Signet iOS App Search

Search

Search is where shoppers go when they know what they want—or think they do. The legacy experience was rigid and lacked guidance. We built a mobile-first search that handled misspellings, surfaced relevant paths, and responded from the first keystroke. With predictive results, dynamic filters, and contextual errors, search became a smarter, more intuitive way to shop.

Partner

Signet Jewelers

My Role

Search UX Design Error Handling Logic Sort & Filter Design Interaction Patterns

Built With

Figma Amor Design System Native iOS Patterns Data-Driven Logic

Outcome

Delivered a mobile search experience that reduced friction and increased conversion.

Kay App 1
Kay App 1
Kay App 1

We engineered search as a predictive layer, not a passive field. As users typed, results updated live—offering keyword predictions and tappable category suggestions. Beneath that, we surfaced relevant product cards in real time, helping users move from query to checkout with speed and clarity.

Kay App 2
Kay App 2
Kay App 2
Kay App 3
Kay App 3
Kay App 3



Jared App 4
Jared App 4
Jared App 4

Intelligent error handling and recent history made the experience forgiving and flexible. When users mistyped a word, we offered smart corrections and fallback suggestions. For return users, recent searches and viewed items stayed just a tap away—reducing dead ends and repeated effort.

Zales App 5
Zales App 5


Intelligent error handling and recent history made the experience forgiving and flexible. When users mistyped a word, we offered smart corrections and fallback suggestions. For return users, recent searches and viewed items stayed just a tap away—reducing dead ends and repeated effort.


Kay App 6
Kay App 6
Kay App 7
Kay App 7
Kay App 7
Kay App 6
Jared App 4
Zales App 5

Search wasn’t a standalone feature—it was fully integrated into the broader system. Result pages carried over sort and filter logic from the PLP, allowing users to refine by price, category, or gender without breaking flow. Every interaction was backed by analytics, giving us a way to evolve the logic with real customer behavior over time.

Supporting Features