Food Based Dating

Planning what to eat on a first date has never gotten any easier!

Combining forces with local venues to make a better online dating experience.
Prioritizing ethical gamification over manipulative design patterns.

Time to Design Concept

2 weeks

My role

Product Design

The Problem

  • Unequal playing field online
  • Some only seek validation leads to zero interaction
  • Risk-free Reward leads to negative behavior
  • Pen pals forever
  • Need to establish commonality
  • Online Dating is an addiction, same effect as “Doom Scroll”

The Solution

  • Adding more navigation per profile changes user focus
  • Partnership with local venues gives 1st Date ideas
  • Limit max number of matches
  • Schedule assistant pushes to make first move
  • Rate date and give feedback

Design Thinking Process

Affinity Map

Surveys

Personas

Process Pain Points

We can’t change the psychology of the pain points, but we can reduce them by limiting certain features.

By limiting other common functions, we can prioritize the goal of the app.

Optimized Interaction

Competitive Analysis

Constant app usage increases chances. Apps generally bury users unless they’re on premium. Dating apps are generally biased in favor of certain users.

Competitive Experience Analysis

Brainstorming

Considerations & Consequences

  • Rating systems can affect someone’s perceived self worth.
  • Rating system introduces manipulative patterns.
  • Will people rate the experience or the persons aesthetic?
  • How do we present qualitative data in an easy to read format reducing the focus on numbers?
  • Users with many high scores will get more experiences than someone just starting out.
  • Does this NPS system reduce people to just numbers?
Black Mirror Season 3: Nosedive

Wireframes

Onboard

Scheduling

Business Partnership

Experience Screens

Results

  • Ethical gamification
  • Swiping based on aesthetics is greatly reduced.
  • Limited chat capabilities removes “pen-pal outcomes”.
  • Scheduling assistant pushes for more out-of-app experiences.
  • An algorithm that focuses on peer-to-peer interaction over aesthetics and swipe rates.
  • Stats revolve around out-of-app experiences.