Shaping a scalable platform for brand intelligence.
At
The Harris Poll
Industry
Enterprise SaaS, Brand Intelligence
Why it mattered
Brands needed to understand perception in a constantly shifting landscape.
Consumer opinion changes quickly, influenced by media cycles, campaigns, competitors, and cultural moments. For brands operating at scale, understanding how perception evolved over time was essential, yet often fragmented across static reports, delayed research, or disconnected tools. Teams needed a way to monitor brand health continuously, not retroactively. QuestBrand set out to provide always-on brand intelligence across hundreds of brands, competitors, and audience segments. The challenge was not collecting data, but turning an ongoing stream of raw inputs into something decision-makers could trust and act on without waiting weeks for answers.
Raw data alone wasn’t useful without structure, context, and restraint.
The underlying data arrived dense and unfiltered, often in raw CSV form. While powerful, it required significant interpretation before it could inform real decisions. At the same time, the platform needed to serve a wide range of users, from research experts to generalist marketers, without overwhelming either group. The opportunity was to shape a platform that balanced depth with usability, flexibility with simplicity, and scale with coherence.
Structure and direction mattered more than features at the outset.
What I shaped
A coherent product foundation for a broad, multi-user platform.
QuestBrand was shaped as a unified platform rather than a collection of isolated tools. Product direction and interaction models were guided toward consistency across brand equity, conversion funnels, profiling, trends, emotional imagery, and ad recall. This foundation allowed different user types to navigate the platform confidently, even as use cases varied, and ensured the experience scaled without fragmenting as new capabilities were introduced.
Usable visual systems for dense, always-on brand data.
Design patterns and visual frameworks translated raw, high-volume data into interfaces that supported exploration and comparison without overwhelming users. Emphasis was placed on hierarchy, progressive disclosure, and meaningful defaults to help users move from overview to insight efficiently. Feature prioritization favored repeatable patterns over novelty, keeping the platform flexible while maintaining simplicity as the dataset and audience grew.
The impact
A trusted platform that scaled across brands and teams.
QuestBrand launched as a 0 → 1 enterprise platform capable of supporting continuous brand tracking across portfolios and competitors. Teams were able to move faster from data to insight, evaluate campaigns in closer to real time, and adopt the platform across multiple brands within the same organization. The product established a scalable foundation that supported both depth for expert users and accessibility for broader marketing teams.
Always-on.
Replaced periodic brand studies with continuous brand tracking.
Multi-brand adoption.
Used across multiple brands within the same organization.
Strong platforms emerge when direction holds steady as complexity grows.