You can then also do a sensitivity analysis to figure out how much your conclusions change if you modify your priors. So if you, the reader, think the priors are wrong, then you can change them and re-do the analysis.
I think the most interesting thing about this analysis is exactly that: we can look at the priors and come up with a principled conclusion. We can then argue about whether the priors are right.
It's very easy to "make guesses" that present your conclusion, throw in a paltry amount of money, then make bank off the publicity.
This possibility poisons the well for the entire process. If they can make money off this even if they are completely off-base, then it's not rational to build up the trust necessary in their process to engage with their model.