Network Statistics

This section contains general stats, like the number of transactions, active users as well as transactions per active user, both in counts and growth, given a specific cohort (timeframe) and date_filter in the NEAR network.

Dashboard Parameters

1. Timeframe: Number of days back
2. Date_filter: Hourly, Daily, Weekly and Monthly

User Retention-Like Metrics

This section contains statistics about what percentage of users are new vs old in the ecosystem, given a specific cohort (timeframe) and date_filter.

Bounty Specific Findings

When specifically looking at the timeframe 90 days as well as looking at the data in a daily format, what we can see is that there were a few active user spikes around the 11-12th and 20th of April which both correspond to spikes in new users using the network. What we can also see is that there was a massive transaction spike around May 10th (during Terra collapse) that is also reflected by the number of transactions per active user. We can see that up until May 10th the number of transactions had been growing greater pace but ever since has slowed down over time. What we can also see is that the old vs new % value for the 90-day cohort is stabilizing at around 20% of users being old users, which is not a bad sign for the network. When looking at the 9000 day timeframe , in other words since the network’s inception, we can see that the old vs new cohort % is stabilizing at around 15%, which is still a pretty high value comparably. Also, we can see that there was a massive spike in new users around March 16 - 20th.

Citizens of NEAR

When looking at the total active users in the last 90 days, what country would NEAR resemble?

NEAR would resemble Durg-Bhilai Nagar with a population of about 1.24 M people! Durg-Bhilai Nagar is a city in India that serves as an educational hub in the region, with a total of 59 universities and colleges such as IIT (Indian Institute of Technology). That’s pretty cool!! 😎