If there is a complex job to be done, you often face the dilemma: do it yourself and spend more time and effort, or outsource it to a team of experts. In reality, it’s often better to hire specialists so you can work on the things you’re really good at.
The exact same principle applies to embedded analytics. This is a principle called OEM analytics, where instead of building out analytics yourself, you purchase an off-the-shelf embedded analytics tool instead.
Today, we define OEM analytics, show you how it works, and how it can benefit your business.
What is OEM analytics, and how does it work?
OEM (original equipment manufacturer) analytics software refers to tools developed by specialized analytics providers, intended to be embedded or integrated into another company's software or applications.
Essentially, it’s analytics software built by one vendor but packaged into and sold within another company's product, often rebranded or white-labeled to match the host product's look and feel.
To define OEM analytics in simple terms, it lets software companies offer advanced analytics directly in their own apps without building the analytics technology themselves.
The benefits of using OEM analytics software in your product
Using OEM analytics tools instead of building your own data analytics setup has a few advantages. Here's what you can gain by adding OEM embedded analytics to your software/product.
Faster time to market
Building advanced analytics from scratch is incredibly resource-intensive. Even if you have a seasoned team of data scientists and developers, building your own analytics setup can take months. Some software companies can afford this while others need those resources for their core product.
Purchasing an OEM analytics solution allows you to get up to speed within days, connect your data sources, and let your team (or customers) do data analysis sooner rather than later.
On top of time and cost savings, this can give you a competitive advantage in a crowded market.
Lower costs
According to Glassdoor, the average salary for a developer in the USA is around $135,000. If you have an in-house developer, every minute they spend working on your analytics setup is a minute taken away from your core product.
And even if you outsource the work to a freelancer or an agency, this can easily go over $100 per hour. And that's just for one developer, without involving data scientists, analysts, engineers, designers and other stakeholders.
Purchasing OEM software is almost always cheaper, and you know exactly what your costs will be from the very start.
Increased product value
SaaS companies typically use OEM analytics to provide more value from their product to the end-users. For example, an e-commerce platform can launch a dashboard allowing users to view their sales data in real-time.
This makes products more usable, provides self service analytics capabilities to your end users and last but not least, gives you opportunities to upsell customers with new features and packages.
Niche expertise and reliability
Purchasing off-the-shelf OEM software gives you access to a team of experts with experience building nothing but dashboards and analytics modules. This ensures shorter development cycles, faster time to market, and a team of experts you can troubleshoot with.
Let's say you have a team of developers, data scientists and software product owners. If you ask them to build embedded analytics into your product, chances are they're going to do an okay job. However, they're experts in their own fields, not in OEM analytics software.
Focus on core competencies
Let's say you're building a carbon tracking app and every minute and dollar are precious. You have a packed roadmap and just a handful of devs to work on the product. Your customers keep requesting built-in dashboards but you know the scope and cost and that you can't afford it.
Purchasing OEM analytics for your software application frees up time for your development team to work on the core product. The OEM analytics team simultaneously works on the embedded analytics product and its seamless integration into your existing app and processes.
Scalability and flexibility
Building analytics tools internally is a great exercise in how capable your team is. However, there is a major difference between 20 and 200 users using those analytics dashboards. You're going to need different data access levels, security features, drill-down options, the ability to share dashboards internally and externally and much more.
OEM software is built with scalability in mind, allowing you to easily add data sources, team members, dashboards, and everything else needed to grow your team and user base.
Continuous updates and innovation
Building your own analytics in a software product comes with a hidden risk: you're left in isolation. You won't know if there are new ways to speed up dashboard performance, new integrations to add, visualization types and similar.
OEM analytics software teams don't just handle your software product. They have a wide range of customers from different verticals and they're up to date on what the market needs. So, as soon as they launch a new UX/UI update, all the users across the board receive those same updates.
Lower maintenance overhead
When purchasing an OEM analytics solution, you can go on with business as usual because if something goes downhill, you can simply reach out to the team who sold you the product. Issues with integrations, connectivity, performance, data access and similar are not yours to worry about.
However, if you're the one who built and set up your own embedded analytics, troubleshooting is exclusively your responsibility. Once again, this means taking away developers' time when they should be working on the core product offer.
The downsides of using an OEM analytics solution
OEM analytics software also has a few challenges that you may want to consider as this option is not built for every product.
Limited control over features
When you're purchasing OEM analytics, you're with them for the long run. Whatever the service provider has on their roadmap is what is coming for your analytics solution. In other words, you can't expect something built exclusively for your own use case.
To prevent this from happening, choose an original equipment manufacturer whose roadmap aligns with your future needs and expectations, or a headless embedded analytics tool like Embeddable.
Dependency on external providers
Your product's analytics capabilities depend entirely on the OEM vendor’s reliability, uptime, and responsiveness. Issues or outages on their side directly affect your customers' experiences, and you have less control over issue resolution. This can be avoided in some cases with self-hosted deployment, but you’re still dependent on the provider to an extent.
Less differentiation
Because OEM analytics solutions are generally available to other businesses, your competitors might be using the same analytics tool, making it challenging to differentiate your product's analytics offering in the marketplace.
Bypass this problem by customizing the look and feel of your dashboards to meet the needs of your end-users instead of copying a competitor 1:1. This is one of the biggest advantages of using a headless embedded analytics tool.
Integration complexity
Even though OEM analytics are designed for embedding, integrating them seamlessly into existing products can require considerable engineering effort, especially if your platform is complex or has specific technical requirements.
The solution to this problem is to choose an OEM analytics provider with an API or SDK for easy embedding, instead of using outdated iframes.
Long-term costs
While OEM analytics can reduce initial development costs, ongoing licensing or subscription fees can accumulate significantly over time. As your user base expands, costs may scale dramatically, sometimes becoming less cost-effective in the long run.
To prevent this, choose an OEM analytics provider that offers a fixed price for an ongoing time period, with clear upgrade options and costs for additional users and services.
Data privacy and security concerns
With an external analytics solution, sensitive data often leaves your environment to be processed by the OEM vendor, increasing the complexity of compliance and potential exposure to security vulnerabilities.
To ease your mind, choose a provider with the right certifications and compliance, such as SOC-2 or HIPAA. Before signing any contracts, review the service provider's data security policy.
Vendor lock-in risk
Relying heavily on a single OEM analytics provider can make future migrations difficult, expensive, and disruptive. The transition could become complex and costly if you later need to switch providers or move analytics in-house.
For example, locking into using Power BI or Looker can make things complex because of their proprietary tech and programming languages. Simply choose a platform with a selection of development and embedding tools, such as API or SDKs, and most importantly, make sure it has strong documentation.
Get started with embedded analytics today with Embeddable
Offering analytics alongside your core product can improve its value, increase customer satisfaction and retention, reduce churn, and give you a competitive advantage in a crowded market. Building it yourself is not always possible, and when it is, your money and time are better spent elsewhere.
With Embedable, you can build fully customizable, interactive embedded analytics into your software in a matter of days, not months. With easy embedding options, a rich variety of visualizations and beautiful UX and design out of the box, Embeddable makes your developers and customers happy.
Get access to Embeddable today.