The market for searching for food online is exploding. According to one expert at Google, “there are over 1 billion restaurant searches on Google every month” (Kelso, 2020). To capture this market and ride the general digital trend of internet personalization (as evidenced by Google search results, ads, YouTube and social media algorithms, etc), we created Munch to be an algorithm meant to help people find food they’ll love. <br/><br/>Munch offers the ability to search for food by restaurant or even as specific as a menu item (ex: search for the best Pad Thai). The best part? It is customized to your preferences based on a quiz you take when you open the app and from that point continuously learns from your behavior.<br/><br/>This thesis documents the journey of the team who founded Munch, what progress we made and the reasoning behind our decisions, where this idea fits in a competitive marketplace, how much it could be worth, branding, and our recommendations for a successful app in the future.
Included in this item (7)
Details
- Munch: The Better Way to Eat and Experience Dining
- Inocencio, Phillippe Adriane (Co-author)
- Rajan, Megha (Co-author)
- Krug, Hayden (Co-author)
- Byrne, Jared (Thesis director)
- Sebold, Brent (Committee member)
- Computer Science and Engineering Program (Contributor)
- Barrett, The Honors College (Contributor)