The 3 Elements of OEM Analytics
The popularity of embedded analytics shows no signs of slowing down. In fact, according to the State of Embedded Analytics Report, over 90 percent of application teams currently embed some form of analytics in their applications. This includes non-commercial IT-managed applications used by internal staff and partners, as well as commercial independent software vendors (ISVs) and Software as a Service (SaaS) providers providing white-labeled and OEM analytics to their customers.
The latter group presents a very unique use case. As important as embedded analytics is for in-house teams, it’s even more critical for OEM analytics use cases. Because ISVs and SaaS providers sell a commercial product, the value of embedded analytics goes beyond user satisfaction. It can make a difference in revenue generation, customer churn, and winning new customers.
Consider the following statistics:
- 78 percent of commercial application teams say they charge more for the analytics in their commercial applications
- 98 percent of commercial software companies say embedded analytics contributed to revenue growth
- Application teams estimate that embedded analytics contributes 54 percent of
the total application’s value
The 3 Elements of Embedded OEM Analytics
Despite the importance of OEM analytics, many ISV and SaaS teams forget to consider some crucial elements when embedding analytics in their software applications. Successfully embedded OEM analytics generally have three things in common:
They’re White Labeled
White label reports are necessary to ensure brand consistency and a seamless UI/UX. White labeling analytics allows developers to match an application’s fonts, colors and overall design scheme to the embedded analytics, even if they are technically being created separately. With white label analytics, product teams maintain control over the application and the ability to customize it without worrying about creating a disjointed user experience.
They’re Forward Thinking
It’s only a matter of time before your customers want to do something new in your analytic application—whether that’s connecting a different data source or creating a visualization that hasn’t been done before. These requests usually leave application developers and product teams with two equally undesirable options: Either change the core functionality whenever a unique request comes in, or refuse requests and end up with unhappy users that have to deal with the application in its original form.
That’s why commercial application teams need to constantly be looking forward. Customer needs change so quickly that it’s critical to keep an eye towards what users are going to want and expect six, 12, or even 24 months out. For embedded analytics in particular, some of the sophisticated capabilities that we believe will satisfy customer demands now and in the future include integrated workflow and write-back actions, multi-tenant security, and embedded self-service BI.
They Offer Tiered Pricing Packages
What’s the point of offering embedded OEM analytics in a commercial application if you can never monetize it? ISV and SaaS companies should consider their long-term revenue options up front before embedding analytics in their products.
One of the most effective but often-missed pricing models for embedded analytics is to give users a free version of the product with a limited feature set, and offer more capabilities to customers who are willing to pay. Giving users a taste of the full BI offering helps them understand its value and, more importantly, helps them figure out which features—and ultimately which paid subscription tier—they need. Another benefit of tiered pricing? It gives your customers different options as their needs evolve.
It’s important to note here that not every BI vendor can support tiered pricing strategies. Look for an embedded OEM analytics platform that lets your application team control every aspect of the application on user-, role-, and rights-based levels, all in one place.
Monetize Your Application with Embedded OEM Analytics
The elements mentioned above contribute to both the user experience and your business’s bottom line. Creating a great user experience by being both forward thinking and white labeling your analytics, the customer’s perceived value increases. With a higher perceived value, customers are willing to pay more through tiered pricing packages. Learn our recommended steps to monetize embedded analytics and see how you can customize elements of embedded OEM analytics in this demo of our platform.