Future of Taste

This week, we put together our final presentation of our work, rehearsed it, and presented it. From the presentation, we got more feedback from which we will tweak our work. This is important because in UX, communicating your research and how they impacted your decisions is an important part of the presentation.

We created a logo and visual direction so that as a group we can build out the high-fidelity mockups together. We planned out how we will be presenting the concept so that we know which parts of the user flow to focus on for high-fidelity.

We can finally put our ideas into a visual form!

We have a decent idea of what problems to solve and how we’re solving them, but now we have to test whether the exact implementation works with users. And that’s what our wireframes are for.

We used both Sketch and Balsamiq Mockups for this.

These wireframes were put into Invision so we could test usability and organization of the app. We were then able to distribute the testing as the prototype was accessible over the internet.

We discussed our project direction based off of our AI testing and key takeaways (in our current presentation slides). Users might explore tags or profiles for similar taste and a series of questions based on friends recommending restaurants. We might shift the focus from AI to person-to-person or have a mix of AI and friends to make recommendations. Features we consider incorporating (but not limited to): 

Platform for people to explore and discover their tastes. 1. Profiles can be personalized with taste quizzes and discovery games. 2. Restaurants and places tagged for discovery or direct recommendations. They can give recommendations to friends and receive recommendations. 3. Users can explore general recommendations from location based feed. 4. Discover new people for friends or dating from general feed and tags in common.

A main question of concern was: "How do you bring people together"? and our next step on how should we encompass specific features, functions, group activities, and emotions into the app or tool. Perhaps, we could explore a feature where every time a user wanted to eat they were paired up with someone who is also in the same situation. This could be moderated so that users will be paired up with immediate friends or friends of friends (they may or may not know) based on their preferences similar to LinkedIn or Facebook. There could be other filters such as categories like networking that users would select and be paired up with like-minded individuals. We discussed several apps that have either data visualization or a way to track data such as Mi-fit (originally for tracking fitness, but could be useful for taste tracking), 23&me (data is displayed and can be linked up with another person's for comparison of results), and the Cara App. Our To Do will consist of mock AI to adapt a better dining experience for a user both emotionally and socially. Where the more you track your habits the better the AI or tool will get.

We discussed our progress and thoughts on the journey map, merging data from personas, other technologies, and storyboard. The journey map will be created in InDesign and will be in a Circle graphic. It will cover the experience of the persona's before and after situation. For instance, Ashley (the persona) was overeating and stressed out from planning foods that are gluten free for her boyfriend. Then she hears from a friend or a Doctor who recommends the program. The result is she uses it and is much happier. The persona was determined to be in a relationship since they would seem more likely to want to explore restaurants with their partner. We talked about using mobile device features with voice recognition like Siri to ask and respond to questions regarding food intake in a wearable device form. The AI would be worn on the arm and track eating habits and would interact with the wearer about different aspects based on their food habits and help them achieve goals. (Example situations: tracks what you eat or the types of food you eat.) The other wearable device discussed would appear as a retainer (or Invisalign) device to track what was eaten. Lastly, the storyboard will be a more general experience of a person using the wearable device in a certain way. The team will meet prior to the presentation to confirm all the necessary elements of the presentation.

Big Goals: Learning about self & Learning about self with others.

Platforms: Taste AI, Taste App, Taste Smartwatch, Taste VR, Invisible taste braces(calorie calculator)

Questions:

Where should I eat right now?

Where should we all go to dinner?

How and what should I or we cook?

How many calories am I supposed to eat?

Who would I like to invite to dinner?

How do I become healthier?

How do I find a new favorite restaurant?

Challenges: Collecting data, Keeping data safe, Building customer database.

Product design and development, Modeling and coding.

New tech: AI Machine learning, Voice activation, Tracking movement of eating, Talking Calorie Counter.

Synthesizing data: Visualization of data, Visualization of stats from tracking, making data viewing and sharing fun, Real-time calorie calculator and a reminder.

Tools: A taste butler, taste learning, smart tracker, Gamify taste tracking, A fat & calorie calculator.

Goals to increase:

Incentivize prosocial behavior,

Incentivize more restaurant dining

More educated about food

Easy access to personalized recommendations

Taste Categories:

Selective: Allergies, Diets for Weight Loss, Ingredient Transparency

Healthy: Organic, Diets for health, Health food first

Adventurous: New tastes, novelty, extreme experiences

We had a group meeting today and focused on discussing our next steps prior to the next class and the18th of April. We mentioned screener tests for participants in the future questions. We also created several categories: Adventurous, Selective, Healthy, and Sweet Tooth, which each of our group members will build out a persona. We will place these gathered items into a group document. We will review data from our initial interviews to help in creating these personas and seek additional information from people who fit these categories, as necessary. 

This week, we built two low-fi prototypes and tested them. We gained some insight from each one, which we talk about in our slides above.

We also had a guest lecturer in class today, who had some interesting work experience to share.

This week, we are testing two different app prototypes with real people.

Just as an in-class exercise, we made a quick storyboard and some basic screens for an app that connects people based on their culinary preference

We can credit Marc for the nice sketching

On 21 Mar 18, we conducted card sorting interations in relation to our findings from the contextual interviews on the whiteboard initially. We chose several main categories: Social, Feelings, Health, Tech, and Learning and began placing the cards we thought best matched the main topics. During the second iteration we moved to the wall, there were several cards that were in-between feeling and health. We ended up doing a third iteration in a different location (the table) for a fresh perspective, which eliminated the cards (in limbo) between health and feelings. Then, we voted by tearing a card into 6 pieces attaching our initials to it and placing 3 next to main categories and the remaining  near specific cards inside the category that interest us.

After gaining additional insight and clarity on what contextual interviews were, each team member agreed to conduct individual interviews on 16 Mar 2018. After meeting with Selwa on 19 Mar at 12:30pm-12:45pm, the team understood that we must come together to discuss our individual interview findings. We confirmed today that we will, “Meet in person and do card sorting and voting to synthesize findings.” We created at least three slides pertaining to "new technology findings / technology inspiration” and will continue to tweak and develop our presentation as necessary. 

Our Team joined the check in with Selwa on 19 March to discuss our brief and other aspects of the project. The discussion notes are included in the attached image.