So tonight, I’d like to talk about what web analytics is, and why we should track metrics on our sites. I’d also like to show you some of the things, outside of tracking page views, that you can do with web analytics. Finally, I’d like to share some of my experience with web analytics as it pertains with sites that I’ve been involved with.
Web Analytics is the study of the online experience of a web site for the sole purpose of improving it. On the screen, I’ve provided a quote from Eric Peterson, the guru of web analytics.
So why analyize?
To prove that the business goals for building the site are being met.
“We built it … did they come?”
“Is the site performing as expected?”
Understanding Site Visitors
How did they find the site?
How many times did they visit the site during a period of time?
How many pages do they view during a visit? What pages?
Do they do what we want them to? Fill out forms? Download PDFs?
Why do site visitors leave the site?
Identifying Opportunities
Search terms used to find site & content
Site visitors looking for content not found
All this, to improve the site for ultimate performance.
Different information sources can be used to improve your site:
Web Traffic Data: server logs and page tag data
Web transaction data: Data form an e-commerce system or CRM back-end system.
Web server performance data: useful for server support staff to determine performance and bandwidth issues.
Phone / Call Center activity: Data obtained through human-to-human interaction with a call center representative.
Usability Studies: Can provide data on usability, accessibility and user experience issues and opportunities.
User Submitted information: User submitted information from Feedback forms can provide information on system and perception issues.
There are two methods for obtaining web data:
Web Server Log data: Data obtained from your web server can be parsed by client-side software to make the data meaningful.
Page Tag data: JavaScript code placed on each tracked page provides in-depth information about the page and the client’s browser device.
More information on the various vendors and software can be found in Appendix A of this presentation.
Web server logs record various information from each request made to the server.
Page tag-based web analytic systems obtain similar data as server logs. Additionally, they obtain information about the client’s browser, operating system, custom IDs and tags, as well as conversion data, unattainable from server logs.
Now both of these methods have their pros & cons. (See screen)
So what’s the perfect solution? Sorry, but there isn’t a perfect, accurate solution.
So how should web owners and designers properly analyze and track their websites?
Especially if you have a financial or accounting background, please don’t try to “balance the books.” Each method and even most data points have their weaknesses when it comes to solid accuracy. So instead, use the numbers to view trends, over a period of time. If you have the resources and inclination, you also might consider leveraging both server log data and page tag data to integrate into a hybrid approach.
On this screen, we look at a diagram that shows how the value of the data obtained increases as the data becomes more unique.
The core metrics obtained through web analytics are
Hits
Page Views
Visits
Unique Visitors
Uniquely Identified Visitors
A hit represents a request to a web server.
If you think of it, a web page may create several hits to a web server. One for the web page, other requests for each image on the page, any includes, etc. Therefore, a web page that contains 6 images would create 7 hits to a web server. So except for the needs of server support staff, this metric provides no business value.
The Page View metric represents the number of times a web page, be it static, or dynamic, has been displayed. It is useful for determining the popularity of select content.
A Visit (or session as WebTrends refers to is) is represented by activity during a period of time (usually 30 minutes) that takes place on a website.
Visitors are one of the most unique metrics used in web analytics. By default, a visitor is represented by an IP address or a cookie. Uniquely identified visitors are cross referenced by another back-end system, usually an e-commerce or CRM system.
Other metrics that can aid businesses and web design are bounce rates, referrers, client technical stats and conversions.
A bounce represents when a visitor arrives on a web page, then immediately navigates back in history (likely via the browser back button) or leave the site entirely.
When site visitors bounce from a page, it usually means that they did not receive what they expected from the page. Visitors usually either hit the back button or leave the site entirely.
Referrers are important in determining where your site visitors are coming from, how they found your site, etc.
Web analytic software, specifically page tagging systems, provide lots of details on the client and it’s environment. This is valuable in designing for the most optimal situation.
For instance, if your site is designed for a fixed 800x600 width, and most visitors are viewing your site with monitors at a resolution of 1200x800, you might consider a redesign to take better advantage of the extra screen width of your audience.
