Lidar x Treasure
Lidar is building a web3 intelligence platform for builders to better understand how their products and communities are performing, and make informed decisions on what to do next.
We are currently building out the Alpha version of the product, working with a small group of web3 projects to build custom dashboards / reports and answer key burning questions with data.
Based on our learnings from these early explorations, we are building a self-serve analytics tool. We’re interested in having Treasure on as an early partner in this “genesis cohort”.
Link to our overview presentation below.
Example use cases for Treasure
In the context of Treasure, we have a few ideas on how Lidar could be useful. As we understand it, there are several elements to the ecosystem:
- MAGIC as the underlying currency for the ecosystem
- Several core cartridges (Bridgeworld / Smolverse)
- Partner cartridges integrating $MAGIC into their gameplay
- A custom marketplace smart contract
- Several NFT collections (owned and third-party)
- A core Discord community with game / governance / economy communities
At the basic level, we can offer analytics on these individually:
- Total volume, unique wallets, etc. interacting with each (or combinations) of these contracts
- Activity on the custom marketplace vs. others like OpenSea
- Discord growth/engagement activity/sentiment across channels and time frames
- Retention, churn, and cohort analyses across games and in Discord
Beyond this however, we can start to think of the various “archetypes” of users in the ecosystem based on their on-chain and off-chain behaviour:
- Traders who have bought / sold the currency without interacting with the game
- NFT collectors who’ve bought / sold NFTs without interacting with the game
- Gamers who are actually playing the games
- Fans who are involved on Discord / the community in other ways but have limited/no contract interactions (content creators and other members)
- Each of these can be broken down against specific cartridges or considered in aggregate across the Treasure ecosystem more broadly
Once we map out these archetypes, we can start to deliver even more insightful views of how the ecosystem is performing:
- How different archetypes have grown in different macro environments and where growth is coming from between specific games / types of activity
- Which types of archetypes are driving revenue for the ecosystem on an absolute basis as well as on a per-capita basis
- How the ratios between these archetypes compares to other gaming ecosystems, highlighting ways that Treasure is different / better / worse than its peers
- And again, retention, churn, and cohort analysis broken down by archetype to identify where there is the greatest opportunity for improvements on the product
If any of this - the general deck - and the examples of insights highlighted above sound interesting, we would love to chat with the relevant teams on your side. That could be operations, product, and/or the community teams.
In that conversation, we’d love to better understand what types of burning questions you have that we could answer with data, and take it back to see how long it would take us to get access and what we would need from you in the meantime (eg. installing our Discord bot on your server).
Typically, we like to start with 2-3 simpler questions and then iterate on a weekly basis with a project leader on your side who gives us feedback regularly in a Discord group or a standing 20-30min meeting.