Persona

Problems and Challenges

Convenient online shopping has become a habit for many, but it also brings numerous issues: spending too much time browsing products, impulsive buying, and paying for unnecessary services. There are many complex reasons for this phenomenon, but a major factor is the widespread use of recommendation algorithms. By analyzing user data, recommendation algorithms can suggest relevant products to each customer. These suggestions significantly influence consumer choices. Recommendation systems might make us question our own tastes. Instead of asking ourselves, "Do I like this?" we might ask, "Should I like this?"

Solution

There are many tools available that help users develop good habits to combat poor spending habits, but they do not truly solve the problem. Raising awareness of this phenomenon may be the way to expose and address the issue. By creating a mirror of user data, we can reveal the extent to which algorithms understand personal information, thereby exposing the algorithms hidden behind the interface.

Visuals and Interaction

User personas are modular, auto-generated illustrations. Details of the personas (such as hairstyle, skin color, clothing, and whether they wear glasses) change based on algorithmic predictions. Users can link the app to their platform accounts or install a browser plugin to enable automated data collection. The color scheme and visual style reflect the texture of old reports, suggesting that user data is under scrutiny. The night mode design is inspired by the dark web. The mask used as the logo symbolizes the state of user information: people often think they are wearing a mask on the internet, but it is the internet companies that truly have an unobstructed view behind the mask.