Custom Views give you a powerful way to look at your analytics reports. If you have not bothered to set any up then read on and see why it matters… When you first set up your analytics account Google creates a default view for your website that includes every piece of data that’s collected. This default view is what you are used to navigating around when you look at your different reports. However more data does not necessarily lead to better insights. Views are an effective means to look at the most interesting segments of your traffic.

The Event Tracking feature in Google Analytics is a great way to measure how users are interacting with your website content. By just adding a small amount of extra code to each web page or template you can track pretty much any actions that a user takes on a specific page, such as clicks on specific links, downloads or video plays. I guarantee setting up Event Tracking is worth your time and just the process of setting up Event Tracking and examining the possible behaviors that visitors can take on each page will get you thinking about what you really want your visitors to be doing.

Getting started with Google Analytics is sure to be confusing unless you have a good understanding of the terminology. This is certainly not a complete list of terms but it does reviews those terms which I think tend to cause the most confusion.

At, Himalayanwonders, most of the organic traffic to the website lands directly on our blog. Most of this traffic reads a few pages on the blog and then leaves without ever even looking at any of our products. We figured this situation could be improved if more of the traffic reaching the blog could be enticed to visit our product category and product detail pages. The Funnel Visualization feature in Google Analytics gives us a means to visualize the flow of traffic from the blog along with quantifiable metrics that we can use to measure success as we implement specific changes. Most examples of conversion funnels revolve around the checkout processes but if you have a little creativity and a clear objective in mind you can put funnels to work in a number of situations.

Are you struggling to measure the right conversion metrics and make sense of the different means to visualize funnels, goal -flows and visitor pathways? If you are not using Google’s Free Enhanced E-Commerce Analytic feature this article outlines what it is and how it can quickly help you increase your websites overall performance.

Here is a look at what might be the 5 best features followed by a brief outline of how to set this up for your e-commerce website.Google calls this powerful feature the Shopping Behavior Analysis Report and a quick glance at the report gives you a good picture of how the different layouts (templates) that make up your website are performing. Let’s assume we are working to optimize a typical e-commerce site consisting of several templates which include; informational pages, product list pages, product pages and the checkout process. Generally the goal of creating informational pages is to drive search traffic which after landing on the informational page should continue down the funnel to product listing pages and eventually the checkout process.

Google Analytics just incorporated a new feature that makes Cohort Analysis easier then ever. This might be one of the coolest changes to Analytics in the past year. If you have not heard about Cohort Analysis before this is a quick review.

We are constantly making changes to optimize our website, but measuring the true impact of those changes on different visitor segments over time is difficult with traditional testing tools. Cohort Analysis is a powerful tool for optimization that allows you to track how your audience or a specific demographic engages with your website as well as different marketing tactics through time. Standard analytic packages already allow us to attribute actions to specific audiences based on variables such as; demographics, device, geography. Most of incorporate this data into the A/B and/or multivariate testing that we do but we seldom think of the limitations of these common practices. The biggest issue with A/B and multivariate testing methods is that they only give a snapshot of performance during a specific time interval.

Measuring the conversion rate of a specific page or the value it contributes to an overall conversion rate is both an art and a science. This article examines several scenarios ranging from a single page website to a complex website with multiple templates where conversions are not as likely to take place on the first visit.