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Palomar

Link, write, earn

MA 2020/2022
Keywords
web3, blockchain, ownership economy
Overview

Palomar is a decentralized writing platform, to connect and reconstruct knowledge. Powered by links, Palomar is committed to exploring more sustainable business models for creators.

Collaboration

Special thanks to Matters team ( Emilie Hsu, Yingshin Li, Zack Li, Jiepin Zhang ), and Zerui Cai.

Context

What is web3?

To answer this question, we have to look back, at the history of the web. 

In web 1 and web 2, all data is stored on a central server, and the use of data also triggered many problems, such as information cocoon and limited creative freedom.

To put it simply, web 3 is imagining new possibilities by changing the way data is stored and used. Over the past few years, a number of web 3 platforms were created, to make a difference with the existing web 2 advertising-based business model.

Research

What are the design opportunities in web3? 

To answer this question, I did research on 3 aspects:

1. Meetings with web3 developers

2. Desk research

3. In-depth interviews with users


I reached out to Matters, to understand the need and the pain of the current web3 platform. It is one of the biggest web3 publishing platforms which has more than 80,000 creators. The platform provides an interface as familiar as web2 applications and a distributed file system for storing and sharing data.

Matters tries to promote the concept - “creativity has a price”. After a meeting with them, I summarized three challenges they are facing. 

Their biggest confusion is the pricing plan. They have developed a subscription service as an MVP, but they still wonder whether the monthly payment model is suitable for every creator. Also, a limited user base is still their pain point. In addition to that, they hope they can nurture a self-driven community.


I carried out user interviews with 5 readers and 6 creators who are in different stages of life. The goal of the interview is to understand readers’ day-to-day reading journey and consumption habits, also the creator’s journey and their opinions on revenue. Here are key takeaways from the reader's persona, and further defined design goals.

How might we design an economic model for 'paid content' in a web3 scenario, enabling creators and consumers to exchange value efficiently, and provide them with a community?

Concept

To respond to this question, I proposed the concept:

Links as tokens

- In this platform, creators can publish their articles on topics

- Each topic has an initial pool of funds, creators who post on the topic will receive a share of tokens as the basic income

- When an article is linked to other articles, creators will be rewarded with additional tokens

- Readers can support topics by donating tokens

Validation

To validate my concept, I brought my idea to Matters and asked for their opinion. They loved the idea and pointed out that encouraging smaller creators to produce is very important. They also agree that the Subscription feature itself is more suitable for top creators. They mentioned two features they had in the platform which is similar to my feature: the hashtag and reference.

I also held an online workshop to test the basic functionality of the product and discussed the current ‘hashtag’ and ’reference’ user experience on Matters.

- Before the workshop started, users were asked to write around topics and link each other’s content - In the ice breaker stage, I asked creators about their experience using the hashtag/topics

- Based on the preparation condition, we then lead participants to read, write and link

- We also allow readers to donate tokens at the same time

- After the activity, tokens are assigned based on the final data

- Finally, we have the roundtable discussion about the experiences


By observing users’ behaviour in the workshop, I also noticed that because all participants received a similar number of links, in the end, it does not show a very large difference in income. So I assume similar activities could be carried out in the future and the earnings distribution formula should be improved based on the data collected.

SPECIAL
THANKS

Special thanks to Zerui Cai, my tutor Sun Qian, and Matters Team

Team