I don't understand this bit as the system was introduced on 24/1 shouldn't everybody's before number be equal to their rank? So all Sr. Members would have started at 250 etc.
I just wanted to make the point that you can't really do a comparison of the numbers that ranked up yet as it takes 8.5 months to get the activity to get from Sr. to Hero we'll have to wait that long to get a fair measure.
True, everybody's before number should be equal to their rank. I´ll explain what I meant in my referenced comment about the Before Data not being 100% exact:
- Merit Txs were based on the extraction that runs up to the 23/03/2018.
- Rank data is extracted with a snapshot for each user somewhere between 28/03/2018 and 29/03/2018 (quite a few hours are required, so snapshot is not simultaneous for every user whose data was extracted).
I worked back from the current Merit Balance (28/29th), substracting the Merit awarded, to get to the initial Merit status of each user.
There are nevertheless some gaps due to the underlying raw data being analyzed having a few days difference. Basically, I don't have in this analysis all the Txs until the exact moment that each individual user's snapshot was taken (lacking 5 days transactions to be precise).
Let's say for example user X had 60 Merits on the 28/03/2018 and the sum of Txs for the user shows he was awarded 50 Merits since the kickoff until the 23/03/2018. That would mean that 10 Merits are non justified from the Tx, so they could either be:
- Given in the initial airdrop (10 lets say)
- Or have been generated between the 23rd and the 28th.
I cannot tell the exact origin of these 10 Merits with non-100% synchronized data sets, but I do know that the user X does indeed have 60 Merits (at least on the 28/29th), and at leat 50 received through the TXs.
The above should, notwithstanding, have little effect in the overall picture of the analysis presented. Future updates (If demanded..) could be made to shorten that window to a max. of 1 day lag between the two datasets implied.
In relation to the second point you mentioned, I think it can be done: If we take any consecutive two month window from last year and knew how many users had ranked up in that window frame (regardless of how it took them to get there), we could compare to current two month timeframe.
Say for example Feb/Mar last year has 30 users rank up to Sr. Members (however long it took them). We could compare those to current rank up data (18 Sr. Members). Ofcourse context is different and should be stated to interpret the results.