“Data literacy is not a math or science skill. It is a life skill. It is for everyone!” Dr. Kirk Borne, Principal Data Scientist at Booz Allen Hamilton, shared these words in a recent webinar sponsored by Logi Analytics. He refers to this concept as . It’s the driving force for why self-service matters in your application’s analytics solution. Self-service analytics enable users of any skill level and job type to discover insights that tell stories about the data that’s available to them.
Learn about the five types of data stories users commonly find in their data that lead to “Aha!” moments. Then see what kind of “Aha!” moments your data is waiting to tell you.
Your data can give you the simplest signal or precursor about something big waiting to be found. The signal can be as simple as tracking the number of web clicks a customer makes to their account. Once you pick up the signal, it can lead you to future sales and marketing opportunities.
For example, a financial services company discovered how to detect customer churn and prevent it by analyzing the number of times customers accessed their web account. Dr. Borne explains in the webinar how they did it and ended up saving an estimated $1 billion in customer value.
Anyone in your organization can find insights, not just the data science team, machine learning engineers, or database people. They can detect patterns or contextual events in the data that might result from an external event. These events present opportunities that can noticeably impact the performance of your business.
Consider the example of a sales team at an organization that noticed a dip in sales over an entire day that trended across the US from coast to coast. In the webinar, Dr. Borne explains what phenomenon caused it and what the company learned from it to create future business value.
By observing behaviors and exploring data, you can discover how situations leverage each other. For example, an increase in sales of one product and subsequent sales of a related, higher-priced product might determine the best time to upsell customers.
As Dr. Borne describes in the webinar, an electronics company experienced this situation that led them to a successful marketing campaign. He shares how the company timed promotions based on the previous purchase of an item that resulted in the increased sales of a more expensive item.
Companies can no longer afford to have just the data scientist or only those with data access to take action. Everyone in the company should have the ability to look at the data and be empowered to speak up. They need the opportunity to communicate to the right people and create value when they gain insights from the data—the “Aha!” moment.
Dr. Borne says, “If you see something in the data, say something. That’s really the true meaning of data democratization.” For example, a database engineer’s keen eye for detail resulted in a simple gesture of celebrating a child’s birthday on a flight. In the webinar, Dr. Borne explains how that small gesture created a big boom for the airline company.
In this mobile analytics world, the three most important things for customer intelligence and business intelligence are “location, location, location,” according to Dr. Borne. He refers to data as the new space-time continuum that can provide that location information.
A customer’s location can signal intent, such as what they need or want to do. By checking location data, companies can offer timely services. For example, a mobile cellular company tapped into the location data of its customers to create timely offerings. Dr. Borne explains how simple insights and context led to a successful marketing campaign at the right place and the right time.
Anyone in your organization who uses digital information and data can make a positive impact on your business. As each of these data story types indicate, finding that “Aha!” moment in your data leads to business value. Learn how the companies in each of the examples in this post found their “Aha!” moment. Dr. Borne shares their stories in the webinar: Maximizing the Business Impact of Data through Self-Service Insights Discovery.