Borrowed and Blue
A transactional marketplace and inspiration platform connecting couples with local wedding vendors.
Site redesign
One of the most significant impacts I had at Borrrowed & Blue was overseeing a complete site redesign. The redesign happened in conjunction with a Rails upgrade, changes to our database models, and significant front-end improvements. I worked closely with our engineers to deliver the new site on a short time frame.
Development was hampered by a lack of consistent components and styles. I developed a new, simplified style guide and worked with the engineering team to streamline our components and layouts.
We significantly improved page speed and pages per session. The improvements to search were lauded by vendors as a simpler and friendlier way to manage their profiles. Smarter organization and usage of data led to nearly 3x faster page loads.
Data modeling
Our database models hadn't been designed with flexibility in mind and the entire product was essentially locked into fixed silos. Every vendor was locked in a [location]/[category]/[profile] structure.
It was possible for vendors who had a "home base" in Boulder, Colorado to not be listed in Denver, Colorado – merely 20 minutes away, because Boulder and Denver were distinct "locations". This significantly hampered growth and usability once B&B decided to launch "nationwide" with their vendor and wedding database.
We reworked the site architecture and models to allow for vendors to have multiple "working locations" and support a radius-based search for local wedding vendors.
We redesigned the homepage experience to allow visitors to dive straight into a specific search type.
Vendors reported that the re-worked experience made managing their B&B presence significantly easier. User testing and analytics indicated that couples were able to execute their searches with less confusion.
Photos
We built a massive database of wedding imagery by working with local photographers and vendors. The goal of this project was to 'unlock' that imagery from being siloed in individual "wedding" galleries.
Our unique dataset allowed us to build an experience that allowed couples to have a Pinterest-like browsing experience, but also filter by location or venue – creating a shorter path to finding a vendor they might actually use.
We used vendor data and computer vision to build tag data on each image. We used that data to identify the key filters/categories that couples were interested in (rings, flowers, centerpieces, dresses, etc)
Photo detail pages surfaced the appropriate vendors for that photo, provided a way to expand on that particular wedding, and suggested related images based on location and vendor.
The new photo browsing experience allowed us to significantly increase page views and time on site by providing a more dense and relatable web of "rabbit hole" content.