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Visitor segmentation

Segmentation is a fundamental marketing approach, but it is often difficult within web ana-

lytics to relate customer segments to web behaviour because the web analytics data aren’t 

integrated with customer or purchase data, although this is possible in the most advanced 

systems such as Omniture, Visual Sciences and WebTrends.

However, all analytics systems have a capability for segmentation and it is possible to cre-

ate specific filters or profiles to help understand one type of site visitor behaviour. Examples 

include:

● 

 First-  time visitors or returning visitors

● 

Visitors from different referrer types including:

 

– Google natural

 

– Google paid

 

– Strategic search keyphrases, brand keyphrases, etc.

 

– Display advertising

● 

Converters  against   non-  converters

● 

Geographic segmentation by country or region (based on IP addresses)

● 

Type of content accessed, e.g. are some segments more likely to convert? For example, 

speaking at Ad Tech London ‘06, MyTravel reported that they segment visitors into:

 

– Site flirt (2 pages or less)

 

– Site browse (2 pages or more)

 

– Saw search results

 

– Saw quote

 

– Saw payment details

 

– Saw booking confirmation details.

Budgeting

To estimate profitability and return on investment of e-channels as part of budgeting, com-

panies need to consider both tangible and intangible costs and benefits. A suggested checklist 

of these is shown in Box 12.4.

A similar approach can be used to calculating the ROI of enhancements to an e-commerce 

site. Hanson (2000) suggests an approach to this which requires identification of revenue 

from the site, costs from site and costs from supporting it via a call centre. These are related 

to profit as follows:

Operating profit 

= Net income from sales - E-commerce site costs - Call-centre costs

Net income from sales 

= (Product price - Unit cost) * Sales - Fixed product costs