Wharton@Work

October 2021 | 

Understanding Customers: Toward a Data-Driven Culture

Understanding Customers: Toward a Data-Driven Culture

As the global pandemic waxes and wanes, uncertainty continues. At the same time, sweeping changes are occurring in consumer behavior, priorities, and buying habits, according to Forbes and other media outlets. Companies are scrambling to stay ahead of trends, and to determine which changes are fleeting and which can be anticipated long term.

In this challenging environment, mastering customer analytics becomes more critical than ever. With that urgent awareness, three executives from Waste Management, the leading provider of sustainable waste services for homes and businesses, recently enrolled as a group in Executive Education’s Analytics for Strategic Growth: AI, Smart Data, and Customer Insights. The program is intended to help executives leverage their company’s data to the fullest, sharpen their analytics mindset, and implement a fully digital business strategy.

“We really wanted to advance how we use customer analytics within the company to shape business processes,” explains VP of revenue management Mike Solheid. “How we evaluate annual price increases with our existing business; how we can implement targeted retention activities. The ultimate goal is to grow profitability.”

In fact, focusing on the customer is a major priority at Waste Management, explains Michael Castronovo, senior director of revenue management. This was one factor that drew both men to the Wharton program. Another deciding factor was that Castronovo and Solheid were already familiar with Wharton marketing professor Peter Fader’s books, including Customer Centricity, and Fader teaches in the program. Castronovo calls Fader’s work “something of a model for how we’re implementing this concept of putting the customer at the center of everything we do.”

“Given Pete Fader’s role in this program, it naturally jumped to the top of the list in terms of the right fit,” adds Solheid.

Solheid elaborated on Waste Management’s need to expand its customer analytics capabilities. “Over the years, within some lines of business, we've gotten into predictive analytics to say, for example, ‘The likelihood that this customer defects based on certain attributes is X.’” But he wants to evolve that further, to understand “what that means not just to today’s defection, but to longer-term value for the company.” This understanding could yield important prescriptive actions to recommend to frontline agents, salespeople, and drivers, he says, regarding how best to interact with individual customers in various scenarios.

Both men gave the program high marks, saying they particularly appreciated the faculty’s real-world approach and their focus on practical applications to business. Solheid was glad the program’s main content was on “how to draw insights from the analytics and what to do with those” rather than the technical aspects of data science. Castronovo comments, “The Wharton faculty from Eric [Bradlow, PhD] to Raghuram [Iyengar, PhD] to Peter [Fader, PhD] brought in energy and excitement — they were very approachable and used business-friendly language.”

Castronovo says a big takeaway for him was the idea that there is no one monolithic “customer.” For example, if the company misses a trash pickup, “a first-year customer is going to have a very different experience with a service interruption than maybe a seven- or eight-year one with whom we have a pattern of interactions.” Among Waste Management’s hundreds of thousands of customers, “the analytics help us understand individual customers’ experiences and the impact on them.”

Solheid notes that the program specifically helped him and his team determine how to communicate internally about targeted, analytics-based retention campaigns. The program also helped the team formulate how to use an A/B environment to test the effectiveness of those campaigns.

Both Castronovo and Solheid say they also appreciated gaining a better understanding of different analytical and statistical methodologies, which would help them more clearly communicate with their data science team. “Even though I can’t write the code, now I can more effectively ‘talk the talk,’” comments Castronovo.

Having colleagues from Waste Management attend the program at the same time was definitely an advantage, they say. Castronovo notes that the group would occasionally message each other during class to highlight particularly useful concepts. Solheid says that attending together “allowed us to have follow-up conversations, brainstorm about what we learned and how we want to apply it.” Above all, the program gave both executives greater confidence and external validation for their company’s customer analytics initiatives. As Castronovo puts it, “It gave us an energy boost… It confirmed we were on the right road.”