Goals and Funnels and Filters – Oh My!

Last week, I wrote about a variety of metrics I looked at to determine the effectiveness of my blog – such as recency, bounce rate, referrers, traffic and time spent on page, to name a few – given its eight unique visitors. While that analysis was interesting, I know it was very limited given the low number of individuals who are visiting my blog. However, I’m happy to report that my blog has picked up another five unique visitors in the past week for a total of 13 and that, while I know I have a long way to go, growth in unique visitors does give me hope I’m going in the right direction.

This week, I’m going to look at some of the reports and features I’m didn’t address last week – specifically goals, funnels and filters – and talk about how I am starting to use them. I’m also going to discuss the actionable insights I can gain from the data collected using these traffic parameters.

Goals

Google Analytics (GA) allows me to set up 20 goals for my blog. As P.I. Reed (Lesson 6, para. 2) explains, a “goal is a Web site page that helps generate conversions for your site (with some extra code, they can even be file downloads or on-page actions).”

With blog objectives of thought leadership and interesting content, I’ve decided to set three goals:

Visit duration. My first goal focuses on boosting average visit duration from 3.08 to 3.5 minutes. The reason I’ve chosen this visit characterization metric is because it offers insight into how long my visitors are spending with my blog during each session. If I’m providing interesting and relevant content, I should be able to increase the amount of time my visitors spend with my blog. As of the time I posted this blog, I had no completions for this goal.

Page Views/Visits. My second goal is to increase the number of page views/visit from 2.61 to 3 or greater. This visit characterization metric allows me to see how many pages my visitors are viewing during each visit, which gives me an idea of how engaged they are with my site (P.I. Reed, 2013, Lesson 6). I’m particularly interested in this metric since my hope is that my visitors will visit more than one page, finding my content engaging and interesting. It will be interesting to see if I’m able to tie this goal to new versus returning visitors when analyzing my data next week. Again when I posted this blog, I had no completion information to share related to this goal.

Share/Social Connect. To boost visitors to my blog, I’ve selected share/social connect as another goal. This engagement metric allows me to see how many of my visitors find my content interesting and relevant enough to share, helping me determine if my objective to establish myself as a thought leader is working. Presently, I have achieved three goal completions as of the time I posted this blog, yielding a goal conversion rate, which is sum of the conversion rate for my three goals, of 7.14 percent.

It’s important to note that goals also allow you to set a dollar value for each conversion. While Google Analytics (2013) strongly suggests using this feature for all visitor interactions, I wasn’t sure what “values” to place on each of my three goals, given my overall blog objectives of thought leadership and relevant content. If you have suggestions on how I might assign a monetary value to my goals, or have read good articles about how to do this, please share.

Funnels

Funnels, according to GA (2013), will allow me to look at the paths my visitors take on their way to my conversion goals, which I’ve established as sharing social content, page views/visit and visit duration.

Funnels can provide very useful information. Since I have no information in my funnels reporting section at the present moment, I decided to speak with my employer’s digital media specialist, Brian Donohue, to get a better understanding of how funnels can be used by businesses.

Where I work, Donohue uses an e-commerce conversion funnel for the company’s individual dental product. The ultimate goal, he explains, is to realize a sale of the product. There are several steps involved in the conversion process – demographic information, comparing and selecting a plan, proceed to checkout, creating an account, and payment/enroll.

By setting up a funnel that follows a visitor through each part of this process, Donohue (2013) says he can look at three things:

• What steps in the company’s conversion process are giving customers the most trouble
• What copy/language might be contributing to the customer’s decision to continue or leave
• What technical issues might exist that make it difficult for the customer to complete the conversion

The funnel, he says, allows him to see how customers are interacting with the company’s various channels, such as social email and organic search, as well as help him optimize marketing efforts to increase conversions.

To further enhance my understanding of how funnels can help me measure the effectiveness of my blog (so when I have data available I can best interpret it), I viewed a useful video from Google (2011) that explained how funnels are a lot like a basketball game – it takes more than one player, or channel, to secure a goal, or conversion. And each part of a funnel helps provide the information needed to show how each player (or channel) is, or isn’t doing, its part in securing a goal (or conversion).

Filters

According to P.I. Reed (Lesson 6, 2013), filters can be applied to the information in my GA account, allowing me to manipulate the data to enhance accuracy of reporting. Specifically, GA (2013) allows me to set predefined or customized filters.

Predefined filters include the ability to exclude/include information from specific domains and an IP address, and to a particular subdirectory,(Google Analytics, 2013). Google Analytics (2013) also offers five customizable filter types: exclude, include, lowercase/uppercase, search and replace, and advanced. Each of these filter types performs a specific purpose as outlined below:

Since I presently am not using filters for my blog, I spoke with Donohue to find out how he uses filters. He (2013) explains one of the pre-defined filters he uses regularly is to exclude traffic from the company’s IP address. By using this predefined filter, he can rule out data from employees looking for information to use in their jobs that can skew effective measurement of goals and conversions. Last year, Donohue also set up two filters specifically  designed to collect information on mobile and tablet technologies. By using these filters, he was able to see how many visitors were using mobile phones or tablets to visit the company’s website and make the case for responsive design.

Donohue (2013) emphasizes that if you use filters, it is always wise to maintain a profile with unfiltered data because once the data has been processed you cannot go back to the raw information.

Conclusion

Based on the above information, goals and conversions are the reports that will provide me with the most actionable information from my blog – information that is crucial in helping me understand if my blog is reaching its objectives – thought leadership and relevant content. If I achieve my three goals, I can gleam information about what should be repeated or enhanced in the future. If I miss my goals, then I will have information about what might need fixed, changed, or enhanced to increase the effectiveness of my blog, moving forward.

As for filters, I might want to consider setting up filters that allow me to look at information for only those visitors who come to my blog via social media channels, or to exclude all visitors who come from my place of employment.

Over the next week, I’d appreciate your help is driving some traffic to my blog so I can better understand how all elements are working – or not working – in helping me reach my goals,  so please consider sharing via Facebook; emailing my blog to a friend; or tweeting about it. And if you have suggestions for other goals or filters I should set up, I’d love to hear from you.

References

Donohue, Brian. (2013). How to use funnels and filters. In-person interview on Nov. 27, 2013.

Google Analytics. (2013). Beth’s blog. Retrieved Nov. 29, 2013, from https://www.google.com/analytics/web/?hl=en#report/visitors-overview/a45647041w76369387p78959657/

Perley Isaac Reed School of Journalism, West Virginia University. (2013). Lesson 2: Web Metrics & SEO. Retrieved Oct. 28, 2013, from WVU eCampus Web site: http://ecampus.wvu.edu

YouTube. (2011). Multi-Chanel Funnels in Google Analytics. Retrieved Nov. 29, 2013, from http://www.youtube.com/watch?v=Cz4yHOKE5j8