KSU Masters Project Journal
Week 8 - 9

Kent State University - Master's Project Proposal Spring 2018
 

Smart Kitchen: The Amazon Fresh Refrigerator & Voice-Based UX Integrated Alexa

Week 8-9 - Scope
 

  • Developmental model
     

  • Short Interviews with participants on the 5 areas of focus.
    1. Searching for food ideas and recipes
    2. Comparing recipes
    3. Acquiring the ingredients
    4. Learning to cook recipes
    5. Sharing experiences

     

  • Links: Mental Model Example

Mental Model Topics of focus

Participants for the mental model questions

Interview 01 - Janaca  July 02, 2018 - Second interview

Interview 02 - Rob  July 02, 2018 - Second interview 

Interview 03 - Evelyn July 04, 2018 - Second interview

Interview 04 - Howard July 04, 2018 - First interview

Interview 05 - Marla July 06, 2018 - Second interview

Mental model questions and topics of focus

The following areas of focus have been defined as a hypothesis of what I believe to be the most important in the journey of discovering new foods and new food recipes in the SMART kitchen experience.
 

  1. Searching for foods
     

  2. Finding recipes
     

  3. Acquiring the ingredients
     

  4. Learning how to cook the recipes
     

  5. Sharing your experiences - Ideas, comments, notes, issues, photos, food creations, stories, etc.


 

 

Mental Model Findings
 

Mental Model Topic: Searching for foods and Ideas (Recipes)

 

 

One interesting finding relating to searching for food ideas and recipes ones that 3 out of 5 of the participants agreed that the billet he to compare two recipes against each other for their nutritional value and ease of cooking was important to them. Additionally, 3 out of 5 participants suggested the recipes should be sponsored by outside entities specialize in and cooking and recipes. For instance Epicurious. Other suggestions reflected that sponsored links, logos, and possible other description information be provided. When it came to the Alexa audio instructions participants suggested Alexa should be able to filter out food allergies, consider their past preferences, and consider starred or favorite past recipes they have cooked in the past.

 

Additionally, artificial intelligence comes up in the discussion. Participants commented that within the Alexa audio instructions should suggest or expect Alexa to learn from their previous food style choices. This artificial intelligence expectation expands into their past nutritional preferences as well.

 

Joyful experience note: If Alexa was able to suggest keeping amino under 500 cal because your past eight out of 10 meals fell under 800 cal this might be a cause for Joy as a and experience for a user.

 

When it comes to nutrition, some basic information was also suggested. Basic nutritional values such as fats and carbohydrates could be displayed in a small but concise area in the search result listing. Additionally, the ability to change this listing by serving or by meal quantities. Possible sponsored sources could also be listed in this area and were suggested by the participants. Specialized search filters we're suggested as well. And autocomplete, ethnic categories, the ability to filter by food and drinks, as well as celebrity chef recipes.

 

Photography quality came up and the ability to favorite by the hero image of the recipe was a consistent 5 out of 5 requests from the participants. The ability to use Pinterest as a way to socially remember their favorite foods and food recipes was also a top suggestion. When it came to the description within the construct of the search result listing, Wiki links, user review ratings, and user review comments that were short and sweet also arose as desirable expectations.

 

Because the refrigerator is smart and some of the assumptions require the refrigerator to take into consideration what you already have in the fridge that was purchased through Amazon. An indication in the search result listing for recipes that required ingredients you had in your fridge already was a powerful idea that surfaced from off of participants.  This could easily show up as some degree of indication in the search result for a way for instance for users to easily move through foods that are already opened or currently in use within the refrigerator already or a SMART FRIDGE FILTER. Lastly, preparation time and the approximate cost per meal with the ability to change the number of people expected at your table completed the searching for food ideas segment of this mental model.

