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Embedded Analytics

7 Critical Capabilities to Take Your Embedded Analytics to the Next Level

By Michelle Gardner | February 1, 2019
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The benefits of deploying modern embedded analytics are massive—but so are the risks of doing nothing. Application teams that embed modern analytics capabilities and sophisticated dashboards have a proven business advantage over those that stop at basic data visualizations. They’re better able to differentiate their software from competitors, reduce customer churn, increase revenue, and improve customer satisfaction, according to the 2018 State of Embedded Analytics Report.

Given the clear benefits of modern embedded analytics, it’s no surprise that Gartner predicts that by 2020, 80 percent of enterprise application vendors will compete on the sophistication of advanced analytics offered in their solutions. The key is to plan now. If your roadmap doesn’t include at least a couple sophisticated analytics capabilities, you risk falling behind.

>> Related: 5 Best Practices for Choosing an Embedded Analytics Platform <<

Consider these seven sophisticated features as you plan your next analytics update: 

  1. Adaptive Security

Your analytics should have adaptive security that plugs right into your current framework. After all, your team has already invested significant time and effort building your security infrastructure. Why re-invent the wheel? Look for an analytics solution that uses your existing security framework and supports single sign-on, multi-tenant deployments, and precise control over user access.

  1. Custom Branding

Embedded analytics should disappear into your application. If users see a disjointed experience, they may leave your product and start considering alternatives. Look for an analytics development platform that gives you complete control to white-label BI software and customize the user interface, user experience, and branding. Custom-branded analytics reflect the exact look and feel of the rest of your application, creating a completely consistent experience. Modern platforms also give you control at the global level and granular level (third-party visualizations/controls), and support extensibility.

  1. Self Service

Self-service analytics empowers end users to ask new questions of their data without sending ad-hoc reporting requests to the development team. Rather than exporting data or jumping into another application, users can help themselves to what they need in your software. Choose an analytics platform that not only lets you embed self-service capabilities, but also allows you to customize them for your application experience and user skills.

  1. Predictive Analytics

Embedding predictive analytics is the newest way for application teams to drive real business value for their users and set their products apart in crowded markets. Using historical data and machine learning, your application can deliver future insights and help users act preemptively. Look for a predictive analytics solution that is designed for almost anyone to use and doesn’t require statistical modeling, Python, or R expertise. This will keep the development burden off your development team.

  1. Insight-to-Action Capabilities

New capabilities such as integrated workflows, write-back, scheduling, sharing, and alerts empower end users to turn insights into action without leaving your application. Few applications include these capabilities, but they’re some of the easiest ways to add value. Look for an embedded analytics solution that empowers end users to take immediate action or trigger another process from your application.

  1. Tech Stack Integration

Embedded analytics solutions should make your developers’ lives easier. Your application team has already invested plenty of resources in your software, including deployment, technology, and data structures. Why duplicate efforts just to add or enhance your dashboards and reports? Choose an analytics platform that scales with your server infrastructure, leverages the data investments you already have in place, and deploys with your tech stack.

  1. Scalability

Your embedded analytics should scale with your business without incurring massive additional costs. Otherwise you could end up with stagnant dashboards while the rest of your application innovates—or, even worse, you may be forced to rip out the solution and start from scratch. Choose an analytics solution that scales linearly with your server infrastructure and has a scalable pricing structure (with no per-user or per-license fees).

Want to learn more about choosing an embedded analytics platform? Read the Gartner 2018 Critical Capabilities Report for Analytics and BI Platforms >

 

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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