An application to assist in the sometimes chaotic nature of planning group dinners. We want to remove the barriers to togetherness.
The age old questions of “what do you want to eat” can be a haunting scream into the void sometimes. This may sound dramatic, but reflect back on times you’ve tried to arrange a dinner out between more than 2 people. Geographic distance, what’s fair, and who likes to eat what, are all questions that can drive indecision or cause friction.
We forge some of our fondest memories meeting with friends over food. Historically the sharing of meals has brought humans together. In our recent human collective memory we’ve experienced times where meeting with friends, or dining out were not possible.
During our research all (100%) of our respondents indicated that indecision is a real problem when they are planning on where to eat. This impacts negatively on their decision making process when planning outings with friends. The difficulty of this process can cause hesitancy in respondents for planning and meeting with friends. 100% of respondents indicated that within their core friend group there are members who are geographically dispersed. This adds increased complexity and points of friction within the surveyed group as trying to find a restaurant that meets dietary as well as travel needs can present an obstacle. Finding a restaurant that meets the group's dietary preferences can also be tough as only 40% of those surveyed indicated they had similar taste to their friends.
Our research demonstrates a fairly common problem. How does one decide on a group dinner that can satisfy disparate tastes, different schedules and that is a fair travel distance for those involved, and limits the need for one person to make a decisive choice. There is no current solution for this situation.
We want to create an intuitive process to plan group dinners. One that takes into account the blockers presented above, Distance, Dietary Preferences and Decision making (Three D’s).
By collecting the users location data and their dietary preferences we want to present a curated list of restaurants that meet the following criteria, 1) exist in a fair travel distance for all participating and 2) restaurants are weighed on most common dietary preference, using a utilitarian approach (the needs of the many).
As a user, I want to make planning dinners with groups of friends easier, so i am more motivated to plan these get togethers
As a user, I want to find a restaurant that most closely meets the dietary preferences of the group.
As a user, I want to find a restaurant that is a fair travel distance for the group.
How can we make the experience of planning group dinners intuitive and conflict free so that this process is less stressful and encourages more frequent human connection over food?
We want to start with a small and narrow focus to ensure we address the 3 main blockers that we’ve discovered exist in the group dinner planning process.
Dietary Preference: Users will be prompted to select from a list of restaurant / food types, ie Pizza, middle eastern, sushi, Italian. Each user's list will be used to create the final list of suggested restaurants with weighting favouring common choices.
Distance: Users location data, either taken from their device, or entered in their profile, will be used to establish a radius. This will influence the location of the restaurants in the final list presented to the group weighted to provide a fair travel distance for users in the group.
Decision: The above 2 parameters will result in a list of restaurants that the user group can use to make their decision. A decision made by an application and not one person which should reduce the friction, personal feelings, and indecision.
Scenarios
User Story #1: As a user, I want to make planning dinners with groups of friends easier, so i am more motivated to plan these get togethers
Acceptance Criteria:
User Story #2: As a user, I want to remove conflict from the dinner planning process, as my friend group has disparate tastes in food.
Acceptance Criteria:
User Stay #3: As a user, I want to remove resentment some of my friends feel due to distance they travel, this will ensure these friends are more likely to attend
Acceptance Criteria
Measuring Success
By Demo date, we would like to be able to generate a restaurant list that meets our criteria of
1) Food preferences
2) geographical Distance
Product Success Metrics
These metrics will allow us to identify if our application is providing its intended value. They will also help us identify gaps and other use cases that are currently not supported but could be a future feature.