Sales Analysis

The first step in successful analysis of customer behavior is having the right e-commerce system (shopping cart) installed on your site. When considering an e-commerce system, you need to list and prioritize the statistics which are important to you - these will determine the choice of an e-commerce system and supporting statistical modules.

For example, the Miva Merchant or the ShoppingQ e-commerce systems allow the use of the Urchin e-commerce reporting module, which combines sophisticated log file and e-commerce analysis. For the cost of a log analyzer such as Webtrends, you get an equivalent log file analyzer plus e-commerce analysis.

Another product to consider is Clicktracks which does a great job, for a reasonable price, of log file analysis, and tracking visitors right through to the sale. Thus, it is very useful for ROI analysis and determining the keyword phrases that lead to the most new customers.

Google Analytics is a very popular free statistics package from Google. This is the same division of Google that now offers the Urchin ecommerce module. Google Analytics provides comprehensive statistics and best of all, the package is free.

Whatever package you choose, it should either include trend analysis (such as graphing weekly results, over time) or provide for easy export of the results to a spreadsheet or database.

What customer analysis statistics are important? These are the main ones:

• matching sales revenues with site visitor activity, by week and month, in total and by product line
• matching weekly and monthly sales with site visitor activity over time (trend analysis), in total and by product line
• matching sales revenues with site visitor activity, by day and hour, in total and by product line (to measure the effectiveness of advertising campaigns)
• matching sales revenues with site visitor activity from main referrers, by week and month, in total and by product line. Where the referrer is a search engine, also matching the search query with sales revenues.

These statistics are combined with log file analyses of visitor activity on the site.

What are these statistics telling us?

• who did buy
• how much did they buy
• when did they buy
• what did they buy
• from where they arrived at the site
• in which region they are located
• how they arrived at the site (e.g. by what search engine query)
• from which page they entered the site
• their path through the site
• from which page they left the site

on a weekly and monthly basis and the trends, over time.

More about e-commerce reporting