With such raw data, graphical representations are premature. Some result has to be pretty substantial, and be an expected result, to be likely to stand up through further analysis. The 69% for answers given may be such a thing. It sounds right. However, 54% of those marked as "never came back" (NCB) also got answers, and so far did not come back.
At least two questions might be looked at: what happens to new users (or, more pointedly, why do some never come back)?; how do we, as a community, treat new users?
The second question can be considered because it likely has an effect on the outcomes for new users. Once bitten, twice shy. Perhaps we seem too biting? How to turn "Perhaps" into some meaningful knowledge?
Useless questions are useless. However, a user asking a useless question first up, isn't necessarily going to ask a useless question in the future. If their experience of asking their first question, which was important to them, but not the sort of question that fits on SO, is so bad that they never want to hear of SO again, then perhaps something is going wrong. I know that a lot has been put into the site to avoid being overtly "you are rubbish", but analysis of the data may reveal further areas where things need to be considered in that light.
Back to the data for now. There is more than one type of new user. Not all users just come to ask a question. Some are keen to answer. Some are keen to learn, and contribute where they can through edits, comments, and voting, before they feel confident enough to answer something. Some just come to learn, look, or something, without further contribution. Some of any of these groups may later ask questions.
For those who ask first up, there are two simple situations: after their first question, they ask another at some point; after their first question they don't ask a question - within the time-period being monitored.
That "time-period being monitored" is an obvious problem. Going back a year, or two years, may show a different sort of profile for the NCBs, although care has to be shown to consider whether SO was sufficiently the same a year, or two years ago, to attempt to understand any differences/similarities (big changes to the Closing last summer, for instance).
Then the simple situations can be a little more complex. Some of those "never came backs" may still be visiting the site, even though they have not asked another question. Even developers with experience sometimes ask questions, but less likely twice in a two-month period. Are some of the NCBs still visiting the site, and how many? What are they doing? Answering, commenting, editing, researching or just otherwise here from time-to-time?
A definitive definition of NCB will not be easy, but maybe someone who has visited the site more than seven days after the last activity on their question which was the last thing when the question was active (some formula to decide when community activity on a question stopped, which is not undone by someone providing a new answer or comment or vote three weeks later).
So, an NCB would be someone who has not asked a subsequent question and has at least not visited the site after activity on their question died down.
New users end up in one of three categories, CB, NCB and Others (who make the totals balance, even if too small in number to be worth analysing further - assuming the numbers are relatively small).
Then the "smack in the face" VS "encouragement" have to be broken out from the data.
The first are Downvotes, non-positive comments (yes, this is subjective, but it is the way the new user understands the comments which will affect how they feel about it), Closing and Deleting.
The second are Answered, Upvotes, neutral/positive comments, Editing.
"Nothing" doesn't really fit either group, until we know what "Nothing" is - which is going to be difficult without an initial manual reviewing of a sample of them. Results of analysis dictate when/if/priority of this being done.
So, CBs and NCBs broken-down by (net) numbers of Downvotes; another, higher priority, sampling for Comments; analysis of speed of Closing/Delete; number with net zero and actual zero question votes; number of net Upvotes; answered, no of answers per question, voting on answers (count, broad indicator of quality answer if at least n votes), number of acceptances, correlation between acceptance and highest-voted answer; number and type of edit (tags, title, body).
We can expect that Voting has an impact. We can expect that Comments have an impact, but not easy to evaluate up front. Closing/Deleting seems to be a candidate, and is open to some automated analysis. Edits may not affect things much, as an expectation, but would tend to be positive.
From the user, their own edits, Accepts and comments may indicate that they have an engagement. If many CBs take some of this action, it may be expected that some proportion of NCBs who act in a similar way on their initial question may still ask a second question, but it just hasn't come up yet.
OK, knock the above into shape, drop out the rubbish, include anything else rational, prioritise, estimate, and I want something substantial on my desk by this time next Monday.
Actually, you might want to explain a model for new users first. If I had mailed a leaflet to these 73,000 people, then 20/73 is a fantastic conversion rate. If I had made one sale to 73,000 people, I'd be very disappointed if I made a second sale to only 20/73 of them. So, the model is neither of those, but is there one?
Ask a good question, reply to comments, comment/vote on answers, accept what helped with the problem, continue using the site, asking, answering, editing, commenting... it is rarely going to happen with a first-time question from someone with little experience. Someone with little experience will have other questions to ask. They should be coming back. Next time their question should be better. Most of those 53,000 should be a source of future questions.
Just lastly, a breakdown by tags may be interesting. If Downvotes are a big influence, I expect that in some tags there is a greater tendency for over-the-top Downvotes than in others.