Online shoppers are overwhelmed with choices. Originally pitched as the “pandora for clothes”, Tailored Fit uses an algorithm with over 1,200 clothing data points to aggregate the top picks for each shopper. Interacting via web or mobile, the more that shoppers “heart” items, the better the recommendations.
October 2013 - October 2014
AlphaLab, startup accelerator
1st Place at Startup Weekend Pittsburgh
How our startup began
I joined Startup Weekend Pittsburgh 2013 as a curious designer. Within 30 minutes, I met Nat, a guy with a great idea, and we quickly formed a team. We landed first place that weekend and I left as the UX designer and Nat as CEO of Tailored Fit. In 2014 we were granted seed funding and accepted into AlphaLab, one of the top startup accelerators in the country, and later became one of their companies-in-residence.
Tailored Fit was a ripe opportunity to test my maturing skills on a live product while I pursued my graduate degree in Human-Computer Interaction. I supported the team through continuous rounds of ideation, wireframing, and user testing
all of your shopping in one place
With one easy interface, Tailored Fit eliminates the need to jump from site to site. Quickly "heart" and "dislike" items to see recommendations that match your taste. According to top users, they loved Tailored Fit because it provides a new type of personalized fashion exploration.
We created the Clothing Genome Project, which learns your style to help you find the perfect match
Next Step: Localized Recommendations
Taking recommendations one step further, Tailored Fit began developing a product to help vendors reach consumers in the physical world in real time.
Imagine your boutique on a bustling street full of shops. Now imagine the ability to push product recommendations to consumers walking by – they love what they see, stroll in, and you've already prepared their item, in their size, with a dressing room waiting.
With iBeacon technology, this could become the new norm. We began working with a popular, brick & mortar boutique in Pittsburgh, e.b. Pepper, to pilot this service.
With endless options of retailers, online shopping can be burdensome and overwhelming
We explored the way that people shop for clothes. We did this through ideation, competitive analysis, prototyping, think alouds, and user testing. Using a lean methodology with scrum, we iterated upon our beta release with customer feedback, redesigns, and new features. The website saw monthly updates and the mobile app was released just six months after the company began.
A researcher and designer, I combed user feedback for key insights, which I then translated into design recommendations. Our team filtered insights based on business value and effort, and channeled these into new mockups for beta testers every few weeks.
Some iterations of the Tailored Fit web application:
Throughout the lows and highs of startup life, we persevered in our solution to the overwhelming shopping experience. In 2014, after an amazing year together, we made the tough, thorough decision to discontinue Tailored Fit. I learned the value in calculated pivots, being honest as a team, and how far passion and focus can move a product.