Goals, Funnels & Filters

Anyone tracking web analytics has thought about how their own visits to the site being tracked are affecting their analytics. For example, a person who visits their own site several times a day to ensure that a page looks the way it is supposed to might be nervous that a bump in the number of visits and pageviews was caused by their own behavior and not authentic interest. Or, a person who is showing a colleague what’s great (or not so great) about their site may be concerned that the click path developed by Google Analytics reflects their own wonky click path that really had no logic or strategy to it.  So what do we do to keep this from happening? Well, enter stage left: goals, funnels and filters.

Goals

First, I want to discuss goals. A goal is a webpage that helps generate conversions for your site. With some extra code, they can even be file downloads or on-page actions. Some examples of goals include a thank you page, a purchase confirmation page, an about us page or a particular news article.  These are helpful because they take the guess work out of determining how many of the visitors that have come to your site converted into actual sales – you can really just track them yourself!

In reading up on goals, I realized something my own blog was missing – an About Me page!  I decided that it would be a good idea for me to add an About Me page where I provide some background information about who I am and what I plan to accomplish with this blog.  Since the purpose of this blog (besides the fact that it was a class assignment) is to write about my experiences with web analytics, there are no ecommerce purchases or any types of call to action that I need to track. But knowing who visited my About Me page will let me know if the visitor wanted to find out more about me or if they were simply interested in the information I wrote about.

To set up my goal, I followed some simple instructions I found here. I then decided that a proper goal would be three pages/screens per visit. This is because ideally, I would want visitors to get to my page because they Googled a specific topic covered by one of my blog posts. Once they get there and read that post, it would be my hope that they would be intrigued by what they read so much that they would want to know who I am and read my About Me page.  After learning of my credentials, I’d love it they it if they would read at least one other blog post before exiting my site.

What’s great about Google Analytics is that you can assign a monetary value to the conversion. This could help executives determine how much revenue their site is earning for them. However, my site is not revenue-producing so I did not select this option.

I got to verify my goal and found that my conversion rate (based on data from the past seven days) would be 16.67%. Because a goal is sometimes tough but not unattainable, that pretty much confirmed for me that this goal was a good one for now.

Funnels

Next, I’d like to chat a bit about funnels.  A funnel represents the path you expect visitors to take on their way to converting to the goal. Defining these pages allows you to see how frequently visitors abandon goals, and where they go.  Being that my goal is three pages/screens per visit, it would be helpful for me to know where my About Me page fits into the equation, as well as which pages and screens are usually viewed before dropping off. Perhaps these pages/screens are so great that the visitor finds what he or she needs before leaving or maybe they’re so bad that the visitor leaves because they think the site won’t provide them with the information they are looking for.

In looking at my current Visitor Flow, I see that of my 14 visits, 11 dropped off. Of the three that stayed on, two went to visit my post about the comparison between Facebook ads and Google AdWords. All three that stayed on ended up going to my post about Content versus Conversation.  From there, one dropped off. If I had a revenue-producing website, I might consider adding advertisements to the content versus conversation page since most people end up on that page. Since I just added my About Me page, I will need to give it some time to analyze where that page falls into the visitor path before I begin determining what tweaks I need to make in order to reach my goal.

Filters

Lastly, I’d like to discuss filters.  Filters are applied to the information coming into your account, to manipulate the final data in order to provide accurate reports. Google Analytics has three predefined filters. One excludes traffic from a specific domain, such as an ISP or company network.  Another excludes clicks from certain sources, i.e. single IP address, and the last includes only information on a particular subdirectory (for example, www.example.com/motorcycles).

After seeing that my two visits to my own blog were recorded in the Google Analytics information that I wrote about last week, I decided that it would definitely be a good idea for me to block my own IP address. I mean, I visit my site at least once a day, and multiple times any day that I am making tweaks, so it would be unfair to assume that 10 out of 10 visitors were 10 different people when in fact, all or most of them were me. I followed the instructions as outlined by Brad Hogan in his blog and began blocking my own IP address immediately.

I used to manage the content of the corporate site of the company I used to work for. I know that site was visited and used frequently by employees and internal staff. If I were still managing that site, I would definitely block traffic from the company’s entire network. I would also report on traffic from that particular subdomain, though, so I can analyze the company’s own behavior and how the employees interact with that site.