EDIT: We've updated this proposal based on community feedback. Looking forward to your thoughts!
“Is Nouns activity growing?” “Who is helping increase engagement and spreading the meme?” “Which proposals are driving growth?” “What’s our spend rate?” “How many builders are contributing to the Nouns ecosystem?” “Are the amount of proposal candidates increasing?”
TL;DR
We aim to create a single-purpose website where Nouns activity metrics are published. It will integrate activity across social channels and highlight which Nouns, advocates, and proposals have best supported the Noun’s meme propagation. Our creative motto is: Track Memes, Not People.
As a starting point, this proposal focuses on [1] onchain activity (supported by the Nouns subgraph), [2] two sources of social media (Farcaster and Instagram), and [3] a limited set of metrics — such as proposal submissions, votes, comments, posts, and engagement. Opportunistically, we will incorporate additional sources and expand the set of metrics.
Background
As of the moment, the Nouns’ community and audience members produce a wide variety of data. Over time, more data is likely to migrate onchain (e.g. similar to vote comments today) and data will be produced across even more digital localities. The United World of Nouns will have a wide-ranging data footprint. Combining data across these localities can become a powerful tool for proposal development and decision-making.
However, as @Krel mentioned in their Request for Proposers:
“Nouns DAO does not have a reliable way to measure ‘growth’ or ‘success’. Its not clear what should be measured, or what growth in the context of Nouns even means.”
This project will create an initial repository of activity growth combining onchain and offchain data. We are long overdue to experiment on this front!
Scope
The metrics tracker will be in the form of a single-purpose web application.
To begin, we will include onchain data available in the Nouns Subgraph and two social media channels: Farcaster and Instagram. We will publish a selection of core metrics that provide clarity to Noun holders and the wider community.
Most importantly, the underlying data pool (Meme Activity Database) will serve a first step towards a data-driven Nouns culture, which community members and potential builders can use to find opportunities for proposal submissions.
Success of this project will be measured based on web application usage (unique visitors), proposal references (e.g. This project will increase X metric supporting Noun activity growth), and data pool connections (e.g. external usage of the Meme Activity Database).
As a stretch goal, we will look to expand the data sources, for example including key derivative NFT projects (Gnars, LilNouns, cc0-lib) and other dominant social spaces (Discord, Discourse, X, Lens, etc).
Note: X (formerly Twitter) has been deprioritized due to its cost ($5k per month) until initiative is proven useful. It would be included in future proposals.
Note: Discord has been deprioritized due to its fragmentation (there multiple Nouns servers) until initiative is proven useful. It would be included in future proposals.
Product Components
Whenever we want to test our internet speed, we can easily go to a speed test website. If we want to see how our activity on X (formerly Twitter), we can go to profile analytics.
Where do we go to check how the Nouns ecosystem is growing? We go to .
The Pulse is a single purpose website showcasing onchain and offchain activity metrics. This includes public conversations related to the United World of Nouns. The main graph, which we are currently calling “Activity Momentum” will showcase daily activity growth, a proxy for the Noun meme adoption and mind-share online.
Our data analytics approach will combine methodologies from (1) traditional media broadcasting (e.g. combining data like number of views, replies, likes, proposal submissions, unique voters, etc.), (2) crypto-native metrics common across DAOs, and (3) materials science and engineering (read more about how engineers develop material selection indexes here).
Data will be synchronized in real-time directly from the Nouns’ Subgraph, Farcaster, Instagram to an SQL database. The sync mechanism will be architected in a uniform adapter interface for easier future integration with other onchain data and offchain sources, such as Twitter, Discourse, Discord, Telegram, DeSo, and Lens.
Example Onchain Metrics:
- Treasury
- Treasury Usage Rate (Monthly Spend)
- Burn Value
- Candidate Props Growth
- Proposal Submissions Growth
- Active Proposals
- Percent of Proposals Funded
- Total Unique Builders
- Average Auction Price
Example Offchain Metrics:
- Number of Posts
- Total Engagement (Likes+Comments+Shares)
- Engagement Rate (Ratio of Engagement to Posts)
- Most Engaged Content
- Total Followers
- Follower Growth Rate (Updated based on API opportunity)
- Noggles Score: Count of posts using “⌐◨-◨” on Farcaster*
*In the first phase it won’t be possible to index Instagram posts by content, only be hashtags. As a result, the Noggles Score won’t be able to include Instagram posts.
