Please describe your proposed solution.
Our proposed solution is an NFT recommendation API that can be integrated by any Cardano NFT platform. The API will use machine learning (ML) to analyze the transaction history of a user's wallet and generate a personalized selection of NFTs that are listed for sale (or rent) on the platform. The API will leverage NuNet's decentralized computing network to pre-process our data set and train the ML model.
We believe that this solution will address the problem of lackluster NFT search and discovery, which leads to missed sales opportunities and low user retention for NFT marketplaces. By providing users with relevant and appealing NFT suggestions, we aim to increase their engagement, satisfaction, and loyalty. We also hope to attract new users who are looking for a more personalized and curated NFT experience.
Our solution is unique because it combines the power of (public) wallet data, NuNet’s decentralized computing network, and our extensive experience implementing ML solutions in ecommerce – to bring an ML strategy to the Cardano NFT market that has already proven revolutionary for Web2 applications. We will also integrate our API with Plutus.Art, a leading Cardano NFT marketplace, as a proof of concept and a showcase for this solution’s potential. And we’ll work with a SaaS attorney to draft a licensing framework that will allow other platforms to easily implement the API at minimal cost.
How does your proposed solution address the challenge and what benefits will this bring to the Cardano ecosystem?
ML-based Recommender Systems are defining features of virtually every leading, Web2 commerce and content application. From the video recommendations users see on YouTube, to the product recommendations they’re presented with on Amazon, ML-based recommendations play and integral role in the UX of the world’s leading platforms. But to our team’s knowledge, recommender systems are virtually non-existent in the NFT space.
This is especially strange given that the personalized marketplace experience made possible recommender systems is such a great fit for NFT marketplaces: Public blockchain provide ample data for the development of effective recommender systems. And NFT marketplaces typically sell a diverse array of assets whose value/appeal is highly subjective, and thus perfectly suited to personalized UX based on individual user preferences.
That said, our Recommendation API will benefit the Cardano ecosystem in a number of ways:
1) Increasing NFT Marketplace Transactions:
A 2021 Barilliance study (<https://www.barilliance.com/personalized-product-recommendations-stats/>) found that ecommerce platforms which incorporated ML-based, product recommendation systems could attribute an average of 12% of their sales to recommendations, and that some platforms were getting as much as 31% of their sales from recommendations. Of course, product recommendations can come in some forms that are outside the scope of this current proposal (such as on-platform and email notifications). But even a more modest gain of increasing marketplace sales by 5% (which is our mid-term goal for the NFT recommendation API) is very significant if the solution is widely adopted.
2) Facilitating cooperative models and increased sustainability between NFT platforms:
For example, NFT analytics sites will be able to link their users directly to marketplaces where they can buy recommended NFTs, thus making both analytics sites and marketplaces more sustainable.
3) It will showcase the potential of NuNet as a decentralized computing network that can support ML-based applications on Cardano.
This is a new use case for the NuNet network, and this project will accelerate the growth of NuNet’s capacity to support additional AI/ML projects.
4) Moving towards more personalized UX/UI on NFT platforms will benefit a broader diversity of NFT projects and users.
Currently, UI on leading NFT platforms typically centers around trading volume “leaderboard stats” and thumbnails from the most popular NFT collections on a blockchain.
The absence of a personalized, NFT discovery experience on NFT platforms is the Web3 equivalent of being advertised Mr. Beast videos every time you sign onto YouTube, even though you only ever watch videos on how to paint watercolors. And this suboptimal UX not only affects customer retention and sales. It also undermines the success of a broader diversity of creators, by needlessly allotting all the UI “real estate” to projects with the most popular appeal in the current market.
How do you intend to measure the success of your project?
We intend to measure the success of our project using both quantitative and qualitative metrics. Some of the metrics we will use are:
- The number of platforms that integrate our API
- The number of users who connect their wallets to our API
- The number of NFT recommendations generated by our API
- The conversion rate of recommendations (how many users buy or rent the recommended NFTs)
- The retention rate of users who use our API (how often they come back to use it again)
- The satisfaction rate of users who use our API (how much they like or dislike the recommendations)
- The feedback from platforms and users on our API (what they like or dislike about it, what they suggest for improvement)
We will collect these metrics using various tools such as analytics software, surveys, interviews, and social media. We will also compare these metrics with baseline data from before we launch our API to measure the impact and improvement. We will report these metrics to the Catalyst community and the Cardano Foundation on a regular basis.
We estimate that our solution will impact at least 10% of the current Cardano NFT users within one year of launching our API, based on our market research and user feedback. We also expect to attract new users who are interested in personalized NFT recommendations. We aim to reach at least 5 Cardano NFT platforms that will integrate our API within one year of launching it.
Please describe your plans to share the outputs and results of your project?
ArgusNFT and Plutus.Art activity:
We plan to share the outputs and results of our project in various ways, such as:
- Publish recommendation-api integration guides
- Open source the model training pipeline on the NuNet network
- Create examples/guides/video
- Integrating our API with Plutus.Art, a leading Cardano NFT marketplace, and inviting users to try it out and provide feedback.
- Creating a website and a blog to showcase our project, its features, its benefits, and its impact.
- Promoting our project on social media platforms such as Twitter, Reddit, Telegram, and Discord, and engaging with the Cardano NFT community.
- Participating in relevant events, webinars, podcasts, and interviews to present our project and its results.
- Reaching out to other Cardano NFT platforms and offering them to license and integrate our API at minimal cost.
- Reporting our progress, achievements, challenges, and learnings to the Catalyst community and the Cardano Foundation on a regular basis.
Partner NuNet activity
1. Spreading Outputs Over a Timescale
Our project plan includes clear milestones and deliverables, which will be shared publicly as they are completed. This incremental release of outputs will ensure a continuous stream of updates for the community.
This approach lets us provide updates on a regular basis, and offers users the chance to provide feedback that we can use to guide subsequent development. We
2. Sharing Outputs, Impacts, and Opportunities
We intend to leverage NuNets and ArgusNFTs various communication channels to share our project's outputs, impacts, and opportunities:
- GitLab: The primary hub for our technical work, hosting our codebase, documentation, and issue tracking. This will be the main point of reference for the details of our project.
- Social Platforms: We plan to regularly post updates on our progress on platforms like Twitter, Discord, LinkedIn, and Reddit. This will include major milestones, bug fixes, and insights from our development work.
- Technical Discussions: We will continue to hold weekly technical discussion where we discuss the technical aspects of our work. This provides a forum for live Q&A and discussion with our community.
- Blogs: A regular blogs to summarize the progress we have made, highlighting key achievements and outlining the next steps in our project.
3. Testing and further research
As an open-source project, our outputs will be freely accessible for further research and development. We encourage the community's involvement in testing our solutions to enhance their real-world performance.
Community Testing: We'll invite our users to participate in alpha and beta testing phases, where they can help identify bugs and suggest improvements. We'll use GitLab's issue tracking for managing feedback and provide guidelines for issue reporting and feature suggestions.
Internally, we'll use project insights and community feedback to guide our future work, optimize performance, and prioritize new features. Our aim is to foster a collaborative development ecosystem that is robust, relevant, and of high quality.