How might we leverage the grocery shopping experience to help people make more conscious nutritious choices?

...and how might we help people follow through with these choices?

All of the food we eat needs to come from somewhere… whether that’s a restaurant, your grandma’s house, or a grocery store. Americans purchase over 80% of their food from a traditional supermarket or grocery store, so we decided to focus on designing interventions for consumers while shopping since that is where a vast majority of decisions about nutrition are made.

 

We had the hypothesis that if unhealthy or non-nutritious food never gets into your house, then you won’t eat as much of it. Well, with the exception of the occasional McDonald’s run, that is…

This leads us to the primary question that we wanted to tackle.

Phase 1: Secondary research 

Full-service stores

Communities with full-service grocery stores tend to eat more fruits and vegetables and tend to have a lower risk of obesity. However, low-income and rural neighborhoods often face limited access to full-service grocery stores.

Personalized nutrition

This is “about the consumer of the future, that has more data available and wants to use this to their advantage. We think this consumer will desire more bespoke products and services.”

Negative focus

Mandatory labels may include negative aspects of foods, but voluntary labels will not. Apps are usually short of verification. The consumers are actively looking for brands that tell a sustainable story.

The future interaction

Five primary strategic underpinnings are central to change and are no longer considered trends: tech, convenience, experience, fresh food and local. Future grocery design will be significantly affected by technical advances like artificial intelligence, machine learning, and robotics.

Phase 2: Primary research

During our process, we focused on speaking with urban millennials, ages 23–35, who purchase their food regularly at various types of grocery stores. These stores included traditional supermarkets, ethnic specialty stores (like Indian shop, City Spice Market, and Korean supermarket, H-Mart), farmers’ markets, and even online services like Instacart.

 

We conducted one-on-one interviews with them, observed them while they shopped, and had them send us updates and photographs as they shopped in stores nationwide. On top of this, we did an incredibly thorough scan of secondary literature in an attempt to understand the nature of the problem as well as the current “competitive landscape.”

Out of all of that research, we came to the following 6 key insights:

 

Key insights

 

People automatically “know” what is categorically healthy vs. unhealthy, but there is a significant grey area in the middle of that spectrum and many of our assumptions about what falls into these categories are based on long-held orthodoxies.

People only look at labels for new products or brands, not the ones they buy regularly. As a result, they will never know if nutrition facts change due to alterations in product recipe or new labeling policies.

When people look at nutrition labels, they only look at the 1-2 key elements they understand as being “bad,” like saturated fat, sugar, or calories.

They rarely look for “good” or pro-nutritious ingredients, and also do not understand the “good” ingredients and their effects on the body as much, either.

There is a disconnect between moment(s) of purchase, moment(s) of consumption, and eventual feedback.

The “modes” we are in during shopping—our mental states, needs, sensory experiences, and emotions—do not equal those we are experiencing as we eat or prepare the food we previously purchased (sometimes days prior).

In our very connected world, “time shrinkage” is a perceptual reality for most people. This leads them to make tradeoffs in the form of convenient choices, which are typically seen as incompatible with nutritious choices.

Most people’s motivation for making nutritious choices comes from external, superficial, or temporary factors, such as losing weight for that perfect “bikini body” or getting an energy boost to get through a late night of studying.  

Phase 3: Developing and introducing inBalance

inBalance makes it simple to plan and shop for well-balanced, nutritious foods. By combining our robust Amazon-enabled database with real-time, tech-driven updates about your in-store shopping habits, we are able to give you up-to-the-second nutrition information about the purchasing decisions you are making and nudge you toward options that balance your basket.

This very same database allows us to help you plan your meals ahead of time, scan hundreds of Amazon crowdsourced recipes recommended for your needs, and consider the needs of others in your household or social circles for whom you need to shop.

Scene 1

“It’s Sunday—I need to plan this week’s meals and go grocery shopping.”

On Sunday morning, Yuan receives a message from inBalance reminding her that it’s her usual grocery shopping day and asks her to update her list for the week. Along with this message, she receives a $2 off coupon for salmon because inBalance knows that she has been low on her Omega-3 intake lately. 

