We embarked on a research journey to understand how we could meaningfully define Web3 communities and assess their health. This article is a short summary of our findings. For those interested in the depths of this rabbit hole, here's the full paper.
Much like traditional companies, historically, the medical field focused on treating illnesses. Little action would be taken to care for people until something went wrong and immediate actions were needed. As time has passed, we've learnt the hard way that being proactive and preventing is cheaper, more effective and enjoyable than curing.
In web3, where many tokenomics designs depend on network effects, healthy communities can enter a positive feedback cycle of talent attraction, valuable contributions, value creation and advocacy. While unhealthy communities can quickly enter a death spiral.
Importantly, basic metrics like engagement or sentiment tell us little about the underlying dynamics. Some communities come together under pressure while others fall apart; some transform conflict into deeper relationships, while others divide or create permanent bad vibez. What sets them apart? And, can we measure it?
To understand why communities differ, we'll start with a definition of community and then discuss how to understand and assess Community Health at a deeper level.
A community includes:
A place or platform(s) where the community exists and community members interact with each other.
A social structure based on the relationships between community members.
A shared meaning or collective identity.
And time - a shared history.
When these elements come together, we get a sense of community as an emergent property in the hearts and minds of the individuals and in the collective behaviours.
We also define community as composed of multiple systems, nested within each other:
the relationships between the individuals,
subgroups (formally created) and cliques (informally emerging),
the overall community,
and the broader ecosystem in which the community is embedded.
All the nested systems of a community depend on each other.
Are DAO communities different from other communities?
Four common traits differentiate DAO Communities:
They exist in symbiosis with an organisational aspect (the DAO),
Include multiple stakeholder classes and tend to blend them into one,
Gather primarily online (although this might change in the future),
And subscribe to the Ethos of DAOs: decentralisation of power; autonomy; shared goals, vision or values; and a shared treasury managed by the community.
This means that DAO Communities are particularly positioned to leverage (and suffer) from network effects. Since your contributors, investors, and users share the same space (and can be the same people), what affects one of them will quickly affect the others.
A DAO's community is considered healthy in the moment when it contributes (or at least does not destabilise) its nested systems and itself, meaning it:
Satisfies the needs and aspirations of the members (including alignment with their values, e.g. the Ethos of DAOs);
Promotes healthy relationships, and functioning subgroups and cliques;
Advances its collective goals (the community's capacity to generate value for the DAO as a whole);
Exists in a healthy ecosystem;
Resist shocks, adapt and transform as needed
Importantly, communities don't exist in a vacuum but interact with other communities: Members contribute to several communities, joining and leaving DAOs following their needs and aspirations. Over time, it's almost certain that a community will experience a series of shocks and changes, sending ripples through the ecosystem.
How do we approach Community Health?
The definition above invites a series of questions: how do we best satisfy the needs of the members? how do we become more adaptable or resilient? How do we promote functioning subgroups?
Because each community is different and because community health is complex, the answers will vary and will likely require some experimentation. The key is knowing where attention is needed, and how to gauge progress. Which is what we're covering next.
We assess a DAO's Community Health at 3 levels of granularity:
Layer 1 -The vital signs: a frequent, quick check to take the pulse using global indicators and adjust the level of attention given to improving community health. For example, a Layer 1 Health check can tell you:
Is my community aligned on a shared identity?
How engaged is my community and how is retention?
Are we risking losing contributors through an unhealthy community?**
Layer 2 - The health assessment of the different nested systems: a more detailed assessment of the health of the different subgroups and cliques, the relationships between members and the well-being of the members themselves. This view allows targeting initiatives with precision.
For example, a Layer 2 Health check will tell you:
How many sub-groups exist in my community and which need attention?
Is my community siloed or, on the other side, too connected and overwhelming?
How decentralized is my community?**
Layer 3 - The enabling factors for long-term health: a thorough investigation of predictive factors such as trust, self-empowerment, communication practices, psychological safety, etc. by leveraging data-driven methods and tailored interviews to give you insight into how the health of the community will evolve over time.
For example, a Layer 3 Health check can tell you:
What tensions exist between different sub-groups and can we sustain them?
What voices (contributors’ needs and aspirations) are not heard and met?
Why are people leaving us?
That's why we have built a tool to make it super easy for you. Interested?