Social food recommendation service for friends taste-alike and earn credits towards the next meal.
- UX/Prototype - Kei Tseng (First iteration)
- User Research - Uijun Park (First iteration)
- UI - Min Lee (First iteration)
- Product Design - Kei Tseng (Second iteration)
First iteration is to propose the UX direction and insights through research and prototyping for Seamless, the food ordering service. The focus is on how might we engage and retain the users. Second iteration is to further refined the product/service design.
We started out very ambiguous by breaking down the end to end user journey, user research and setting up with hypothesis to prototype and test the assumptions. Based on the insights, I dived into designing the product and developing the website to validate the product.
Product design prototype and website for validation.
Understanding the user insights
Experience journey reveals the pain points involving information architecture, transparency problem on delivery status, unreliable and passive review system. Insights from user research reveals the joy of sharing food socially with friends, wanting to save money and time, and tired of repeated food.
Find the value proposition
We analyzed the competitor landscape based on user insights and defined the hypothesis for the prototype to determine the market opportunity and value proposition. The first assumption is user want the service to be more efficient to schedule and make meal plans in order to save money and time. The second assumption is users wants to engage in the social experience. The prototype concept is a food ordering service that allows users to schedule and order meals in advance and recommend food to friends as feedback. Defined the go-to strategy, the insights shows that the core value proposition is to focus on social engagement with food recommendation. To humanize, connect and build trust.
Humanize, connect and build trust.
Users find the meal planning and scheduling is efficient but hardly a competitor advantage feature. Users can relate more and find friend recommendation more reliable. They shows interest to learning more about the recommendation from their friends however lacks that interaction feature. The feedback flow shows improvement in response.
User flow designed around business objective
Crafting the flow that acquires user to recommend with incentives, connect and build trust to try out recommendations among friends taste alike and engage the user to recommend and bring more friends on-board.
Building incentive and revenue model
In order to engage the users, the service focus on affiliate and referral model for the food recommendations to generate incentives for the user.