My Example Idea: Fate
A smart food bin and shopping app that learns what you waste to help save you money.
This was my project from 2015 on General Assembly's UXD course, shown here because it exemplifies my passion for context-driven, AI-first, design.
This page outlines my research in to the problem of food waste, page two shows how I developed the solution.
View my main UXD page here.
Research in to food waste.
There has been plenty of research in to food waste conducted by the government's WRAP institute, and a lot of data is presented in their Love Food Hate Waste scheme.
The central problem is people buying more food than they realistically need.
More than just wasted food and resources - people are wasting their own money.
To get a handle on the issue I conducted my own research, which allowed me to generate user personas:
User Personas.
And for both personas there's always supermarket's efforts to contend with.
An onslaught of noise through which there's no signal of what they actually need...
* Illustration by Sam Zuppardi
I distilled my user personas in to a model for illustrating why people waste food.
Each user type has their own hopes and plans, shopping weak points and pressures in life that make them waste food.
Summarising why various personas waste food.
People waste food because they shop with hopes and dreams (this offer looks good, I'm really going to make the most of it!) but time and again reality bites and shatters them. Plans change, our tastes are flimsy, our effort and convictions even flakier.
Reality is the great antagonist to the dreams we aspire to when we shop.
But does reality have to be this relentless force we fight with?
Why not try and learn from reality - use its lessons to inform how we shop in the future?
With this model in hand, I can see what user needs current apps are serving, and why that approach is failing to reduce food waste.
Sketching my USP.
Turning the current vicious circle in to a feedback loop would be a radical new approach.
What we throw away is no longer a black hole of lost data but instead:
- a vital source of context,
- cross referenced with shopping data,
- to provide timely feedback preventing the user from buying what they don't need.
This is how it fits in to the current model of user behaviour:
How the product fits in to user's lives.
The advantage of this approach is its hands-off nature - the user spends little time and energy using the app itself.
No time consuming manual data entry, controlling shopping lists and food inventories.
No great effort on changing your normal routines to adapt to the demands of some new app.
With the research covered, continue to see how I develop my solution...