For most organizations and businesses looking to gain something from being online, whether it be financial or otherwise, the most important online goal are conversions.
Key Performance Indicators (KPIs) are the core of web analytics. KPIs are used to determine the successfulness of an online presence.
Here’s an example from Best Buy that illustrates what KPIs are and how they are used.
For the remainder of this presentation, I’d like to look at a few Case Studies, experiences I’ve had in using web analytics.
In the case studies, we’ll cover:
Tracking conversions
Tracking e-mail campaigns through to conversion on the website using parameters.
How web analytics can be used to impact web site redesign and search engine optimization efforts.
For the first case study, we’ll take a look at how I implement basic conversion tracking on a client site using Google Analytics.
The client’s business goal was to increase the number of leads they were receiving from the website. To take any action, we had to measure what we had currently to know if things were improving.
The page flow for inquiries on the client site is as follows:
Visitors arrive on a product page. They click on the inquiry button.
The inquiry form is presented. The site visitor completes the inquiry form and clicks the submit button.
The site displays a confirmation page, which generates a confirmation email behind the scenes.
So in Google Analytics, we’ll create a ”Goal” to track this conversion.
On the Goal page, we enter the goal information.
Active Goal: Yes
Match Type: Exact (Note: there are times when the Match type may not be exact due to parameters)
Goal Page: For this demonstration, our confirmation page is our goal page. The confirmation page designates that the conversion is completed.
Goal Name: A unique, descriptive goal name.
Case sensitive: For this demonstration, since the site is on a Windows server, there’s no need to check this option.
We’re now presented with a page that allows us to enter each page of our conversion process. For this demonstration, we’ll just have the inquiry form followed by the confirmation page. However, other sites, specifically e-commerce site, like Amazon, might have several pages that make up the conversion process (Shopping cart, Shipping info, Credit Card info, Verification, Confirmation).
After receive some traffic, the report will be populated with data.
However, if you take a closer look, there’s an obvious problem. The abandonment rate for our inquiry form is just over 75%. To get a better idea at where the problem might be, we’ll take a look at the Conversion Funnel.
What is a Conversion Funnel?
In a process, many people enter, while only a few finish. Obviously, the goal is to have as many site visitors complete the conversion process as possible.
Google Analytics shows us the Conversion Funnel, the pages that referred site visitors to the Conversion Funnel, and the pages site visitors went to when they left.
My client leverages email marketing as a channel to market her travel products.
While the email service provides metrics around the email distributions (sent, opens, clicks, etc.), it doesn’t provide any information on what recipient do once they navigate to the website from the email. The email service has metrics, the website has Google Analytics, but how to bridge the two?
Google Analytics offers custom parameters / variables that allow you to track data from other sources, like non-Google Adwords ad campaigns.
Google provides an easy way to create the tracking URL strings.
On this screen, an example link is displayed, with its HTML code.
The email code to display the link (starting with the <SimpleURLProperty> tag) contains parameters repeating the URL and the link label. You’ll notice the link’s parameters (in green) contains the Google Analytic parameters created form the Google Analytic URL tool.
Once the email has been distributed, the email program displays the current metrics.
In Google Analytics, the email campaign information, as it relates to web site activity, is displayed.
The insight that web analytics provides is perfect when planning for web design or a web re-design project.
Current popular pages is useful for determine what content is popular & relevant, and what content isn’t.
Many analytics tools provide a site overlay feature, which places the clickthrough counts on each link. This is helpful in determining which navigation methods work for your site.
Keyword research is paramount when optimizing a site for the search engines. Being able to see which keywords are currently being used to access a site’s content is valuable insight.
Finding out where your traffic is coming from is helpful for planning future link strategies.
Finding out where your traffic is coming from is helpful for planning future link strategies.
If you’re managing search engine paid ad campaigns, being able to see how the traffic converts is valuable.
In summary;
Use web analytics to provide the insight needs to make smart design choices.
Follow the web analytics methodology.
Make sure to act upon the results of web analytics.