Good Food Team Presentation - GS1 Hackathon

DevPost: https://devpost.com/software/gs1-challenge
GitHub: https://github.com/jui2010/GoodFood

Every person is different, and each one has different wishes, preferences and desires.

Research from Food Watch highlights that consumers are looking for different aspects of Honest Products, such as Nutritional Quality, Carbon Footprint, Organic, Vegan.

Manufacturers can't possibly print everything on the pack and some marketing claims may be misleading. Brand owners and retailers are not able to provide each consumer with relevant insights in an individual level, at the moment they are buying their groceries.

Producers and retailers need more insights about the consumer's decision making process and their preferences + Consumers need information at the right time to help them make a sustainable choice, given their food restrictions and health concerns

Sustainable Development Goal (SDG) #2, defined by the UN, is focused on ‘Zero hunger’ and includes ‘End hunger, achieve food security and improved nutrition and promote sustainable agriculture’.

What it does:
We have introduced a platform wherein each user can choose their own products which are align with their values and goals in life.

The points that they achieve in this process and sharing with friends will in turn motivate them to follow their daily routine.

It allows users to select aspects of products which are important to them, such as:

Nutriscore
Organic
CO2 footprint
Plastic-Free
Vegan
Gluten Free
etc
Then user can clearly see how the products they want to purchase compare across those attributes.

They are also able to see how they are doing against their chosen goals and share success with friends.

How we built it:
JavaScript, React, Python, Atrify API, Google Cloud, Flask

Challenges we ran into:
Tricky to get product-level CO2 footprint. Nutriscore information is not always perfect. Defining fresh products is only possible with access to "use by" dates.

Accomplishments that we're proud of:
In just a few hours we've extracted relevant data from a new data source (Atrify) and built an clear and intuitive tool.

What's next for GoodFood:
Include a location-wise grouping of retailers who sell sustainable products
Include more dimensions for customers to select
Improve CO2 calculations
Explore Epo system integration

Transcript

1. “GoodFood” Team GS1 Hackathon 2020 “Boosting radically honest products with AI and data” 19 September 2020
2. Overview Understanding the problem Target audience Timeline Demo Our solution Table of Contents
3. Team name: Good Food Team members: Elena, Jui, Sharayu, Dania Mentors: Regina, Christoph, Claudia Type of solution: Technical prototype Challenge: Products on Demand Technologies used: Javascript, Python, Atrify API Overview Good Food Jui Dania Meira Sharayu Elena Nemtseva
4. Understanding the Problem 01 Every person is different, and each one has different wishes, preferences and desires. 02 Brand owners and retailers are not able to provide each consumer with relevant insights in an individual level, at the moment they are buying their groceries. 03 Producers and retailers need more insights about the consumer's decision making process and their preferences + Consumers need information at the right time to help them make a sustainable choice, given their food restrictions and health concerns
5. Our solution We have introduced a platform wherein each user can choose their own products which align with their values and goals in life. The points that they achieve in this process and sharing with friends will in turn motivate them to follow their daily routine. Good Food: Enabling a choice that balances between both healthy and more sustainable food consumption The term ‘Sustainable diet’ encompasses health and environmental aspects of food patterns It connects to the second of the Sustainable Development Goals (SDGs), defined by the UN, which is focused on ‘Zero hunger’ and includes ‘End hunger, achieve food security and improved nutrition and promote sustainable agriculture’.
6. Project timeline Friday 12:00 Start Understanding each challenge and the data available + Choice of challenge and team Friday 16:00 Brainstorming Call with all team and mentors to talk about initial ideas Friday 20:00 Progress Building the frontend to understand the food preferences of the users. Saturday 10:00 Update Session Call with all team and mentors to share the prototype and collect feedback Saturday 15:00 Hack Solution Prototyping and documenting the solution Next Steps Improvements Add more food dimensions like Vegan, Protein Rich, Price,better co2 calculations, integration with EPos systems. Recommend food substitutes to help achieve their goal Develop redeem points strategies with partners
7. Target audience Our customers will include people from all age categories who need help deciding amongst a myriad of product attributes like Nutritional value, CO2 footprint, Organic, Vegetarian, Plastic-Free. The solution will cover all the above situations and enable choice.
8. Persona 01 Wendy Writer Female Age 20 Vegetarian Add screenshot of her profile
9. Persona 02 Berry Books Male Age 45 Cares about kids’ nutrition and plastic waste Add screenshot of his profile
10. Thank you! Organisers and Sponsors