How might emerging technologies encourage people to be more eco-friendly?
Good Earth is an AR app that empowers people to make eco-friendly consumer decisions at the grocery store.
Surprisingly, concern about environmental issues doesn't automatically translate into eco-friendly behavior.
Here are some factors that reliably predict consumer behavior in grocery stores.
We drew inspiration from a number of precedents that are successful at persuading consumers to change their behavior in favor of environmental and social causes.
Imperfect Produce is a startup that sells ugly, misshapen vegetables by creating an aura of desirability around them.
Buy Black is a Chrome extension that promotes black-owned businesses by offering alternative suggestions to online shoppers.
Good Earth is a just-in-time intervention that surfaces carefully selected triggers in context.
Good Earth guides users to the items on their grocery list. For each item, the app presents eco-friendly alternatives.
Users are able to interact with the data in order to find out more about Good Earth's recommendations.
Our designs were driven by the insight that people like information, soft nudges, and the freedom to make their own choices.
Our concept is designed for a future in which mixed reality head-mounted displays are much more prevalent. With such a future in mind, we designed our concept to be handsfree so that it could accompany shoppers as they moved about the store.
Good Earth's capabilities may be just as easily deployed on mobile.
People who care about the environment can sign up for Good Earth on their phones.
New users create a profile in which they indicate which environmental issues they care most about.
Good Earth stores information about the items on the user's shopping list.
At the store, Good Earth guides users to the items on their shopping list.
At the appropriate time, Good Earth displays eco-friendly contextual information to help users choose what to buy.
Early on, we explored how shoppers might be influenced by factors such as information, convenience, friends' behavior, explicit nudges, and appeals to morality.
Here are three examples of our early prototypes. Each shows a progression of information that a user might see in augmented reality:
Here's an example of how the above prototypes might appear in context.
My teammate Aaron and I got thrown out of Whole Foods for user-testing our ideas in the frozen foods aisle.
We reduced possible confounds by testing our ideas on chicken, pork, beef, and three types of fish.
We narrowed the scope of our prototypes by employing data about friends' preferences, data about envionmental impact, and a menu of options (best/ok/avoid). We tested combinations of these elements under different situations, such as price sensitivity and preference:
If we had more time...
We would test our high-fidelity prototypes in context, i.e., with real customers in an actual grocery store. Given the scope of our project, we were able to conduct initial research at the grocery store, but we were not able to take our designs back to our users. If we were to take this project further, that would be a crucial next step.
As research lead, I led generative research, contributed to ideation, and helped narrow and refine our final concept. The Goodearth team also included A. Faucher.