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copied!<h1>Web Analytics Solution</h1> <p>First of all you need to choose a general propose Web Analytics Solution. Since you are an E-commerce you want to choose one that has good support for tracking E-commerce data.</p> <p><a href="http://www.google.com/analytics/" rel="nofollow">Google Analytics</a> is the obvious choice here not only because it's free but also because it's better documented and easier to implement. </p> <p>depending on your size it may make sense to implement a more Enterprise level Ecommerce solution. You may want to take a look at <a href="http://www.omniture.com/" rel="nofollow">Adobe Omniture</a> and <a href="http://www-01.ibm.com/software/marketing-solutions/coremetrics/" rel="nofollow">IBM CoreMetrics</a>. They are much more expensive not only because of the licenses but on an implementation perspective. It may take months to implement one of these other tools and the cost of the implementation can be almost the same as the costs for the licenses. Still if you need more enterprise level analysis and integrations with other BI solutions it may be worth taking a look at these. </p> <p>Note that Google Analytics also has a <a href="http://www.google.com/analytics/premium/" rel="nofollow">Premium Edition</a>. This is a fairly new alternative and provide some extra features and early access to beta features. </p> <h1>Product Recommendation</h1> <p>Depending on your Ecommerce platform you might already have some kind of product recommendation or up-selling. You usually can improve these systems based on analytics data. There are just a few options on the market, and most companies doing this tend to develop their own recommendation engine. </p> <p>If you're just getting started with it, it might be worth looking at <a href="http://www.liftsuggest.com/" rel="nofollow">LiftSuggest</a>. I haven't tried it but they seem easy enough to implement and leverage Google Analytics data to improve cross-selling.</p> <h1>HeatMap</h1> <p>It's easy enough to implement and may provide some nice isights. I find them more distracting usually but every now and then you can make good use of them. The most common seen around are <a href="http://www.crazyegg.com/" rel="nofollow">CrazyEgg</a> and <a href="http://www.clicktale.com/" rel="nofollow">ClickTale</a>.</p> <h1>Behavioral Targeting</h1> <p>This is a technique to customize your site based on a previous knowledge you have about the visitor in order to increase his conversion rate. Tools don't help you much here, since you have to customize your site and no tool can predict how to do that. One common approach is to create buckets depending on factors that you can infer. For example: Users with Internet Explorer might be less tech savvy and thus might be more interested in non-tech products. On the other side Linux users are probably on the technology field. So you can put users on buckets depending on which country they came from, which browser they're using or if they are logged in you can use the information they entered on their profile or based on previous purchases. One tool that helps you doing that is called <a href="http://btbuckets.com/" rel="nofollow">BTBuckets</a>.</p> <h1>A/B and Multivariate Testing</h1> <p>Google analytics has an A/B testing tool integrated with the tool. Another Good tool that provides both A/B and Multivariate testing are <a href="http://unbounce.com/" rel="nofollow">Unbounce</a>, <a href="https://www.optimizely.com/" rel="nofollow">Optimizely</a> and <a href="http://webtrends.com/products/optimize/" rel="nofollow">Webtrends Optimize</a>.</p> <h1>Custom Solution</h1> <p>Everybody these days are developing custom solutions. If you still have money and time to spend on Web Analytics after you exausted the other options you can look into building your own. Collecting the data the way you want and analyzing the granular data. Here solutions range fro server side to client side collection, but for the analysis they are usually done with <a href="http://hadoop.apache.org/" rel="nofollow">Hadoop</a> or with a OLAP Business Intelligence Tool like <a href="http://www.microstrategy.com/" rel="nofollow">Microstrategy</a>.</p>

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