MiVino 4.0

MiVino App


A sommelier designs a wine app with shoppers in mind, unlocking a wealth of potential in the retail sector.

With the help of wine experts, AI, and API’s, MiVino locates the closest store stashing your favorite wine, but also price compares, turns you onto new wines, provides a tasting journal, and most importantly hand picks bottles specifically for you when you send a snapshot of a grocery store wine display with your phone. You now have a growing roster of faves! (And a handy app to help out when they are hard to find).

 
Whiteboard-style compilation lays out the MiVino vision.
 
 
 
  • After spending 5 years of my career as a sommelier, I discovered that wine enthusiasts need help selecting bottles in grocery and retail stores.

    Research: I conducted interviews with patrons of a local wine bar known for its knowledgable team of sommeliers. I asked various guests of the bar about their experiences with choosing wine away from wine bars and restaurants.

    Goals: I sought to find out about current apps/tools that wine lovers may use. What is working for them? What would make their wine shopping experience better? What role does the sommelier play in their wine selection experience?

  • Synthesis: An underlying theme revolved around the relationship between the wine drinker and the wine expert. The restaurant sommelier provides recommendations based on a deep understanding of the product as well as an understanding of the customer. That personalization increases with the frequency of interaction with the customer. Regulars often revisit an establishment time and time again because the sommelier knows their palate and what they like to drink. When the sommelier is taken out of the equation (i.e. a grocery store setting) the wine shopper experiences these Pain Points:

    • Too many options

    • Difficulty locating specific wines, trouble remembering a particular bottle that they loved (or didn’t love)

    • Frustrated with running around town in search of a particular bottle’s availability

    Analyzing my research, interviews, and my recollections as a sommelier, I determined the product’s Main Funtions:

    • Locate wines catered to the user’s preferences within a store using current location

    • Locate a specific wine within specified driving proximity to the current location of the user

    • Create wine journal entries that lock in special memories, wine specs, and personal notes about a wine

    User Persona: Marsha was developed from a combination of my research findings and years spent observing the actions and behaviors of customers I served at wine bars and restaurants.

    Problem Statement: The customer cannot find that wine they were served when they are shopping at a grocery store, and they are not sure how to find something similar. The selection is overwhelming and the lack of expert help can be discouraging. On top of that, they’re in a hurry and the whole aisle is crowded and disorienting.

    User Story: “As a wine shopper, I want to choose wines confidently and quickly so that I can finish my grocery trip and get home to my family.”

  • Ideation: I sketched multiple user flows based on the problem statement and user needs: Personalization, specific wine location, and wine journaling.

    Prototyping: After wireframing a few low-fidelity prototypes, I gathered assets to create a high-fidelity prototype of the new app design in Figma, focusing on key functionalities and user flows.

    Usability Testing: I conducted usability testing with wine shoppers to evaluate the effectiveness and usability of the prototype, further polishing the product to prepare for development.

  • Iteration: I designed a prototype for an app to be used on a mobile phone that delivers main functions in a quick, user-friendly way.

    Development: As it is, the final design assets and usor flows of the minimum viable product are ready to be handed off to developers for implementation, where Google Maps API, Google Lens, and the in-phone camera will power the main functions.

    Launch and Measurement: In addition to testing, monitoring usage data and user feedback to identify further iterations of the MVP, the future holds space for AI to be implemented into the compiling of tech sheets for wines, and eventually the formatting of said sheets to conform to the design language of the MiVino brand. Iteration: Refine the design based on feedback from usability testing. Repeat the develop and deliver stages iteratively until a user-centered and effective design is achieved.