Follow Datanami:
July 21, 2021

Why Embedded Analytics Are the Foundation of a Successful Application

Vijay Pendyala


Is your application starting to become irrelevant?

Or, put another way, is your application focusing only on facilitating the transactional parts of the customer interaction process while missing an opportunity to also provide critical insights? Because if your application is, it’s losing value. Sure, transactional tasks are getting automated, say sales or inventory management. A transactional report is getting generated. But is the business task itself getting done better or faster?

Embedding a layer of analytics into your existing application, on the other hand, is a pathway to delivering better results rather than just statistics because in-app analytics is a conduit to better decision-making.

Data analysis is no longer the sole domain of a few highly trained technical people. Today, amid the rise of data discovery, making the most of analytics falls on business leaders and other users as much as IT teams. Everyone is expected to be aware of their business domain data to make the right business decisions.

Application teams are now expected to simplify the difficult tasks of data preparation and visualization. Gleaning insight from near-real-time data, visualizations, interactive reports and other capabilities allow application teams to stay ahead of the curve on what’s needed next.

Embedded analytics are the foundation of successful application optimization. Here’s a closer look at how they can save time, increase productivity, lead to innovation and serve customers better.

Centralizing and Automating Analytics to Save Valuable Time

With an analytics layer embedded in your application workflow, you can centralize and automate analytics and reporting processes in near-real time.

Say your organization has dozens of locations, each generating dozens of business metrics, whether data on sales, staffing, inventory or numerous other factors. The data is invaluable. Finding actionable insights, however, might be insufferable without an in-app analytics solution that aggregates and reports the data in a consistent way across locations.


Otherwise, how much time would employees spend gathering the data? How much time would managers or IT teams spend generating reports? Siloed reporting models incur significant development time and restrict the sharing of data that users need.

Automated data gathering and reporting through embedded analytics can yield insights in near-real-time. Managers, team members and members of other teams can review benchmark categories right from a mobile device.

The net result is increased productivity, real-time feedback and efficiency. Embedded Analytics enables business users to spend less time switching back and forth between business applications and analytics tools, and more time on value-added activities.

A More Detailed and Helpful Visual Understanding

Embedded analytics provide application team leaders far more insight than what, say, traditional business intelligence affords. Traditional BI leans on static, often dated reports. Embedded analytics provide more near real-time data analysis and reporting capabilities.

Tools include dashboards and data visualizations of performance metrics, interactive reports with scheduling capabilities, self-service analytics and ad hoc querying to explore user-unique inquiries, benchmarking to compare metrics against peers or other external data, and mobile reporting.

Users get frustrated when basic data analysis capabilities prevent them from aggregating their own data or creating visualizations. Embedded analytics helps application development teams to innovate faster and increase customer satisfaction. The data and insights can yield new features or new use structures and reduce development time. Superior analytics and reporting experience increase customer engagement and draw new customers.

Gaining a Competitive Edge

Application teams have access to near-real-time data to guide decision-making when expectations for turnaround times only grow tighter. With self-service abilities, they can build dashboards and reports that could be tailored by individual business users to their needs. This improves the productivity of the business users so they can spend more time on your core business aspects that set you apart from your competitors. This in turn frees up application teams to focus on new products that help grow the business and create differentiation in the marketplace.

Whether through the additional insights or time gained, embedded analytics reveal new processes and opportunities. They drive innovation.

To remain relevant, an application must do more than yield a set of results or perform a set of tasks. Such a narrow view of its function ignores myriad other opportunities that embedded analytics can reveal. An application’s goal shouldn’t just be transactional (tracking sales activity or managing inventory). The goal should be about selling better and giving a better customer experience of your products. Actionable insights layered inside of existing applications give the business user makes them productive and make better business decisions.

The choice is up to your organization. It can keep plugging along like the more than half of the respondents to an executive survey who said they were not yet treating data as a business asset. Or your organization can embrace data and give your application teams the right embedded analytics tool to take insights and decision-making to the next level, where your organization reaches a wider customer base, expands profitability and remains competitive and relevant in the marketplace.

About the Author: Vijay Pendyala is the SVP of Engineering at Logi Analytics. He has been working in the high-tech industry with a focus on enterprise software, big data analytics, artificial intelligence (AI). For over 20+ years Vijay has held senior and executive-level roles in engineering, product management, data science, and SaaS operations. As a senior leadership team (SLT) member, Vijay has direct responsibility for leading Architecture, Engineering, Data Science, DevOps, and SaaS Operations. My primary responsibilities include building high-performance teams through the software development lifecycle, growing revenue, improving operating margins, and building market-leading products.

Related Items:

Insightsoftware Loads Up on Embedded Analytics with Logi, Izenda Deals

Embedded Analytics Goes Mainstream