Meme Activity Database (a.k.a. The MAD)
Curcially, the product’s underlying data model will be available for others to query and contribute to. That way, others can embed the index into their own Noun interfaces. Anyone should be able to get clean and reliable meme-data-as-a-service to support a diversity of Noun initiatives. Imagine a world where active proposals have conversation hype trackers, or ongoing projects can easily see total impressions across social media channels.
At the end of the day, we want to facilitate the use of data across the Nouns ecosystem. As the cc0 library enables media usage, the activity database enables tracking and impact analysis.
The Web API interface will be available publicly in the form of parametrizable JSON endpoints. The data will be distributed per specific sources (onchain Nouns, Farcaster, and others) as well as in aggregated form to enable the development of tools such as alerts, bots, and analytics dashboards.
Product Roadmap
The execution of this project will be done in an iterative fashion. By building in public and getting ongoing feedback, we can deliver what the community needs, and data that will support Nouns decisions.
Iterative Phases:
- Phase 1: Deliver basic UI w/ limited branding and processed Farcaster data displayed in form of metrics. Deliver mock-up UI for onchain metrics and Instagram metrics. Host open Q&A with Nouns (e.g. via Aburra) to gather community feedback.
- Phase 2: Deliver basic UI w/ Farcaster metric feedback, plus Noun Subgraph indexing and onchain metrics. Host open Q&A (e.g. via Aburra) to gather community feedback.
- Phase 3: Deliver basic UI w/ Farcaster, Onchain metric feedback, and Instagram metrics for specific accounts and hashtags. Host open Q&A (e.g. via Aburra) to gather community feedback.
- Phase 4: Complete UI polishing and metrics calibration. Host open Q&A (e.g. via Aburra) to celebrate launch and discuss future opportunities (where next).
An Ambitious Vision
This project aims to uncover what “Nouns-Native” analytics could look like, and what data infrastructure is necessary to feed this analytics into the broader Nouns governance and participation process.
We’ve already intuited that we want to Track Memes, Not People — and we’re certain there will be other innovations along the way. After all, we need to address challenges in crossing the web3-to-web2 data pipeline chasm. Is it possible? We think so.
Nouns is a place for ambitious ideas, and we are an ambitious team.
Team
This project will be led and executed by Rafa Fernandez (Farcaster: @rafa) and Rafi Gutkowski (Farcaster: @rafi).
- Rafa Fernandez is a community architect with a focus on building Digital Public Utilities. He has decade of experience in corporate analytics and studied materials-science and engineering. He is the founder of Folklore (Folklore.Institute), a community that curates and commissions research on digital cultures. Most recently, he was part of the Summer of Protocols research program looking at online swarms. Previous to the program he worked at Mirror where he worked in creator partnerships and community development.
- Rafi Gutkowski is a software engineer and data scientist (libred.org, LinkedIn). He started mining bitcoin in 2015 but only after exiting from his recent startup, did he double down on web3. Since then Rafi has been working on sementic analysis of decentralized social graphs, as well as creating web3-web2 bridges, such as Folklore’s web3-signature to feed broadcast applet.
Funding
We are a stream of 22.5 ETH to fund this project over approximately 10 weeks.
The funds will be allocated to a two-person team (Rafa and Rafi). They are split roughly 25-75 between planning and iterative engineering. There is about a 40-40-10 between data engineering, visuals and handoff. There is approximately 10% reserved for bugs and issue resolution.
We expect that once the initial traunch of data engineering and visuals is complete, then we can make a decision on what the community needs more of (if anything), such as expanded data, or expanded analysis
Our Commitments
- We commit to posting updates on updates.wtf with sprint plan and outcomes, in alignment with each of the community Q&A feedback sessions.
- We commit to cancelling the stream based on community feedback.
- We commit to executing this work as an open-source project, such that other onchain communities and organizations can benefit.
Other Notes
This proposal was built based on the Basic Nouns Proposal Template, built by Rafa and available here: https://hackmd.io/@rafathebuilder/BkPAmHZbp
If you’d like to learn more about this proposal, the first Q&A conversation on Aburra is available here: https://youtu.be/_dr2yZulMG