Activating the Data in a System Application


Data Challenge Status

We've reached the end of our Data Challenge journey. You can look back on the process and steps that got us here.


Now we’re getting to the point where the rubber meets the road. All the evaluation, planning, and strategic analysis is finally being realized in an end-user application. At this point the application is ready for a full development and launch use by a bank’s sales and marketing team to begin supporting outreach to prospective customers.

Understanding analytical relationships in data

There’s a common misconception about what the term “analytic” means. Many people assume that an analytic is primarily the visualization of data. In fact, an analytic is a more complex term, which encompasses the identification of a clear business objective, the data analysis that produces an insight related to that objective, the process for accessing the source data on a business-relevant cadence, and then finally delivering it to stakeholders in a usable format (often a visualization, action list, or notification).

In the analytic development process, the visualization of the analytic, while the most visually impressive, is just the final stage. However, that doesn’t mean there aren’t some important considerations around how the analytic should be delivered and visualized to drive adoption response and effective use within a bank.

Selecting a Data Visualization Method

There are a number of tools that can be used to produce data visualizations. Some of Datanova’s clients have preferred business intelligence tools, such as Power BI, QlikView, or Tableau which they use to deliver data and insights to business units and end users. These tools are powerful and customizable, but also require some degree of expertise and planning to configure and deploy in an organized way. The EVLVE system is set up to deliver analytic data directly into these tools.

EVLVE also has a built-in Application Environment, which enables the fused and processed data to be accessed directly from a single user interface. This Application Environment has the benefit of consolidating an entire organization’s library of analytics into a single interface, where all users can access data and analytics in one place.

For this Data Challenge, we’re using the EVLVE platform to stage the analytic that we sketched out earlier in the planning process. Below is a screen shot of the executed Newly Opened Business Segmentation analytic, as deployed in the EVLVE application interface.


This analytic delivers on the earlier sketch, with some minor modifications around the faceting related to business size, which wasn’t a variable that was provided in the source data. While this variable could be appended through other sources, we kept the final deployment more simple, with size segmentation identified as a possible refinement moving forward.

Tips for building and staging data analytics and applications

Regardless, of whether a bank chooses to use its own tools or to leverage an out-of-the-box analytics platform like EVLVE, there are some key things to consider about delivering data analytics:

  • Consolidate analytics (as much as possible) into a single access point

    Every business system now comes with its own analytics, whether it’s an email marketing tool or website analytics. The fact that these analytics are maintained in different systems with different access points (and login information) makes it common for people to self-select their own analytics and information siloes. While it’s not always possible to pull all of a bank’s analytics into the same dashboard or platform, the more the vital business analytics from a bank’s various departments can be accessed in the same place, the more likely it is that the data insights will also foster cross-departmental collaboration.

  • Build in feedback points

    Data visualization can sometimes be a one-way path out from a central insights engine to the people completing tasks using the underlying data (sales, marketing, operations, etc.). Even the best planned analytic can benefit from refinements over time as users start applying the analytic outputs to their jobs. By providing simple feedback points from users, such as a comments form submission or rating system, it’s possible to identify opportunities for refinement.

  • Enable (but don’t require) exploration

    Most users don’t want to explore data, they just want enough information to do their job. However, there’s frequently an ambitious “data hound” tucked away a bank’s operations, sales, or marketing department, just waiting to explore and discover new opportunities and applications. Sometimes these users can be empowered to explore in very simple way. The EVLVE application includes an end-user, multi-faceted search that enables all users to engage directly with the underlying fused data (while still ensuring appropriate data security and privacy) and try out other ideas. Who knows where the next great idea will come from?

Launching and Evolving the Application

In a bank that already has the baseline EVLVE platform installed, the launch process is essentially seamless. The data transfer from Leadbird is set on a schedule and the application applies the product fit algorithm as the new data flows in, staging it in the application for business units to act on.

Over time, the application and product fit algorithm can be tweaked through user feedback and performance tracking. Additionally, the same analytical insights can be applied to new use cases, such as existing customer cross-sell programs. These new, derivative analytics can be quickly deployed even more efficiently than this test case we’ve walked through in this blog, since many of the same data points and analytical processes are repeated.

Datanova Scientific