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Beyond ROAS Using Amazon Signals and CLV to Underwrite Marketplace Growth Quality (12)
11 AM (PT) / 2 PM (ET) - Thursday, August 13, 2026

Beyond ROAS: 

Using Amazon Signals and CLV to Underwrite Marketplace Growth Quality

Growth on Amazon can make a brand look stronger than it really is. Sales and ROAS may rise, but investors and operators still need to answer a more important question: is that growth creating durable customer value, or simply buying the next order?

Join Theta and Pattern to see how Amazon signals and CLV can be combined to move beyond short-term channel ROAS and assess the true quality of growth. We’ll explore which products attract valuable customers, which campaigns drive repeat behavior, where paid spend may be masking low-quality demand, and how these insights can support diligence, value creation, and board-ready growth planning.

On Thursday,  August 13th,  we’ll explore:

  • How to distinguish healthy marketplace growth from growth that is overly dependent on paid spend, promotions, low-margin SKUs, or one-time buyers.
  • How Amazon and marketplace signals can help diagnose revenue durability, customer quality, and channel risk.
  • How CLV and customer-based corporate valuation convert transaction and cohort behavior into forward-looking revenue and margin expectations.
  • How investors and operators can use these insights during diligence, value creation, budget allocation, and exit preparation.

Speakers: 

Untitled design (4)

Daniel McCarthy

Co-Founder, Theta

Dan McCarthy is an Associate Professor of Marketing at The Robert H. Smith School of Business at the University of Maryland. He is a marketing scientist and methodologist specializing in applying leading-edge statistical methodology to contemporary empirical marketing problems. His research interests include data fusion, limited /missing data problems, machine learning, and causal inference.

Ryan Steggell

Ryan Steggell

Director of Artificial Intelligence, Pattern

Ryan Steggell is Director of Artificial Intelligence at Pattern, where he leads AI-driven e-commerce analytics, predictive modeling, and commercial intelligence initiatives. He combines deep expertise in marketplace advertising, machine learning, and business intelligence to help brands turn data into decisions. Ryan specializes in connecting marketplace performance with long-term customer value.

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