Ultimately we want to make it easy for users to complete certain tasks. Sometimes we can directly capture this type of metric, but usually we need to confine ourselves to metrics that are more removed from the actual user experience.
If we take the traditional view of a content inventory or audit, we have rows representing each page (so each row has a unique URL) and then we have columns for things like the meta description or crawl depth. These columns are the different fields we have available to us in our content analysis.
Your content analysis needs to be grounded on your analyze goal.
Content analysis does not necessarily mean opening up a spreadsheet. Before diving in, you should define your basic approach to the analysis.
Although you can use this database however you like, in general we recommend that you build up a list of fields that will be useful for your analysis. To do so, just click on the heart next to any field name. After you have hearted some fields, you can see an analysis of your list at My List ♥ (at which point you can move to ④. Start iterating on your analysis, starting with the basics).
General usefulness is a blend of the difficulty in getting the value and how useful it is once you have it. These stars roughly correspond to:
Ease of automation is how easy it is to get the value:
Obviously all of the above is ratings in the general case. You may have particular needs for fields that are generally not useful, and you may already have some clean data that makes automation trivial for some elements that are more generally difficult.