Mental Model Topic: Comparing recipes


The ability to compare recipes was part of my original hypothesis in terms of looking at the five major areas of focus for this project. Often, images, short descriptions, user ratings, and photography can help users quickly and easily decide when comparing two different types of foods for a meal. The results from the participant's discussion where is following. The participants felt as though the Alexa audio instructions should include the ability to ask Alexa to compare to selected recipes by nutrition, popularity, as well as ask Alexa for options to substitute out ingredients for alternate options. Additionally,  some participants felt as though they should be able to allow ask Alexa to compare her recommended ingredients with ingredients that they could potentially purchase outside of Amazon.

 

The majority of the participants sampled agreed that the content-length be short.  In this case potentially one paragraph or a short one paragraph. Participants suggested sponsored links such as curious as well as food sensitivity awareness is and a possible rating system. Long-term suggestions included rating reviews by other members on Amazon. When it came to cost,  participants were curious what the total cost of the 2 compared meals would be broken down by serving and or the entire recipe.

 

As with the previous Dimension, photography and photography quality, we're high on the list.  all participants agreed that the quality of the photo would probably assist them and make their mind up 50% of the time or more.

 

Comparison by nutrition was also questioned in the participant sample. Diet types such as vegan vegetarian were suggested as a possibility that when clutch could lead to further suggestions for the user. Other obvious nutritional information such as fats, Sugar's, and carbohydrates as well as a possible link to the FDA surfaced.

 

Prep time that was easy and simple to understand by hours and minutes, as well as total prep time or total cook time rather, completed the comparing recipes dimension.

Mental Model Topic:  Acquiring the ingredients



When it comes to acquiring the ingredients, my original hypothesis was that the ingredients list ultimately transformed into the cart. after further consideration, I'm starting to rethink the ease of understanding and ingredients list also doubling as a cart for our Amazon smart refrigerator. With that being said, I had some sensitivities to asking questions that were not originally planned for the mental model. The Alexa audio instructions that participants suggested included the ability to show all required ingredients, show me what I have in my refrigerator, show me substitutes, by all of the ingredients I need even if I already have ingredients left over in my fridge, and lastly, compare with prices outside of Amazon.

 

Users also recommended Amazon recommends Graphics that they are already used to seeing on the Amazon platform. This led to further discussion regarding the list of ingredients all being branded Amazon recommends. The participants suggested the ability to swap out the recommended option with other options of their choice. Recommendations could change across the entire cart or ingredient list by filters such as cost, user popularity, and nutritional content such as low-fat. Additionally, he's a purchase via the expected delivery time surfaced as a point of discussion among the participants. A further concern regarding the ability to purchase items that were low in stock also was concerned that users wanted to be aware of when planning recipes beyond the next 48 hours.

 

Participants were also interested in the ability to access information about the products they were choosing or considering placing in their cars. Again, the expected delivery date surface as a primary concern when thinking about acquiring ingredients.

Mental Model Topic:  Learning to cook recipes

 

 

The ability to learn to cook these recipes goes beyond the concept of a minimum viable product in my opinion. However, the ability to teach a user how to cook the recipes and Foods you're bringing to their homes, in my opinion, is where the joy comes into play with this entire concept. Additionally, the ability to educate users to use foods and food recipes in unique manners and form a brand adoption of sorts for Amazon.

 

Videos, images, customized Alexa audio instructions, and step-by-step guidance are some of the areas of focus within the dimension of learning to cook recipes. All of the participants agreed that easy to watch and short but concise videos complete with progress bars and other expected buttons such as the pause and play button would a system in learning to work with foods are unfamiliar with quickly. Once again, high-quality imagery clearly broken down and step by step procedural increments in a low cognitive impact page would also score high with participants and future users. Language dialect, next and previous buttons for the next step or previous step as well as cooking technique terminology links or definitions and possible tools required surfaced for the sampled participants. Sponsored links and the ability to take notes on modifications to recipes also surfaced as points of interest for these participants. The Alexa audio instructions were as follows, the rate of narration where the ability to slow down or speed up how fast Alexa is speaking or the rate of the video they're watching was high among three of the five sample participants. One participant suggested language dialect be an option even if they've already registered in one language. Taking or adding a note surface does a command request from one of the participants. For instance, “Alexa, please take a note regarding the modification I'm about to make to the recipe for Southeastern butter chicken.”

