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BI Trends

4 Predictions to Future-Proof Your Embedded Analytics

By Michelle Gardner | August 8, 2017

In the competitive software world, customers are always ripe for churn. One way to satisfy users and keep them in your application is to embed analytics.

But as we’ve said before, basic data visualizations and analytics reports simply aren’t enough to keep your users engaged over the long term. Application teams are using their embedded dashboards to differentiate their products—adding more advanced capabilities, including seamless UI, integrated workflow and write-back, in-app self-service capabilities, and advanced predictive and prescriptive analytic tools.

As forward-thinking application teams up the analytics ante, they’re able to win over new customers and reduce churn on their current ones. In fact, 72 percent of applications plan to invest more in their embedded analytics capabilities within the next 12 months.

>> Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough <<

Companies that want to differentiate their applications for years to come need to stop thinking only about what dashboard and reporting features their end users need today. They have to plan now to future-proof their analytics offerings with capabilities that last.

Where is the world of embedded business intelligence headed? What’s the next product differentiator?  These 4 predictions should get you thinking long-term:

Embedded analytics will be the standard.

Just a few years ago, standalone data discovery tools were a great way to satisfy nearly every user’s analytics needs. But then a few application and IT teams started adding dashboards to their applications—first as a separate tab for static reports, then adding deeper and deeper integrations with more advanced BI capabilities. Embedded analytics is quickly becoming the new standard, and the base level at which every analytic application starts. This means going beyond a few links to basic reports and instead integrating sophisticated capabilities as seamlessly as possible inside your application.

More users will demand embedded self-service analytics.

Without self-service capabilities at their fingertips, users will send ad hoc requests to application teams to get the data they want—which leads to an unnecessary expense of developer time and resources to keep up with demands. More non-technical users are showing a preference for visualizing data on their own and creating outputs by themselves. That’s why embedding self-service capabilities as soon as possible is key to both staying competitive and reducing the burden on your IT team.

The outer bounds of analytics will keep stretching.

Beyond descriptive analytics (“what is”) and diagnostic analytics (“why it is so”), more application providers are looking into predictive analytics (“what will be”) and prescriptive analytics (“what you should do about it”). Wide adoption of prescriptive analytics is still much further out, but it’s worth tracking now to plan for the future.

Advanced analytics are on the horizon.

Advanced analytics has been the “next hot thing” for a while now, but it’s still primarily the domain of analysts who mine data, create models, and test their hypotheses. Over the next five years, expect these capabilities to become widely available to all users as a component of embedded analytics platforms.

The bottom line? Weaving analytics into the fabric of your application and maturing the features you’re offering makes your application stickier and leads to better adoption—ultimately translating into higher sales and renewals. The key is to plan now. Companies that wait to enhance their embedded analytics may end up scrambling to improve their offerings after they lose key customers to the competition. By going beyond canned visualizations and dashboards, you can uniquely position your application in the market and base your offerings on new analytics capabilities that empower users to do their jobs better, smarter, and faster.

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About the Author

Michelle Gardner is the Content Marketing Manager at Logi Analytics. She has over a decade of experience writing and editing content, with a specialty in software and technology.

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