Foodie TV: Date night for the digital age. It has twenty unique pairings of movies with dinner for grub hub to make for a fun adventure in. 
 Traditional clustering of our design was leading nowhere, so we used this insight matrix to gain deeper understanding in the relationship between user insights. Our favorite.
 One of our biggest insights: In our age of custom viewing and single screens, when getting together it is really hard to have two happy viewers.
 This a the product map -- the function structure of all of its pieces mapped to the user's activities. This way, we know user activities are driving the core of product architecture. 
 The insight matrix and function structure led us to this early concept: A self-learning TV. Instead of cataloging the habits of a person, why couldn't screens learn the habits of an entire household? This TV knows its user group watches "Sesame Street" at nine every morning, so it suggests a pared down selection of children's programming and "The Daily Show," since it knows occasionally that show is viewed in the time slot before. Intelligent curation.
 Taking our self-learning TV to our product testers, we learned they wanted more: what else could the television do to create an experience? From them, we came up with the idea of a TV that pairs ordering delivery food with movies. This was a favorite way to socialize with friends, but it involved way too many steps and way too many choices, diminishing the fun. 
 We created a new system that streamlined food ordering and movie selection based on the self-learning TV research.
 Here's an architecture map of the underlying app, including possible future expansions to grow with a business plan. 
 With the maps, it was easy to the build wireframes with the entire team on the same page about product function and how it met user needs. 
 The product UI. We designed it to be fun, light and easy to edit food orders. 
 A direct link to Grubhub makes editing the order easy. 
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