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Tippie Business Analytics team gives Kum & Go crucial insights into its most loyal customers
As a company with a strong loyalty program, Des Moines-based Kum & Go convenience store had collected a trove of customer data via their rewards card usage. The logical next step? Taking what they’ve gathered and finding ways to use it to drive growth.
That’s where the Tippie Business Analytics team came in.
Master’s students Nathan Childress, Kate Lindaman, Adam Palmer and John Staak paired up with Tippie alum and Kum & Go Data Analyst Jane Simpson to see how they could take all those numbers and turn them into an actionable marketing plan. The project was a chance for the students to learn not only how to extrapolate insights from millions of customer records, but also how to present their findings to a group of high-level marketers and executives.
With that much data, deciding on a direction was challenge number one.
“You need to think methodologically before you dive in. These 20-30 million rows of data could have been looked at 100 ways. So you have to determine the end goal, then work back.” Adam Palmer, MBA
Since Kum & Go had asked the students to define 6-8 loyalty customer segments, the team decided to perform a cluster analysis to identify commonalities within the millions of seemingly disparate data points. By drilling into the frequency, type and size of customer transactions, they were able to parse out unique shopper segments which correlated to patterns of behavior.
Once the segments were grouped by customers who shop in similar ways, the team developed personas such as “Fountain Fanatics” and “Meal Dealers.” They also recommended promotions for each, like donut discounts for frequent coffee buyers. This approach demonstrated to Kum & Go leadership how data analysis could translate into an easily understood marketing plan.
“Analytics is not just reporting, but more about classification and AI, which is new to our organization," said Kum & Go's Simpson. “Because the students presented to a large group within the company, it got more people interested in how we could use clustering models in the future.”
The students demonstrated the usefulness of data clustering by highlighting actionable recommendations over technical terminology in their report. Because communication is at the core of Tippie’s business analytics curriculum, they knew exactly how important it was to deliver a clear, relevant insight to the company’s marketers and execs.
“We had to make the presentation digestible to a non-analytical audience. So when they saw the personas, they could think ‘This looks like somebody who would come in to the store. It’s behavior we’ve seen,’” said MBA student John Staak.
Kum & Go plans to adopt the students' presentation style for their own internal analytics reports in the future. The customer insights the team discovered will inform the way marketers at Kum & Go develop personas and target their promotions going forward.
“The most valuable thing that we got out of the project was learning how we could use clustering to come up with offers and improve interactions with our customers.” Jane Simpson, Data Analyst, Kum & Go