I like a good soup or stew. Throw in a little of this, a pinch of that, and the combination of flavors creates something entirely new, especially after it’s been in the refrigerator for a day or two. Your Web data is more similar to this than you might think, and that’s not such a good thing.

For example, let’s say your average time on site is 63 seconds. How many visitors do you think actually spend 63 seconds on your site? Probably very few. More likely, a large number of visitors spend 0 seconds (bounces) and a smaller number spend several minutes. So what can you actually do with data like this?

The answer is to separate the ingredients that went into this data stew. This enables you to compare smaller groups of visitors to uncover the factors that may have influenced their time on site. Fortunately, this is easier than “un-making” real stew. There are several methods, giving you different levels of granularity, which fuel different kinds of decisions.

Segmentation

Broadly grouping your visitors can help you make big-picture decisions, like setting budgets across different marketing channels. Segment your traffic by source, such as paid search, organic search, email and other referrers. Compare the average time on site metrics for each of these segments to measure your relative effectiveness in each area. It’s best to look at multiple metrics like conversions and other goals as well, since each channel could be reaching visitors at different points in the buying cycle.

Dissection

Dissection uncovers more specific data, such as which landing pages to improve or which search keywords to optimize. This goes beyond the quantitative measurement of a typical “top 10 list” to show qualitative metrics such as average time on site or conversion rate for each item. Sorting the list by total revenue (if you track it) can be a great way to combine quantity and quality to reveal your heaviest hitters.

Segmentation and Dissection Together

Dissection on extremely diverse items such as keywords can be obscure and confusing. Try segmenting on a particular root of a common keyword and dissect its variations. This process digs into your “long tail” to uncover variations and modifiers of your core keywords. For example, you might find that visitors who include the term “free” in their search have a very high bounce rate. Knowing this, you can add a negative match to that term to reduce wasted PPC ad spend.

Upcoming AMA Webcast

For an in depth look at how you can compare different groups of visitors to uncover actionable data to help improve your marketing ROI, join Andres Galdames and I on Thursday, August 21st, 2008 at 10:00 am PDT for the American Marketing Association webcast, “Web Analytics: Segmentation Leads to More than Just Reporting”. [https://amaevents.Webex.com/amaevents/onstage/g.php?t=a&d=963190956&sourceid=Lyris]

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