Fun with Web Metrics

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Where to Begin? Metrics 101

Let’s go over some of the basic “units of measurement” that are related to web metrics.

1. “Hit”

I’m going to use the slightly-fluffy definition that a “hit” is any file on your site that gets requested by a browser.   It does not mean a web page – in fact it’s all the pieces that go into a web page: the HTML code, the images and logos and other design elements, the style files, and other program files (e.g., Javascript).    In fact, rendering a web page might actually involved dozens of server “hits”.

This gets slightly muddied in the context of web metrics because invariably someone will ask you questions like “So, how many hits does your site get?” when they actually mean “page views”.

Another way to think of hits is “anything that creates a new row in your server log files can be considered a ‘hit’.”   So, if you’re relying on your log files to look at page views, etc., you’ll have to filter out those lines that are really page elements.

2. Page

Simply, let’s take this to mean “what the user sees in the browser.”    It can be a static page, or dynamically created as part of an online service (e.g. a search results page).

3. Visit

The sequence of pages displayed to a user/visitor from the same site (which doesn’t necessarily mean the same server).   There’s no absolute definition about when a visit ends: for example, if someone is looking at your site, gets up to do something, and returns hours later, is it one visit or two?   One of the conventional practices is to treat a gap between page views of >30 minutes as the boundary between one visit and the next, even if by the same user.

4. Visitor and User

The person (or persons) who are experiencing your site through a browser.   Generally they are identified in the server log by hits within the same visit from the same browser (identified by IP).   Depending on the nature of your site, you might want to make a distinction between “visitor” and “user” if you have registered users.

Now some of you have already poked holes in EACH of these definitions:  What about non-human “users?”   What about IPs that are gateways for many computers? and so on.   One of the fundamental truisms about dealing with web metrics analysis is that the data are extremely “fuzzy”.   Sometimes it’s possible to get a sense of when atypical behavior is present.    Sometimes you have to accept the uncertainty and hope that a useful picture becomes clear over time.

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September 2, 2010 - Posted by | metrics 101, terminology | , , ,

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