Using embedded analytics in software applications can drive your business forward

Analytics in your tools can help users gain insights that can help move your clients and the organization to the next level.

Image: Mykyta Dolmatov, Getty Images/iStockphoto

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More than two years ago, Edsby, which provides a learning management system for educational institutions, began embedding analytics into its software that enabled teachers and administrators to detect student learning trends, assess test scores across student populations, and more, all in the spirit of improving education results.

The Edsby example is not an isolated event. Increasingly, commercial and company in-house software developers are being asked to deliver more value with their applications. In other words, don’t just write applications that process transactions; tell us about the trends and insights transactions reveal by embedding analytics as part of the application.

“Software teams are responsible for building applications with embedded analytics that help their end users make better decisions,” said Steve Schneider, CEO of Logi Analytics, which provides embedded analytics tools for software developers.” This is the idea of providing high-level analytics in the context of an application that people use every day.”

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Schneider said what users want is transactional apps with built-in analytics capabilities that can provide insights to a variety of users with different interests and skill sets. “These are highly sophisticated analytics that must be accessible right from the application,” he said.

With the help of pick-and-click tools, transaction application developers are spared the time of having to learn how to embed analytics from the ground up in their apps. Instead, they can choose to embed an analytics dashboard into their application, or they can quickly orchestrate an API call to another application without a need to custom develop all of the code.

“You can just click on the Embed command, and the tool will give you a Java script,” Schneider said. “In some cases, you have to do a little configuration for security, but it makes it much easier to get analytics-enriched apps to your user market faster.”

Getting apps to market faster

Here’s how an embedded analytics tool can speed apps to market.

A marketing person is tasked with buying ads and organizing campaigns. He or she gathers information and feeds it to IT, which periodically issues reports that show the results of ad placements and campaigns.

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Now with an application that contains embedded analytics, the marketing person can directly drill down into the reporting information embedded in the app without having to contact IT. This can be done through a self-service interface in real time.

“In one case, a manufacturer was trying to improve operational performance through the use of an application and set of stated metrics,” Schneider said. “Everyone had to log in to the application to record their metrics, but the overall goal of improving performance remained elusive. The manufacturer decided to augment the original application with an embedded analytics dashboard that displayed the key metrics and each team’s performance. This provided visibility to everyone. This quickly evolved into a friendly competition between different groups of employees to see who could achieve the best scores, and the overall corporate metrics performance improved.”

For most developers, embedding analytics in applications is still in early stages—but embedded analytics in apps is an area that is poised to expand, and that at some point will be able to incorporate both structured and unstructured data in in-app visualizations.

Best practices for embedded analytics

Companies and commercial enterprises interested in using embedded analytics in transactional applications should consider these two best practices:

Think about the users of your application and the problems that they’re trying to solve

This begins with asking users what information they need in order to be successful. “Application developers can also benefit if they think more like product managers,” Schneider said. In other words, what can I do with embedded analytics in my application to truly delight my customer—even if it is the user next door in accounting who I see every day?

2. Start simple

If you haven’t used embedded analytics in applications before, choose a relatively easy-to-achieve objective for your first app and work with a cooperative user. By building a series of successful and high usable apps from the start, you instill confidence in this new style of application. At the same time, you can be defining and standardizing your embedded app development methodology in IT.