The poll questions are fairly neutral, and I find your rhetoric objectionable. It's more like we have a jar of beads; I say the jar contains 100 beads and you say the jar contains 1000 beads. We will just have to wait until they are counted to be sure, but you in no way have the high ground or anything.
No, it's nothing like that.
The questions are highly biased.
The poll is entitled "how important is it for you that the 2nd row seats of the Model X are stowable?" - it's not entitled "Is it important for you", it's "how important" which implies that it is important.
The subtitle of the poll is "
What do you need to not cancel your Model X reservation?" No selection bias from that? Really?
The next two options then start with "I require" and are loaded toward someone who feels very strongly.
The third option says "It's not a deal-breaker... but...", which implies a negative on top of the deal-breaker.
And finally, your fourth option says "I don't care either way", which is going to be undersampled because of self-selection - those who don't care are going to answer the poll on a lower frequency basis than those who have passion about it.
So then, you went to compare the number of people that care (first 2 options) vs. those who don't care as much (next 2 options, more apathetic). YOU CANNOT DO THIS - it will generate lower frequencies in the latter vs. former.
The *only* thing this poll will tell you is that 58 people selected option "A" and 47 people selected option "B". You can't guarantee they're even Model X reservation holders, or even that they have any interest in the Model X whatsoever. For all we know, 15 of the 58 could be some of the lurker GM execs who would love to see an article on the blogs pop up that "Tesla doesn't care about its customers".
The poll is deeply flawed. Not just a little bit, but deeply flawed from a statistical point of view.
I reiterate the basic statistics textbook information I posted earlier:
From Essentials of Statistics, 5th ed., by Triola:
* Sampling Method: With voluntary response samples (self-selected samples), we can draw valid conclusions only about the specific group of people who chose to participate; nevertheless, such samples are often incorrectly used to assert or imply conclusions about a larger population. From a statistical viewpoint, such a sample is fundamentally flawed and should not be used for making general statements about a larger population.
* Small Samples: Conclusions should not be based on samples that are far too small.
* Loaded Questions: If survey questions are not worded carefully, the results of a study can be misleading.
* Order of Questions: Sometimes survey questions are unintentionally loaded by such factors as the order of the items being considered.
If you find someone who has any reputation in statistical analysis willing to stand behind your statement, I'll hear her/him out. Until then - I'll go with well-established statistical analysis rules. That said, you're well-set in your opinion, in opposition to nearly the entire world of statistical analysis.
If you can't consider that, then there's nothing else I can do, in which case I wish you well.