Mental Model Topic: Sharing your experiences

 

When it came to sharing experiences, my first inclination is to not include the ability to share the minimum viable product. This seems like a complication that the MVP should not be reliant on initially.  Expected Alexa audio instructions looked like this. Next and previous steps, cooking techniques and terminology, the ability to email this recipe to friends and family members, And the ability to share this recipe and my Creations I've made on social media sites like Facebook for instance.

 

Iconography such as the share button or the envelope icon might be used to signify the ability to share or email the recipe, photos, or photos you've uploaded for other members to see within the user interface.  Merging photos of what you have cooked so that other members can see them much like photos on Yelp are used to further describe restaurant experiences as to how I'm looking and choosing to define merging photos. Sharing photos, on the other hand, is the ability to share photos of food you cooked with friends and family members. Imagine standing in front of your refrigerator as you're walking away from your oven with plated foods and telling Alexa to take a screen capture as you hold the plate in front of the refrigerator. Alexa can then let you know that she's added these pictures as photos to be added to her database for Southeastern butter chicken for all members of Amazon Prime to then see. Maybe Alexa can even strip out your face for privacy purposes and only focus on the foods. Other Alexa audio instructions might include Alexa following up with asking if you would like to share these with preferred friends on Facebook?

Appliance cost

 

All five participants were asked to estimate the expected price of the smart refrigerator. The average expectation Hubbard somewhere around $3,500.

Appliance brand

 

All five participants were asked which brands they expected would potentially partner with Amazon for an Alexa infused smart refrigerator. Brands like LG, Sub-Zero, and Samsung surfaced.

Mental Model Deliverable

 

Between three and five people were interviewed a crossed the different quadrants of the model. They were obviously many overlaps in terms of general expectations. I tried to keep the interview focused on general expectations in terms of the user interface design the user might expect to see and the kinds of affording says and services they might expect to experience.
 

The model is displayed below.

Mental Model Topics of focus

Participants for the mental model questions

Interview 01 - Janaca  July 02, 2018 - Second interview

Interview 02 - Rob  July 02, 2018 - Second interview 

Interview 03 - Evelyn July 04, 2018 - Second interview

Interview 04 - Howard July 04, 2018 - First interview

Interview 05 - Marla July 06, 2018 - Second interview

Mental model questions and topics of focus

The following areas of focus have been defined as a hypothesis of what I believe to be the most important in the journey of discovering new foods and new food recipes in the SMART kitchen experience.
 

  1. Searching for foods
     

  2. Finding recipes
     

  3. Acquiring the ingredients
     

  4. Learning how to cook the recipes
     

  5. Sharing your experiences - Ideas, comments, notes, issues, photos, food creations, stories, etc.


 

 

Mental Model Findings
 

Mental Model Topic: Searching for foods and Ideas (Recipes)

 

 

One interesting finding relating to one's search for food ideas and recipes is that 3 out of 5 of the participants stated the belief that one had to compare two recipes against each other, as the dish's nutritional value and ease of preparation were two main factors of importance. Additionally, 3 out of 5 participants suggested the recipes should be sponsored by outside entities that focus on recipes and cooking, an example being Epicurious. Many suggested the inclusion of sponsored links, logos, and other descriptive information. When it came to the Alexa audio instructions participants reported that they thought Alexa should be able to filter out food allergies, consider their past preferences, and consider starred or favorite recipes they've prepared in the past. 

 

Additionally, artificial intelligence comes up in the discussion. Participants commented that within the Alexa audio instructions should suggest or expect Alexa to learn from their previous food style choices. This artificial intelligence expectation expands into their past nutritional preferences as well.

 

Joyful experience note: If Alexa was able to suggest keeping meals under 500 cal because your past eight out of 10 meals fell under 800 cal this might be a cause for Joy as a and experience for a user.

