Thanks. I didn't check the homepage and looked for pricing info in the navigation links, felt it was needlessly difficult. Pricing should be easy to locate from every page for a product like this.
Discovering that users are having difficulty finding pricing information... might be one useful piece of data you could garner with a good analytics tool.
Also I just checked out the pricing's placement and that is utterly terrible UI - the site uses light greyshade striping in the background for difference sections and then has the pricing block proceeded by a very dark background block with no information immediately visible - this is a clear visual flag for the rest of a page being irrelevant and a footer.
And, just to clarify, the site's actual footer uses the exact same coloring for the footer along with a similar amount of excessive top-padding.
Genuine question, how would you find that users are struggling to find pricing using an analytics tool? How would you set that up / what would you look for to identify that? Something like scrolling around / back and forth implying they're struggling to find data or something?
A good signal would probably be dithering as you mentioned above - either scrolling back and forth through sections or navigating through different components if you website has a paged layout.
Additionally, as a business, you want to make sure users are following a pretty predictable flow through some limited entry points (like homepage, FAQ, information bulletins) - then either to pricing and then additional information or additional information then pricing (then, ideally, a sale).
If a user is returning to the entry point (i.e. a flow like information bulletins > home page > FAQ > information bulletins) and that happens enough then you can assume that some information users want after the FAQ (maybe, ideally, you think the pricing) isn't being delivered to them and so they're returning to their entry point to see if they browsed the information incorrectly.
If you've got good stats on how far down on a page people are scrolling that could also be something helpful to detect the specific UI issue I mentioned in the post above.
Edit:
I might suggest Don't Make Me Think by Steve Krug[1] as a resource if you'd like to learn a bit more about user flow analysis.
Hmm, fair enough. This is ~what I was thinking, making inference from their flow through the site. I have seen that book on the desk of design folks I've worked with, but I've not looked through it... not a bad idea though. Thanks.
