Hey @David_NEAR
I will use the Airmeet platform to organise my events to track and measure the success of events Airmeet provides many tools like email tracking, poll, Q&A tools, etc. For example, in-between events or at the end of the event, I can run multiple polls to take feedback from the attendees, Email tracking option of Airmeet can help us to gather emails of attendees to send newsletters later to the attendees, and I will share bit.ly short links of NEAR social media in the event chat to track the conversion rate of the event, but I’m open to any suggestions. Would you please free to suggest If I’m missing anything?
The Impact I expect from these events is that I will stimulate interest in the NEAR ecosystem, which is a broader point. Still, if I describe you in detail, then with the first event, I’m approaching some devs who are actively working with a company, and through this event, I’m going to teach them about the products of NEAR like SandboxDAO, Aurora, NEAR tip bot, etc. They can implement these NEAR products in their office environment like they can fund projects using DAO, use tip bot in their group, and so on.
The second event will be with some dev/computer science students who know about blockchain development, so my goal is to teach them why they should prioritise the NEAR platform for blockchain development by telling them about Aurora, NEAR developer business model, fee structure, NEAR grant, etc. I will airdrop some tokens to the attendees to kick start their NEAR journey just after the event to boost engagement.
If you want to know more about my plans on articles, then let me know. I use top third-party publications like Hackernoon or regional magazines to publish my articles, and as we know, these publications only allow high-quality articles. Later, they share the article multiple times on their Twitter with thousands of followers; thus, I get more boost on my article. From my side, I propagate my article everywhere on social media like Reddit, Quora, etc to gain maximum attention.
You can check previous statistics of an article published on Hackernoon: