A system for aggregating trust signals across platforms and making them operational.
Role:
Role: Design lead, Co-Founder
System Scope
Focus:
Modeling trust from fragmented signals and translating it into clear, actionable interfaces.
Duration:
Oct 2025 - Current
Status:
V1 designed, in active development
/Overview
Designing a unified system for brand insight, prioritization, and action
Context
TrustLens explores how businesses act on trust signals such as customer reviews, online mentions, search visibility, and social sentiment. While this data is abundant, it is fragmented across tools, making it unclear what deserves attention and when.
Structural gap
Most brand tools treat these signals as separate streams, leaving teams to manually interpret importance and urgency. This results in monitoring without prioritization or clear action. TrustLens was created to unify brand signals into a single decision-oriented system rather than another reporting layer.
Design challenge
The challenge was not collecting signals, but reconciling fragmented inputs into a system that provided both centralized visibility and immediate clarity for decision-makers.
Outcome
A unified brand intelligence system that establishes priority, connects signals across sources, and supports timely action.
/Early Validation
Validating demand before building
Before designing the product, we validated that the problem was both real and actionable through targeted customer conversations.
We spoke with 10 existing customers from a prior product to understand how they monitored brand perception across reviews, social media, and online mentions, focusing on validating specific hypotheses rather than broad discovery.
Three customers expressed strong interest in a unified system centered on clarity and prioritization, and two committed to early agency retainers alongside product development.
This signal was sufficient to proceed, grounding early product decisions in real workflows and demonstrated willingness to pay rather than assumptions.
/Need section name
Designing a system for prioritization under uncertainty
Early research and interviews showed that traditional dashboards didn’t fail due to missing data, but missing direction. Teams had access to reviews, metrics, and mentions, yet struggled to know what deserved attention or what to do next.
Rather than adding another reporting surface, TrustLens reframed the dashboard as a decision system focused on prioritization, helping users understand what mattered now, what could wait, and why, even with incomplete data.
Why traditional Dashboard would fail
/Scope Decisions
Translating prioritization into a usable system
Once prioritization became the core design goal, the product architecture needed to reflect it across every surface.
Instead of treating reviews, mentions, social signals, and projects as separate tools, TrustLens organized the system around a primary decision surface focused on what required attention and what action followed.
Supporting context such as historical trends and aggregate metrics was intentionally secondary, used to validate decisions rather than drive them. This shifted the product from a collection of dashboards into a coordinated decision workflow.
Top of the dashboard
Middle of the dashboard
/Onboarding Tradeoffs
Sequencing early value under onboarding constraints
Because not all data sources could be integrated immediately, TrustLens was designed to deliver value with partial setup.
Low-friction social connections established early baseline insight, helping users orient quickly. Deeper business integrations were intentionally deferred to avoid delaying the first meaningful moment of value.
This approach prioritized momentum and clarity over completeness, while allowing accuracy to compound over time.
/Early System Behavior
Internal testing and UAT observations
Observations from early system testing
TrustLens is still in development, but early system behavior was evaluated through internal testing and a UAT environment focused on onboarding flow and decision surface interaction.
During testing, the primary decision surface consistently served as the natural entry point. Action-oriented prompts were immediately legible, while trend views and historical context functioned as secondary validation rather than primary navigation.
Even with incomplete or simulated data, the system structure made tradeoffs explicit. This allowed us to assess whether prioritization remained understandable as signal depth varied and integrations remained incomplete.
These observations increased confidence that a prioritization-first architecture could remain usable and credible before full data coverage, informing how the system was sequenced toward initial release.
/Outcome & Reflection
What This Validated
While TrustLens remains in early development, the initial system decisions validated several core assumptions.
Users responded more clearly to prioritized actions than raw metrics
Early value depended more on clarity than data completeness
Lightweight onboarding increased willingness to explore, even when insight depth varied
Just as importantly, the process clarified boundaries.
Not every signal needs to be surfaced
Not every feature needs to ship early
Some product questions can only be answered through real usage, not design alone
This case study reflects a shift from designing interfaces to designing decision systems, a perspective that now informs how I approach complex, multi-signal products.
Selected Work.
© Chrisk Studio
A focused selection of product work and the decisions behind it.
