We use the word "app" while demonstrating QlikView and users tend to get confused by this word. Most of them get it after explaining what we meant but some don't. Have you guys encountered this situation? If yes, how do you guys explain this to end users?
Ahhh - the age old 'what is a .qvw?' question; is it an App, a File, a Document, an Application etc etc etc - from my experience; there is no definitive answer, Qliktech used to push 'Document' now they're pushing 'App' (I wonder why!?), so it seems even they don't really have a definitive answer.
Throughout my years in pre-sales I found the best way to describe a .qvw to the end-user was that it's akin to an Excel document; you have one file (that consumes one Document CAL - licensing is even more complex to explain to people so start as soon as you can) that can contain multiple tabs (worksheets) and within those tabs you can have multiple charts and objects. Also in the same way as you can email a .xlsx file and anyone with Excel can open it you can also do the same with a .qvw file - the file stands on it's own - visualization layer AND data layer.
In my opinion 'App' relates to a .qvw that fulfils a narrow need - 'show me monthly sales by territory on a map' (you would have a small amount of drill down (Sales Person, Product etc) and association but not much else - like an iPhone App; it quickly and easily does what it says; show me cinema times or what the weather is like; you can select a location but nothing more. Whereas a Document or Application provides the more traditional reporting / dashboard solution whereby it covers a wider range of requirements - eg an ERP reporting solution.
It sounds as though you're trying to get to that 'light-bulb moment' which for me was always the key; use the Films.qvw demo and end-users can't make the leap to their own situation and technical people don't see the power; use a too technical example and you loose the end-users who invariably claim Excel can do the same. I found the key to be a tailored example application and a story from within the data; seemingly random but actually planned out in advance - diving into the data and roaming around to find seemingly real world insights; '2010 profits were hammered in Dept X because of this order...and here's the invoice number, Business Name etc etc'.
Using that method I achieved a 90% SiB > Sale ratio.
