Ep. 239: Dan McCarthy | Food for Thought: How External Data Analysis Can Unlock Competitive Insights

Customer Confidential: Untold Stories of Earned Growth

Episode 239: What hidden insights can customer behavior data analysis reveal about how successful one food delivery app may be over another?

Discover how analysis of externally sourced customer behavior data can fuel dramatic improvements in revenue forecasts and strategic decisions. See how competitor data analysis can help identify strengths and weaknesses that are otherwise hidden.

In this episode of Customer Confidential, we’re joined by Dan McCarthy, director and co-founder of Theta and Associate Professor of Marketing at the University of Maryland's Robert H. Smith School of Business. Dan shares findings from Theta and Bain & Company’s jointly published consumer purchase data study, “Customer Lifetime Value across Food Delivery Competitors.”

Together, Dan and Rob explore how they used a proprietary database of credit card transaction data from Pyxis to track customer behavior for subscription services over five years. They describe how accounting for corresponding economic factors like seasonality and the Covid-19 pandemic helped improve forecasts of transaction velocity, spending, and retention. Learn which food delivery app had the best customer loyalty, the most customers, and highest per-customer spending.

Guest: Dan McCarthy, Director and Co-Founder of Theta, Associate Professor of Marketing at the University of Maryland, College Park

Host: Rob Markey, Partner, Bain & Company

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Time-Stamped List of Topics Covered:

• [02:00] Introduction to customer behavior analysis and business forecasting
• [05:15] How companies can use historical data to predict customer lifetime value
• [10:00] Insights from customer data and the role of subscription services
• [15:30] The impact of external factors like economic shifts and market changes on consumer behavior
• [20:00] How businesses can improve acquisition and retention strategies using data
• [25:00] Using customer lifetime value to forecast future revenue and business growth

Time-Stamped Notable Quotes:

• [02:45] “The notion of having a consistent data set with multiple companies in it so you can compare … all these different food delivery companies [means] you can explicitly see them and you can see the same consumers buying across them.”
• [05:37] “It’s primarily taking these different vintages of customers—where a vintage is defined by, ‘When did that customer make their very first purchase with your firm?’—and then within that vintage, what we want to explain is what these individual customers are going to do in the future.”
• [07:42] “[The data] is what allows us to say things like, is this company acquiring customers well? Are they retaining customers well? How frequently are they buying? And how does that compare across different companies?”

Additional Resources:

• Customer Lifetime Value across Food Delivery Competitors
• Pyxis by Bain & Company