 

When it comes to nutrition, some basic information was also suggested. Basic nutritional values such as fats and carbohydrates could be displayed in a small but concise area in the search result listing. Additionally, the ability to change this listing by serving or by meal quantities. Possible sponsored sources could also be listed in this area and were suggested by the participants. Specialized search filters we're suggested as well. And autocomplete, ethnic categories, the ability to filter by food and drinks, as well as celebrity chef recipes.

 

Photography quality came up and the ability to favorite by the hero image of the recipe was a consistent 5 out of 5 requests from the participants. The ability to use Pinterest as a way to socially remember their favorite foods and food recipes was also a top suggestion. When it came to the description within the construct of the search result listing, Wiki links, user review ratings, and user review comments that were short and sweet also arose as desirable expectations.

 

Because the refrigerator is smart and some of the assumptions require the refrigerator to take into consideration what you already have in the fridge that was purchased through Amazon. An indication in the search result listing for recipes that required ingredients you had in your fridge already was a powerful idea that surfaced from participants. This could easily show up as some degree of indication in the search result for a way for instance for users to easily move through foods that are already opened or currently in use within the refrigerator already or a SMART FRIDGE FILTER. Lastly, preparation time and the approximate cost per meal with the ability to change the number of people expected at your table completed the searching for food ideas segment of this mental model.

Mental Model Topic: Comparing recipes


The ability to compare recipes was part of my original hypothesis in terms of looking at the five major areas of focus for this project. Often, images, short descriptions, user ratings, and photography can help users quickly and easily decide when comparing two different types of foods for a meal. The results from the participant's discussion where is following. The participants felt as though the Alexa audio instructions should include the ability to ask Alexa to compare to selected recipes by nutrition, popularity, as well as ask Alexa for options to substitute out ingredients for alternate options. Additionally,  some participants felt as though they should be able to allow ask Alexa to compare her recommended ingredients with ingredients that they could potentially purchase outside of Amazon.

 

The majority of the participants sampled agreed that the content-length be short.  In this case potentially one paragraph or a short one paragraph. Participants suggested sponsored links such as curious as well as food sensitivity awareness is and a possible rating system. Long-term suggestions included rating reviews by other members on Amazon. When it came to cost,  participants were curious about what the total cost of the 2 compared meals would be broken down by serving and or the entire recipe.

As with Searching for Foods, photography and photography quality, we're high on the list.  all participants agreed that the quality of the photo would probably assist them and make their mind up 50% of the time or more.

 

Comparison by nutrition was also questioned in the participant sample. Diet types such as vegan vegetarian were suggested as a possibility that when clicked could lead to further suggestions for the user. Other obvious nutritional information such as fats, Sugar's, and carbohydrates as well as a possible link to the FDA surfaced.

 

Prep time that was easy and simple to understand by hours and minutes, as well as total prep time or total cook time, completed the comparing recipes findings.

Mental Model Topic:  Acquiring the ingredients



* When it comes to acquiring the ingredients, my original hypothesis was that the ingredients list ultimately transformed into the cart. After further consideration, I'm starting to rethink the ease of understanding and ingredients list also doubling as a cart for our Amazon smart refrigerator. With that being said, I had some sensitivities to asking questions that were not originally planned for the mental model. The Alexa audio instructions that participants suggested included the ability to show all required ingredients, show me what I have in my refrigerator, show me substitutes, by all of the ingredients I need even if I already have ingredients left over in my fridge, and lastly, compare with prices outside of Amazon.

 

Users also recommended Amazon recommends Graphics that they are already used to seeing on the Amazon platform. This led to further discussion regarding the list of ingredients all being branded Amazon recommends. The participants suggested the ability to swap out the recommended option with other options of their choice. Recommendations could change across the entire cart or ingredient list by filters such as cost, user popularity, and nutritional content such as low-fat. Additionally, purchases via the expected delivery time surfaced as a point of discussion among the participants. A further concern regarding the ability to purchase items that were low in stock also was concerned that users wanted to be aware of when planning recipes beyond the next 48 hours.

 

Participants were also interested in the ability to access information about the products they were choosing or considering placing in their carts. Again, the expected delivery date surface as a primary concern when thinking about acquiring ingredients.

