Almost a Week of Zappl Data - Lets Dig In - Steemit Business IntelligencesteemCreated with Sketch.

in zappl •  last year

With much excitement on Steemit,  Zappl launched on the 23rd of October and I have heard much chatter about the app in different communities build around Steemit.

Being the new App on the Block, I though it would be a good idea to look at the first (almost) week in Zappl’s life through the blockchain data.

As always I have used Power BI to connect to  @arcange  SQL database and I have taken data from the 23rd October to 30 October @ 22:30 GMT

When I originaly decided to do this analysis, my though was on filtering the Comments table by the category Zappl. However a post from @crokkon brought to my attention that included within the Json column is the app from which the posting was made.  

Using Power BI it is possible to parse a json column in the dataset, which would enable me extract the apps used to post to steemit.  I was then going to filter the table based on Zappl/0.1. 

This did not work.  It seems because I parsed the json column and created a new column for the apps, a filter on the new column will not pass back up the chain to the database.

My workaround for this is to filter the Json column to rows that only contain ""app"":""zappl/0.1""" and not bother with the parsing.

Lets see how Zappl is Performing

In total there have been 599 posts and 117 comments made via Zappl by 269 unique authors. Averaging at +100 posts per day

The column charts below show the total posts and comments by day.  Zappl was not live for the full day on the 23rd and also today 30 Oct is not yet complete

The second column chart represents the same data but showing the breakdown by %


In the line chart above we can see the unique daily number of authors on Zappl, peaking this week on the 24th with 96 distinct authors.

The chart below represents post and comments made by time of day


The current pending payouts value is $947.84.  this is subject to change as these posts are not yet past the 7 days mark for payouts. This can be further broken down to $943.03 for Posts and $5.81 on comments.  This give an average post value of $1.57

The table below shows the authors sorted by pending payouts and the number of posts or comments made by that author via Zappl.


Interesting also is the Categories that posts have been allocated too


 As at the time of taking the data, 6117 votes have been made on Posts made via Zappl.  This is not how many Votes were made via Zappl but the general performance of the posts on the Steemit Platform. That gives an average of $0.15 per vote and posts get on average 10.21 votes

How does this compare to Steemit in General?

To get a general perspective on this data I had a look back at the data from the September Posts Benchmarking report.  At this time the average payout for a post was $2.63 and the average vote was worth $0.12.  The average number of votes per post in September was 21.69

Awesome Start to Zappl - well done to the team involved

 I am part of a Steemit Business Intelligence community. We all post under the tag #BIsteemit. If you have an analysis you would like carried out on Steemit data, please do contact me or any of the #bisteemit team and we will do our best to help you... 

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I wonder if people are making alt accounts for Zappl?


yup, wanted to write a lot of short 1 liners but didn't want to exploit old curation trail

admittedly i give myself a 20-30% upvote to support short content on the platform and make it worth my while


@stellabelle yes, they are making alternate accounts to Zappl with. To sort of separate their main SteemIt user accounts w/ an alternative.


ohh this is rather interesting


I'd definitely recommend that people do use an alt for Zappl. Right now, the feed is based on users that we follow and their resteems. That means an author that wants to post across multiple niches will annoy a good number of their readers. Once the UI gets better ways to filter then the rationale for using alts to manage different content / content-types will diminish.


Love the angle @stellabelle, give it time, at the moment the rep on the accounts posting are too high to be 'new' account, however if the average reputation of authors drops this would be a good indicators that new accounts are being generate for zappl. it will be interesting to see who is setting up these accounts and funding them. Hoping that the vast majority will be genuine new users.

Zappl would also be able to do some tracking on this via their website stats and tracking of IP addresses. I would be happy to work with them on this data.


I did.


have you posted with this alt account yet to zappl?


Yes, and I will power that account up after the btc hardfork.


Most definitely using an alt account for Zappl, at the very least until there is an option on the blockchain along the lines of do_not_show_on_steemit or apps can keep their posts within their own silo, as should happen with SMTs.

The temptation to zapp is big and I don't want to cause additional noise to an otherwise mostly longform reading audience/crowd. The inconvenience of that is of course that autovoters get lost, but let's keep the pool healthy and work again to earn rewards rather than benefitting the autopilot now.

Congratulations! This post has been upvoted from the communal account, @minnowsupport, by paulag from the Minnow Support Project. It's a witness project run by aggroed, ausbitbank, teamsteem, theprophet0, someguy123, neoxian, followbtcnews/crimsonclad, and netuoso. The goal is to help Steemit grow by supporting Minnows and creating a social network. Please find us in the Peace, Abundance, and Liberty Network (PALnet) Discord Channel. It's a completely public and open space to all members of the Steemit community who voluntarily choose to be there.

This post has received a 0.63 % upvote from @drotto thanks to: @banjo.

@paulag very impressed with this data gathering. When we were talking in SteemSpeak I didn't realize what you were going to do . Thank you!


I often go to communities and ask for ideas or inspiration :-)

If you do have further ideas let me know

When I originaly decided to do this analysis, my though was on filtering the Comments table by the category Zappl.

Many apps also make themselves beneficiary for each post contributed through their pltform/interface. That could possibly also be a table to crawl in future BI analysis.


Yes I have seen this with Dtube and esteem