5 Strategic Competitive Advantages of Embedded Analytics

February 20, 2019
Kevin Smith's picture
VP, Product Marketing
Kevin Smith is Vice President of Product Marketing for GoodData. Prior to GoodData, Kevin was responsible for delivering consulting services such as analytic product strategy, data monetization, and go-to-market services at NextWave Business Intelligence. He is the author of numerous ebooks, articles, and webinars on embedded analytics and building data products. In addition to NextWave, Kevin has held leadership positions heading analytics teams, designing SaaS products, and performance and managing product teams for both small start-ups and Fortune 500 companies such as SAP, ServiceSource, and Qwest Communications. Kevin holds a B.S. in Finance, as well as an M.B.A. in Quality/Process Management, both from the University of Maryland, College Park.

With traditional BI solutions, user engagement and analytics adoption across the organization can remain low, because they may provide limited value to the end user and be difficult to use. From my experience building analytic applications, the only way to improve engagement and deliver a successful user experience is to enable experimentation and iteration at a rapid pace to meet the constantly changing needs of the user and the business.

This is where the value of an end-to-end embedded analytics platform becomes apparent. The benefits of an end-to-end embedded analytics platform include the ability to deliver rapid iteration as well as a user experience that’s seamlessly integrated into an existing workflow. This capability is why Nucleus Research predicts that 90% of business users will interact with analytics at least once per day but only 15% will realize it over the next seven years.

Let’s take this one step further. What strategic competitive advantages do embedded analytics offer?

1. Enables users to gain more value from your product

First and foremost, embedded business intelligence enables your users to derive more value from your product. As opposed to just going through a workflow, now they’re going through the workflow and gaining insights into business performance that they wouldn’t have received from the workflow by itself. They’re understanding where problems are occurring, how much things cost, where there are opportunities to streamline processes. They know what actions to take based on the insights provided thereby impacting the business.

2. Establishes you as the thought leader in the space

Taking advanced analytics and architecting them into a workflow that guides the user from problem to root causes and solutions establishes you as a business with a deep understanding of your given space. Whether it’s insurance, finance, or marketing, this kind of guidance says that your company understands the industry and that you’re well qualified to guide the user.

Imagine you’re selecting a CRM tool. One tool allows you to put in new opportunities and deals,  deal size and probability of close. The other one does that too, but it also gives you analytics to assess your funnel, gain an understanding of how likely things are to close, and estimate what your profits will be this quarter — all from within your workflow.

With this kind of expertise in your company’s industry and more advanced capabilities, the second tool is the clear winner. It helps your understand your job better. Embedded BI can help you deliver that same experience to your customers right in their workflow where they are making decisions.

3. Provides an upsell path

Introducing analytics paves a clear path to additional revenue moving forward. Let’s stick with the CRM example from before. If you produce a product like a CRM, a common goal is upsell—getting customers to buy more functionality over time. Analytics give you one strategy to do so. Launch a tiered offering, with “basic” analytics offered in a lower priced package, more robust analytics with more data and capabilities in a “premium” package or analytics with ad hoc analysis and freeform dashboard creation in a “professional” package. By doing so, you can expand your revenue stream while also enabling your customers to tailor their experience to their needs.

4. Ensures a deep understanding of user personas

User personas in the data domain are rapidly changing and are highly complex. Who is a data scientist and what is he trying to do? What's the difference between a business analyst and a data analyst? What’s a “citizen data scientist”? What's the best tooling for IT vs a data engineer? Who is using a specific feature, why, and how often? Our ability to analyze product usage through different lenses allows us to navigate this complex environment and build the right tools for the right personas.

Additionally, analytics give us  a deeper understanding of the interests of personas as they access charts, create specific dashboards, or navigate around in  certain way. With this knowledge of what they need, you can further refine your core product, targeting the functionality and resources that would be most beneficial.

5. Monetizes data

In the course of using your service or tool, users are generating data, but that data is rarely used effectively. Think of it as the exhaust coming off the engine of your core product—it’s there, but it’s not something you think you can do much with. But, much like a turbocharger hanging off the exhaust system of a car, analytics can be used to put that data “exhaust” to work. That data can now be captured, analyzed, and used to increase engagement, reduce churn, or improve customer satisfaction. The value of that information would otherwise flow right out the tailpipe, but with analytics it can result in additional engagement or value for your users, ultimately generating additional revenue.

Separately, each of these advantages would be a compelling point, but analytics pull all of these advantages together. Companies looking to differentiate themselves from their competitors should consider the substantial value they can capture from embedded analytics.

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