Vera Recommendation Engine

Visual Design
Retail and Ecommerce
Product Designer / Design Lead

Vera is a shopping recommendation engine, providing shoppers with outfit suggestions based on a curated set of social media data. Instead of buying items based on shopping patterns or data-driven popularity, shoppers can be inspired and explore clothes based on what people are actually wearing nowadays.

The project existed in various iterations before my time at the studio. For the current product, I was responsible for redesigning user flows (including the pre-screen experience of a user in-store), wireframing new interactions, and designing the visual look and feel of a demo version at the National Retail Federation's Expo 2019.

↑ Rendering of Vera in store, adopting a click-and-brick model.


The primary users for Vera would be a retail shopper, as well as an employee or team member.

Vera enables a shopper to:

↑ Sketches for interface and product cards.

The interface borrows from interactions and behaviors of online shopping. More importantly, shoppers can directly communicate with employees on Vera to try on their selections. This eliminates the hassle of locating an employee on the sales floor, physically waiting in line to try on clothes, and finding out at the very end that the store is out of a certain size or color.

↑ Visual design mockup of Vera for landscape aspect ratios.

The following screens describe the primary journey: splash, load, feed, product cards, and shopping cart:

↑ Animations of main screens, microinteractions, and transitions.


↑ Wireframes for ecommerce web plugin.

NRF 2019

NRF is an annual 3-day industry event for retailers and retail tech to gather around new products, technology, and ideas. We debuted Vera at the 2019 convening.

↑ Images from the National Retail Federation Expo 2019, including a booth with demo versions of Vera as well as an informational poster I designed.