Guiding a risk-detection product through data mining and user insights

Snapshot

Leaders at our client, a Fortune-100 global software company, sought a way to gain a deeper understanding of customer interaction with their software product. If the client wasn’t able to more effectively anticipate and fulfill customer needs, the success of the product was at risk. To ensure the success of the product, the client chose Kalles Group user insights. 

Our customer had released a risk-detection software tool to customers and was working to leverage customer data to determine the direction of further product development. As the company analyzed the data, they were unable to get the level of insight into customer trends they were hoping for. Leaders realized the company needed expertise to identify their blind spots and gaps in understanding, and help translating customer behavior into needed product enhancements. For the data mining and customer insights expertise the company needed, leaders chose the Kalles Group.

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Challenge

In order to learn more about how customers were interacting with the software, the team needed to go deeper into the data. At the time, the client team was only looking at indicators such as volume and number of accounts. The Kalles Group team suggested looking deeper into activity at an individual user level to learn specifically how users were engaging in the software. This would help identify the right data-points to consider, and the right questions to be asking.

The picture of success was a baseline that would identify shifts in customer needs and inform future product goals.

The Kalles Group data experts would need to analyze the database to determine what data was important and how to find that data based on the events being defined and captured. They would need to find the optimal intersecting data points to measure adoption, engagement, consumption, usage, and any defects that users had encountered. Once they’d discovered the correct data, the insights experts would need a way to present the data points visually to make trends clearly visible and remove bias to reveal weighted perspective of who the most important users were.

Approach

The Kalles Group data experts mined the data to identify the right patterns of user behavior that would inform indicators on which the client would base their metrics. From those metrics, the Kalles Group team would create visuals around patterns of behavior, trends, and profiles of existing users. The Kalles Group data experts eventually decided on Microsoft PowerBI to develop a report that could take data directly from the database in real time to paint a picture of user behavior and product interaction.

The Kalles Group team established metrics around the user lifecycle, and immediately they identified a clear opportunity: Customers that had interacted with the software and encountered a problem had never reengaged with the software.

By reaching out to this customer segment, product managers would be able to gain insight into how to make valuable improvements. The team learned from these customers how to make the software more robust and valuable to a wider audience, and the team was then able to prioritize the product changes that would be most valuable to the most important clients.

The team now had actionable data to guide feature discussions and user outreach. In order to ensure the data became the driver for product development direction, the user behavior data was shared at the team weekly review sessions and then socialized across the teams. Soon, this data was the authority relied upon to inform conversation at weekly product development meetings.

Results

Future product features and product goals are now intelligently forecasted based on the user insights report. The team meets regularly to review insights and identify gaps or problems that prevent user adoption, follow trends and indicators, monitor shifts in use of the product, and prioritize software improvements to address the most important clients. The product team can perform more effective customer outreach and support and are making better informed decisions based on data driven conversations. With the ability to stay in step with their customers, the product has a trajectory toward success.  

The picture of success was a baseline that would identify shifts in customer needs and inform future product goals. 

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