Designing Trust Signals: Turning User Behavior into Measurable Drivers of Growth
Regular talk, 9:40 - 10:40 AM
In product-led systems, not all user signals are equally valuable. Self-reported attributes and surface-level engagement metrics often introduce noise, while a smaller set of high-integrity, behavior-driven signals can more reliably predict activation and conversion. This talk explores how to design, evaluate, and scale trust signals using real-world examples from large-scale professional platforms. We introduce a three-part framework for signal quality—Authenticity (verifiability and resistance to manipulation), Relevance (predictive power for downstream outcomes), and Distinctiveness (incremental information beyond existing features). By reframing trust as a measurable property of data, we’ll examine how these signals can be constructed from user activity, validated through experimentation, and incorporated into ranking and recommendation systems. Attendees will leave with practical approaches to separating noise from signal and building data-driven features that meaningfully impact growth.
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Pronouns: he/himBellevue, WA, USA |