What Not to Do When Analyzing Your Site

Paths don't matter
Many stats packages will give you an analysis of your most common navigation paths through your website. Unless you've got an incredibly restrictive navigation structure this is a complete waste of time. You will be lucky if the most common navigation path people take through your site accounts for more than one percent or two percent of all visits. If you bothered to get a list of how many different navigation paths people took through your site, you would probably find that there were almost as many different paths as there were visitors. One of the things that underpins the nature of the web is the ability of hyperlinks to provide people with the option of following information in an associative way, a way that mirrors their thinking. This is what makes the web so great, so fundamentally different from printed material. 

The only time you want somebody to follow a linear path is when they absolutely have to. Such occasions occur around forms. Typically if somebody wishes to buy something, or sign up for something, or get a quotation, they have to go through a series of forms. The reason it's a series is that no designer wants to present a potential customer with all the questions they need to answer on a single form-- that form would be intimidating. Thus we lead people through a series of successive forms. This is exactly when you need to analyze a page-by-page path. But what you need to know is clickthrough rate, not what path people took-- there is only the one path. What you need to know here is how many people on page A followed through to page B and how many of those followed through to page C and so on. If you're not happy with the clickthrough rate on one of these pages you need to cross-reference success and failure here with the amount of time spent on this page and previous behavior.

This is not to say that you do not wish to analyze some things regarding how people moved through your site. But you don't need to look at this at a super-detailed level. On most sites, all the pages in a given section are the same design and function. There is usually a logical progression from one section to the next. For example, people may move from a listing of product categories to category pages that list individual products and then to those individual product pages. In such a scheme they will probably bounce back and forth between these different levels in your hierarchy. Trying to follow these individual paths is confusing.

What you are really concerned with is how well each level in the hierarchy performs. This means you need to look at overall stats for each level, not specific paths. If you're happy at that level, then you move on to looking at how individual pages in a particular level vary from the norm for that type. For example; is there a particular product listing page that has a significantly lower or higher clickthrough rate than the rest? If so, what is different about that page from its fellows? If its performance is lower, that difference is something to eliminate. If its performance is higher, that difference is something to emulate on its fellow pages. You need to amalgamate all the visitors across all of the individual paths in order to be able to draw conclusions about the effectiveness of your design. Looking at individual paths in this respect will only obscure things for you.

Conclusions
Just because a stats package is giving you a metric doesn't mean it's of any use to you. You need to know when to drill down on common stats, such as average duration, and when to look at things differently. The secret is to decide, in advance, what it is you want to improve in your site. You need to be able to formulate this in business terms. Don't look at your stats until you know what you're looking for or you risk being misled or confused. If you're looking at how effective your web pages are as sales tools, you don't want to count people who bounced from your site and never saw them. In this respect it doesn't matter to you what search engine they came from. What is more important to you is what they were looking for and whether you gave it to them. The core of web analysis is a simple 1-2-3:

1. Do I have what people want?
2. Did I show it to them?
3. Did they buy it?

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