions for alerts, scheduled reports, custom charts or canned metrics. Teams often have to build or connect these pieces themselves rather than turning on a switch.
And last but not least, Embeddable is no Power BI. The latter has been around for years, and it's easy to find a Power BI expert specializing in exactly the kind of dashboards you need. To find a dev who can work with Embeddable, you'll need more intricate knowledge of development and be familiar with exactly what you want from a dashboard for you and your end users.
Embeddable prides itself on transparent pricing, but there is not a single digit on their website that shows you how much you pay per seat or the volume of consumed data. You have to book a meeting with the sales team to get the basic idea of the costs involved.
You can apply to join the beta and in the call, you'll find out that Embeddable charges per employee count, not seats or data usage. A small team with fewer employees will pay less for Embeddable, despite using up more data or having more end-users.
On top of the lack of transparency, another issue is that you don't get to see Embeddable in action until you've already committed to pay. There is no free plan or free trial, only a demo you can attend, which doesn't show you how the platform works with your unique setup.
The pricing model punishes larger companies that may not have many viewers or end-users who edit dashboards, which brings us to our next point.
Traditional business intelligence tools such as Tableau, Power BI or Looker may not be the greatest at embedding, but there is another major advantage: you can use them to create and share reports internally. For example, you want a revenue report across marketing and sales and instead of embedding it, you want to send a simple link to the dashboard to your team.
Well, you can't.
As the name suggests, Embeddable is built for embedding only. You can create some sort of intranet/ knowledge base and then embed the dashboard before sharing.
Traditional BI platforms often include a modeling layer inside the product. You can create metrics, joins, calculated fields, and business logic directly in the UI. Embeddable takes a different path. It expects most of that work to happen upstream, inside your data warehouse or transformation layer.
In practice, that means product teams need a well-organized data stack before Embeddable feels comfortable to use.
For teams with a mature setup, this can be fine. But for many growing SaaS companies, it introduces friction.
Analysts and product managers cannot define or tweak metrics on their own. Simple changes such as updating a revenue formula or correcting a join often require changes in SQL models, tests, and deployments. What could be a quick fix in a BI tool becomes a developer task.
It also makes experimentation harder. Trying a new way to calculate retention or compare cohorts takes longer when every change must go through a modeling pipeline. Business users lose the ability to explore and adjust logic in real time.
Finally, documentation and consistency become your responsibility. Without a built-in semantic layer, you must manage definitions, naming, and ownership yourself. If that work is not done carefully, teams can end up debating numbers instead of using them.
For companies that want analytics to move as quickly as product teams do, this gap matters. Tools like Luzmo reduce that friction by offering modeling and logic closer to the analytics layer, so teams can move from question to answer without always pulling engineers into the loop.
Whether you like AI or not, there is a big chance your customers are expecting some form of artificial intelligence in their dashboard. And while Embeddable is expanding the roadmap with each month, there is no clear sign of AI features coming.
This puts them at a disadvantage compared to legacy tools like Power BI or Tableau, but also dedicated embedded BI tools like Luzmo, ThoughtSpot, GoodData and others.
AI tools can help internal or end-users do predictive analytics, explore data with commands in plain English, detect anomalies and in general, lower the barrier to entry. Once again, Embeddable is built for the more knowledgeable crowd.
The longer a BI tool has been in business, the better it connects to other platforms. For example, Luzmo connects to Azure Synapse, AWS Redshift, BigQuery, Snowflake and just about any other source you can think of.
Embeddable connects to a few relational databases such as Snowflake, Google BigQuery, and Amazon Redshift. For everything else, you're going to have to manually connect the source/application to Embeddable via API. And once again, you'll need developer resources.
Embeddable is not a bad tool by any means. It's simply built for a very niche audience. The ideal target audience for Embeddable is:
The general, objective impression is that Embeddable is still early on in their journey. The fact that they cater to developers narrows down their target market instead of opening it up to a wider audience. Couple that with opaque pricing and it's easy to see why SaaS companies look at Embeddable alternatives instead.
For example, Luzmo.
We offer different embedding methods with full customization, so that any developer can plug Luzmo into your product in hours. Whether you want to go fully custom with our Flex SDK or use the available templates in a drag-and-drop editor is your choice.
Luzmo has a rich library of sources and connectors, and AI features to help with conversational analytics and easy data exploration.
Perhaps most importantly, Luzmo pricing is publicly availabl,e and you can get a free trial to try out how Luzmo works with your app before spending a cent.
Build your first embedded data product now. Talk to our product experts for a guided demo or get your hands dirty with a free 10-day trial.
