Effective Media Proposal Evaluation System for the Polkadot Marketing Collective/s (Stage 1: Focus on Builders)

In summary:

The current OpenGov marketing framework within Polkadot has resulted in a plethora of marketing proposals that are challenging to evaluate based solely on the information provided by the applicants. The strategic solution involves directly gathering preferences from both current and potential ecosystem participants and compiling a dataset to assess potential media reach or other possible goals. This approach will enable the community to make data-driven decisions and enhance the overall awareness of the ecosystem in a decentralized manner. We propose to center this research on builders, who are easily identifiable through public contacts and track records and represent a critical audience for Polkadot.

Motivation:

As decentralized activities in governance increase, there is an escalating need to evaluate the impact and outcomes of incoming proposals. At present, the community lacks clear understanding and metrics to guide decision-making and outcome assessment. Key questions include:

• How do we assess the potential of a given influencer?
• How do we determine the appropriate budget allocation for an influencer?
• How can we assess the actual cost an agent wishes to receive?
• How do we evaluate the results achieved by curators?

We propose conducting research to help clearly define tasks and independently evaluate various outcomes as they currently stand. This research aims to fill these gaps by providing clear guidelines and independent evaluations of different results.

Solution:

We propose reference research with effectiveness metrics. Decision-making requires a benchmark dataset to evaluate these queries, which can be straightforwardly achieved through research and report creation.

Why Builders:

We propose to focus on builders for multiple reasons:

1. Easily trackable within and across ecosystems.
2. Capable of rapidly floating between systems.
3. Accessible through public contact information.
4. Vital to Polkadot’s positioning as a developer-centric system.
5. Engaged in significant crypto transactions and real-life usage (payment, salary, spendings).
6. Active in long-term usage like staking and LP .
7. Often invest in various capacities (angel investors or open market).

Research Funnel Size:

The study will examine three major clusters of builders:

1. Builders who have engaged with Polkadot (through building, participating in grants, hackathons, treasury, etc.).
2. Nearby ecosystems that could potentially migrate to Polkadot and those competing for builders (e.g. rust-based: NEAR, Solana, Fuel, etc.).
3. Young, actively growing ecosystems (e.g., Era, Sui, Celestia, etc.) and those entering them.

An estimated 8,000 entries are expected at the top of the funnel, providing a broad and representative data set: 2,000 from Dot, 3,000 from other ecosystems (hackathons/ZK hacks, etc.), and 3,000 from new, actively growing ecosystems. This diverse audience will allow for evaluating preferences across different sectors, such as country-specific influencers and non-English media.

Research Scope:

Questions will explore their relationship to Polkadot, building needs, media consumption, key influencers, events, aspirations, and more.
The preliminary set of questions includes:

• • Their relationship to Polkadot.
• • Their building needs.
• • Their media consumption habits.
• • Their key influencers.
• • The events they attend.
• • Viable builds and their aspirations.
• • Their opinion leaders.
• • Their country affiliations (to identify regional influencers).
• • Potential information/education sources they've utilized.

Will be happy to have your ideas for questions/research targets!

Budget Models:

The primary proposal considers 8,000 potential respondents, with about 50% expected to provide at least basic info. We estimate that this number of initial contacts in the funnel is sufficiently effective to assess data and obtain representative results.
This dataset will not only provide general answers but also allow for evaluations of more specific clusters being researched. For instance, preferences by countries, niche influencers, local media, and media in non-English languages. This will also allow for a more understandable focus on creating materials to attract developers, which we view as an important task.

Research Main Goals:

1. Identify influential media for current builders and set clear evaluation metrics.
2. Enhance marketing efficiency and transparency, thereby building trust within the system.

Additional Goals:

1. Provide direction for engaging influencers effectively.
2. Evaluate the information structure outside the Polkadot ecosystem
3. Report on builders’ sentiments and challenges within and outside the Polkadot ecosystem.
4. Evaluate the effectiveness of current media strategies.
5. Formulate clear media buying strategies based on research findings.

Extra Benefits of Engaging with Builders:

Considering rewarding builders for survey participation could create a proper engagement funnel and potentially onboard builders from other ecosystems by offering on-chain tokens.

Report and Results:

Divided into two main milestones (50/50), with reports generated at each stage. We aim to publish team results and funding but will ensure data privacy. We plan to consider providing a list of GitHub accounts for community verification of survey participants.

Future Prospects:

Based on success and community feedback, this research approach could be extended to other audience segments.

Acknowledgements:

Special thanks to Raul for his support and to Giotto for steering the focus towards constructive action.