Summer Sprint 1: Prototyping
Welcome to summer!
In the spring semester, our team conducted research of consumers and merchants in the CLO space. Through this research, we derived insights about some unmet needs and problems of the stakeholders in this space and created two concept prototypes- Local Business Investment and Restaurant Finder.
Using the Double Diamond model, we were able to enter the develop phase through our initial prototype ideas.
Stepping back: Define the problem
During the summer planning session with our clients that was conducted after our presentation, we received feedback that there are some interesting features in our concept prototypes but the ideas as a whole could use more work. Based on this feedback, the team decided to take a step back and reevaluate the problem we wished to solve.
The team referred to the insights generated from affinity diagramming sessions in spring to write down problem statements for merchants and consumers in the CLO space. We voted on the problems based on how necessary it is to build a solution for that problem, how interesting and feasible they are and, how passionate we are about them. From this, we chose the following 2 problem statements-
- How can we create experiences for users that do not financially hurt merchants (e.g. CLOs) to get consumers to return to their businesses?
- How can we get people to engage with CLO’s on a deeper level and incorporate them into their daily life?
We presented these problem statements to our clients and decided to go ahead with the second problem based on their feedback.
Ideation
Now that we have a problem statement, our next step was to ideate on different solutions for the problem. We used a two pronged approach for this-
Individual ideation
Each team member came up with scenario-based ideas based on the insights we generated last semester. We used a scenario template of writing out the context, problem, solution and resolution. This kind of template forces us to keep in mind the problem we are solving and how the resolution brings about a preferred future state.
Group ideation activity: Mashup
Working remotely have changed a lot of things for the better or for worse. One such change is that we unintentionally started combining individual work rather than working to create something together. The team recognized that the former is causing us to become defensive of our individual ideas and also prevents us from reaching a common understanding for the solution. To combat this, we decided to dedicate time specifically to work together in a group ideation activity.
We chose the activity ‘Mashup’ to rapidly generate ideas. In this activity, we identified different parameters such as Technology, Industry, Persona, Features and Existing Services that can be combined in a solution. For each parameter, we first listed down the values we can use. For example, following are some sample values for our parameters-
Technology: POS, smart phone, desktop, smart watch
Industry: Entertainment, restaurant/bar, sports
Persona: Olivia, Sara, Ezra, Jasmine
Features: Community-based, impact score, sharing CLOs
Existing Services: Yelp, Honey, Mint, Google Map
After listing down values for all parameters, we selected random values from each parameter and combined them to rapidly ideate a solution within our problem space.
With this two pronged approach, the team came up with several storyboards for our ideas.
Storyboards
From our ideation sessions, the team created the 7 storyboards.
These storyboard ideas were aligned to our selected problem statement- How can we get people to engage with CLO’s on a deeper level and incorporate them into their daily life?
Testing storyboards
After we got all these storyboards ready, we started to test them with users through two routes: test on UserTesting.com and conduct in-person interviews. UserTesting is a very productive user testing tool. We received three responses in less than 10 hours. Meanwhile, we also conducted three in-person interviews. This mix of methods not only enabled us to get as much feedback as possible but also helped us get more in-depth feedback from face-to-face conversations with users.
We synthesized the results of the interview and selected the most popular ideas based on user feedback. Here are our findings:
- Every participant actively seeks out and acts on recommendations from their friends.
- A majority of participants wanted to support local businesses, especially in current times of COVID-19.
- All of the participants were comfortable talking with close friends about rewards and finances, but did not want to engage in any system where they share rewards.
- Most participants liked the idea of engaging with an interactive and gamified program. They also really liked doing something with the larger community.
- All participants were willing to share their spending history with an app as long as the app can generate something useful for them (like a weekend plan, or “smart” recommendations).
Here are the three most popular storyboards:
Data Flows
After deciding which storyboard ideas. to move forward with, we started to figure out how to achieve them. Therefore, we shifted our focus from users to data and try to answer questions like what kind of data do we need and how to process it to achieve the features in our storyboards. We decided to create the data flow and started with data categorization as follows:
Consumer data
Data from consumers, such as demographic info, spending data, social circles, etc.
Merchant data
Data from the merchant side, such as business info, POS data, marketing choices, etc.
Data processing
Methods of data processing that can generate values, e.g., data comparison across all users.
The combined use of data
Services/features we can generate through data collection and processing.
For each storyboard, we came up with the detailed data flow as follows-
Prototypes
After we completed the data flow for each idea, we started prototyping. To explore more ideas in a short time, each of us sketched out the designs individually. We then selected our favorite designs through discussion and built them in Figma. Afterward, we combined the screens having similar functions and further iterated on them.
Next step: Prototype testing
This coming week, we will test our prototypes in UserTesting.com, and then we will further adjust our prototype based on user feedback and start making a prototype for the merchant side.