Yuan has been learning quite a bit about the importance of eating a balanced diet in her Multidisciplinary Prototyping class this semester, so she decides she wants to set a goal for herself to be more well-rounded with the foods she eats and gain weight. Immediately after setting this goal in the app, inBalance recommends Yuan a slew of recipes that she might want to consider for her meal prep this week. In order to take advantage of her coupon and balance out her Omega-3s as suggested, Yuan selects one with salmon and adds all of the items in the recipe to her list. After adding a few other items, she’s ready to head to the store!

 

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Scene 2

“I just arrived at my local Whole Foods. I hope to get in and out quickly.”

Before leaving home to head to Whole Foods, Yuan receives a notification that her usual location—the store on Roosevelt—is extremely crowded at this time. Instead, the app encourages her to go to the West Loop location on Halsted to beat the rush.

 

Since inBalance knows that Yuan is now going to a different Whole Foods location than usual, the app automatically organizes her list in order according to how she can most easily navigate the store and gives her the option to view a map with all of her items marked on it. Using data from the Amazon and Whole Foods systems, it also knows what is out of stock at this new location and—if necessary—can adjust her list with new recommendations accordingly.

Upon arrival, Yuan taps her phone—which is already open to the inBalance app—on the sensors at the entrance, then walks into the store. The sensors above her will track her journey and unlock many of the inBalance features.

 

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Scene 3

“It is so tough to determine what a ‘balanced diet’ looks like for me.”

Following the list in her inBalance app, Yuan comes across the salmon in the seafood section. She grabs a package and adds it to her cart. Almost instantly, the salmon moves from the “list” portion of her app to the “in cart” portion, and her inBalance score updates to account for the nutritional qualities of the salmon: her score for Omega-3s increases, her calorie score balances out, and her score for fiber decreases. She also can click to see more about salmon’s nutritional qualities, which is a bonus because fresh food usually does not come with a label.

The inBalance score shows how the nutritional value of the items in her cart compares to what she needs in order to achieve her pre-set goals. It isn’t intended to be a judgmental feature, but rather, one that guides Yuan to be more balanced with her choices. Her goal is to earn the same score for each category—Calories, Vitamin C, Saturated Fats, Iron, etc.—to prove that these categories are all appropriately balanced for her.

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Scene 4

Yuan ate the last of her favorite cereal this morning for breakfast, so she made sure to tell her Alexa to add cereal to her inBalance list before leaving her home. When she gets to the cereal aisle, she picks up her usual, Honey Nut Cheerios, and adds it to her cart. Immediately, inBalance buzzes to let her know that it has an alternative recommendation for her—a recommendation that will help her keep her diet better balanced for the week.

Yuan is then able to scroll through a set of alternatives that better meet her needs. Each option shows her how it recalibrates her inBalance store so she can make an informed and educated choice about which one to purchase instead. Because Whole Foods and Amazon do not want these features to be perceived as a “rip-off” trying to scam customers by getting them to purchase more expensive foods through their nudges, they have promised a “price match,” so Yuan gets the newly chosen box of regular Cheerios at the same price, guaranteed. 

“I’m often tempted by other, less healthy, items that I find in the store.”

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Scene 5

“Now I just need to make sure I eat all of this before it goes bad.”

Since the sensors overhead have already tracked the items in her cart, Yuan is able to walk out of the store effortlessly! Once Yuan gets back home, she receives a “receipt” with a readout of her final inBalance scores, the recipes she has purchased ingredients for, additional recipes she can make using items that are now found in her home, and even some recommendations for what she should buy during her next grocery trip to keep her diet well-rounded. Once it’s time to cook, Yuan can ask Alexa to pull up the recipes she has selected.

Using the connected devices in her home — such as her smart fridge plug-in or the new Alexa-connected microwave, inBalance knows when Yuan is not eating the items she has previously purchased. As such, it can send her a nudge to prepare and eat them before they expire and reminds her of the goal she set a few days prior. This feature can help her connect her purchase mentality to her consumption experience in the present moment. 

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SPECIAL THANKS TO THE WHOLE TEAM

IIT Institute of Design Students: Laurel Komos, Yuan Feng, Luciano Annes Nunes

IIT Institute of Design Associate Professor: Anijo Punnen Mathew 

Process photos