Next Glass develops software that uses science and machine learning to deliver personalized recommendations to consumers and breakthrough business tools to breweries, wineries, and retailers. Next Glass has analyzed the chemistry of tens of thousands of bottles of wine and beer, and has stored the "DNA" of each beverage in its Genome Cellar™ database, creating the world's largest database of its kind.
Next Glass had an compelling idea, two developers, a scientist, and no solid product strategy or design direction. I joined the team shortly after their seed fundraising round and helped turn the idea into something that they could use as an initial prototype and start to develop.
Wine and beer recommendations, even from professionals, rely too much on industry buzz or the recommender's own palate.
It's difficult to make purchases for a group with varying tastes.
Selecting a beer or wine at a store can be overwhelming. Folks end up guessing what they like based on arbitrary factors like packaging or tasting notes.
Welcome Screen
Scanning a drink
Personalized Score
Score with Drink Details
Along with early market research conducted by the founder, I conducted user interviews and concept tests to inform early prototypes. After development we regurlary tested usability with unmoderated tests via usertesting.com and incorporated user feedback in feature enhancements.
I created a design that allowed users to rate commonly purchased beer and wine and quickly get recommendations with a score between 1 – 100. The higher the score, the more likely the user is to enjoy the beverage.
Named one of the Apple App Store's best new apps
Reached #5 in the App Store's Food & Drink category