[Steemhunt] Hunted products analytics

in #steemhunt6 years ago (edited)

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Hi, @jayplayco here.

I have done some number crunching based on open numbers to see how Steemhunt is moving forward in a bear market like now.

0. Repository

https://github.com/Steemhunt/web

1. How To.

I have gathered the information on the @steemhunt account, as they are publishing a daily report about how many hunts have been verified and how much SBD the hunts have created. (The SBD created includes the voting from the Steemhunt account). Additionally, I have gathered information from coinmarketcap.com to include the historical price data of STEEM. Based on this data I used the following formula to get an average value for a daily Steem price cleaned data.

Daily gathered SBD / Daily Steem Price = Average Value

The data is based on the last 3 month beginning from 15th of November 2018 to 14th of February 2019.

2. Products


Daily hunted products

We have a glitch at the beginning of February and it was due to a system upgrade of Steemhunt. The graph looks like as the hunts are on a similar level, but if we dive into the details it shows a bit different picture.

  • Average hunted products Nov. 15-Dec. 14 : 151.6 products
  • Average hunted products Dec. 15-Jan. 14 : 138.97 products
  • Average hunted products Jan. 15-Feb. 14 : 164.78 products

The total average for all three months is 151.7 products and the activity in December was a bit slower. It may has to do with the holidays in December or also with the average Steem price, which was at a level of 0.27USD in the second period compared to 0.37USD in Nov. 15- Dec.14.
The good part is, that the average hunted products are increasing again and are now on a level of 164.78 products per day.

2. Products vs. SBD

Based on the hunted products number the daily generated SBD reward is moving on a similar level.

If we want to look into the rewards, we have also to look into the relation with historical Steem prices.


Generated SBD rewards at Steemhunt

Similar to the generated SBD rewards we can see as the Steem price is declining, the rewarded SBD is also declining. The main reason here is that the SBD's generated as the reward at Steemhunt is still mainly created by the main account @steemhunt which leads to a proportional high relation to the Steem price. As soon as Steemhunt's user base is growing rapidly, this picture would change.

3. Average daily Value


Average Daily Value

Daily gathered SBD / Daily Steem Price = Average Value

The average daily value is giving a picture of a comparable value of Steemhunt's generated rewards. It also shows a slight decrease, so let's get into details here.

  • Average Value Nov. 15-Dec. 14 : 1253 points
  • Average Value Dec. 15-Jan. 14 : 1328 points
  • Average Value Jan. 15-Feb. 14 : 1021 points

These numbers are interesting, as we can compare it with the average of hunted products. It shows a different picture and gives us the insight that we had the highest average value points between Dec.15-Jan. 14 and that it is decreasing very fast in the most recent term to 1021 points. It may is in relevance with the fact Steemhunt had decided to decrease the HUNT token rewards end of January or it could point (supposing that the rewarding part of the account @steemhunt is on a similar level) that fewer users are curating and upvoting at Steemhunt since a month.

So could this be a problem?


Source: StateofDapps

If we have a look at https://www.stateofthedapps.com/ and see how the development of user engagement is, it actually looks ok. It means that even when the daily reward pool (upvoting users) may shrink for the moment, Steemhunt got more active users on their platform (which is based on different kind of activities). So, in my opinion, it is a short reaction and will recover again.

4. Average daily Value based on Weekdays

Most rewards are created on Tuesday. Saturday and Sunday seem to have the least upvoting activities from hunters. We can assume that active Steemhunt users could plan on posting on Tuesdays.


Daily hunted products

And looking into the numbers shows that Tuesday is really the day with the most hunted products. On the other side, if the hunter would like to have a better chance to rank, they should target a Sunday or Monday, as these days are the least crowded days. If you look into the upvoting pattern, Monday would be the best day to give your hunt a better chance for a good ranking.

5. Conclusion

Even on this bearish market, we can see that Steemhunt is keeping a good pace. The number of hunted products are increasing again, there are fewer hunters upvoting the hunts, but the active user number is increasing, which could be interpreted that more new hunters are active.

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Hey @jayplayco, great work!!
(Your initial version of the post had the #analysis tag. Even though this tag was removed later on, I still believe this category fits pretty well here.)

The products-per-day graph is pretty interesting! While lots of metrics on Steem are heavily biased by bots, the Steemhunt products require "real humans", and seeing this activity rising is a great sign! And StateOfDapps confirms a growth in the user base. I would not have expected such a strong variation of rewards across the different week days - do you have any idea what makes Tuesdays more attractive for votes compared to the other days? It's been a while since I saw the last activity graph across all Steem, but I'd assume we'd see a reduced activity over the weekends there as well.
In the context of reproducibility of the results, it would have been great to have a few more details, scripts or queries on how you acquired the results.

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[utopian-moderator]

Thanks a lot for your feedback! As the timeline for Steemhunt is based on KST (Korean standard time), it would mean that for most of the users in America it would be somehow late Monday. I think that could influence the graph for Tuesday definitely.

As I have no direct insight of the data, I am using reports from Steemhunt's account (They are reporting on a daily base how many hunts have been verified and how much STU has been generated) and I have manually input that into an Excel data to pivot it and get the overview. Additionally, I have copied the history data from Coinmarketcap for Steem matched to the day and used the opening price for it. So my script was my manual searching and typing it into an Excel sheet :)

Wasn't sure if I could use the analysis tag with that kind of data, as most contributors on that tag did so much great analysis based on SQL queries, etc. :) But thanks a lot~!

Thank you for your review, @crokkon! Keep up the good work!

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