Mental Model Topic:  Learning to cook recipes

 

 

** The ability to learn to cook these recipes goes beyond the concept of a minimum viable product in my opinion. However, the ability to teach a user how to cook the recipes and Foods you're bringing to their homes, in my opinion, is where the joy comes into play with this entire concept. Additionally, the ability to educate users to use foods and food recipes in unique manners may further drive brand adoption for Amazon.

 

Videos, images, customized Alexa audio instructions, and step-by-step guidance are some of the areas of focus within the dimension of learning to cook recipes. * All of the participants agreed that easy to watch and short but concise videos complete with progress bars and other expected buttons such as the pause and play button would a system in learning to work with foods are unfamiliar with quickly. * Once again, high-quality imagery that is clearly broken down w/ step by step procedural increments in a low cognitive impact page may also score high with participants and future users.

 

Language dialect, next and previous buttons for the next step or previous step as well as cooking technique terminology links or definitions and possible tools required surfaced for the sampled participants. Sponsored links and the ability to take notes on modifications to recipes also surfaced as points of interest for these participants. The Alexa audio instructions were as follows, the rate of narration where the ability to slow down or speed up how fast Alexa is speaking or the rate of the video they're watching was high among three of the five sample participants. One participant suggested language dialect be an option even if they've already registered in one language. Taking or adding a note surface does a command request from one of the participants. For instance, “Alexa, please take a note regarding the modification I'm about to make to the recipe for Southeastern butter chicken.”

*/** Important & notable to Prime Brand Adoption

Mental Model Topic: Sharing your experiences (Social)

 

When it came to sharing experiences, my first inclination is to not include the ability to share in the MVP. This seems like a complication that the MVP should not be reliant on initially as a measure of success. This may require further investigation and a success matrix. * Expected Alexa audio instructions looked like this. Next and previous steps, cooking techniques and terminology, the ability to email this recipe to friends and family members, And the ability to share this recipe and my Creations I've made on social media sites like Facebook for instance.

 

Iconography such as the share button or the envelope icon might be used to signify the ability to share or email the recipe, photos, or photos you've uploaded for other members to see within the user interface. Merging photos of what you have cooked so that other members can see them much like photos on Yelp are used to further describe restaurant experiences as to how I'm looking and choosing to define merging photos. Sharing photos, on the other hand, is the ability to share photos of food you cooked with friends and family members.

 

* Use Case: Imagine standing in front of your refrigerator as you're walking away from your oven with plated foods and telling Alexa to take a screen capture as you hold the plate in front of the refrigerator. Alexa can then let you know that she's added these pictures as photos to be added to her database for Southeastern butter chicken for all members of Amazon Prime to then see. Maybe Alexa can even strip out your face for privacy purposes and only focus on the foods. Other Alexa audio instructions might include Alexa following up with asking if you would like to share these with preferred friends on Facebook?

*This use case is a powerful one and one that is successful, may drive the value proposition of the entire project and delight our users.

Appliance cost

 

All five participants were asked to estimate the expected price of the smart refrigerator. The average expectation Hubbard somewhere around $3,500.

Appliance brand

 

All five participants were asked which brands they expected would potentially partner with Amazon for an Alexa infused smart refrigerator. Brands like LG, Sub-Zero, and Samsung surfaced.

Mental Model Deliverable

Customer expectations are shown in blue highlight.

 

Between three and five people were interviewed a crossed the different quadrants of the model. There were obviously many overlaps in terms of general expectations. I tried to keep the interview focused on general expectations in terms of the user interface design the user might expect to see and the kinds of affording says and services they might expect to experience.
 

The model is displayed below in blue highlight.

Platform recommendations by feature and facet in blue highlight specific to the customer expectations.

 

Recommendations specific to the five different dimensions of focus for the mental model are correlated column by column specific to the customer recommendations. The platform recommendations reflect an interpretation of how specific features might react given users expectations of how the SMART Alexa infused refrigerator show operate day to day.

 

 

Platform recommendations feature by feature displayed below in blue highlight.

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