Referrers: Where did you come from?

As important as it is to measure the number of people that come to a Web site, it’s also important to analyze how people get to a Web site.  Customers may use a direct URL to get to the site, search based on product or service keywords, or click an ad or link in the company’s marketing materials.  All of these channels are called Referrers.  When looking at Web metrics, a Referrer is a term used to describe the source of traffic to a visit or page (Reed College of Media, 2015).

According to Kaushik (2010) analyzing Referrers can show which Web sites are contributing to site traffic, which marketing initiatives are the most successful, and which keywords most reflect the content on the site.  Kaushik (2010b) also gives insight into several other types of Referrers.

“Internal Referrer: The internal referrer is a page URL that is internal to the website or a web-property within the website as defined by the user.

External Referrer: The external referrer is a page URL where the traffic is external or outside of the website or a web-property defined by the user.

Search Referrer: The search referrer is an internal or external referrer for which the URL has been generated by a search function.

Visit Referrer: The visit referrer is the first referrer in a session, whether internal, external or null.

Original Referrer: The original referrer is the first referrer in a visitor's first session, whether internal, external or null.”

Blue Martini & Debenhams

Debenhams, a British Department Store, was looking to improve the e-commerce experience on their site.  They wanted to increase the number of registered customers, increase daily transactions, and increase the average basket size on a yearly basis.  They launched a new web site powered by Blue Martini Software in 2001. 

The improvement process for the Debenhams site included evaluating which cost-per-click (CPC) relationships were the most beneficial.  Looking at referral percentages and referral purchase amounts, Debenhams was able to quickly asses how to capitalize on each relationship.  Learning that one portal provided a small percentage of visits, but a higher conversion rate than any other site, Debenhams was able to better understand where to spend their advertising dollars.

In addition to looking at which CPC relationships were the most valuable; Debenhams analyzed a detailed list of keywords that drove traffic to their site.  This assisted in the strategy development of paid ads based on keywords (Blue Martini Software, 2002).

As mentioned in the Debenhams example, Referrers can help Web site managers better understand which portals and relationships are the most beneficial for a company’s Web site.  As with all Web metrics, it’s important that Referrers isn’t regarded as the sole metric that signifies success.  A company must outline their goals for what they want a customer to do when they get to the site.  For example, a Referrer can drive a lot of traffic to the site, but if Conversion Rates and Time Spent on Page are low, or the Bounce Rate is high, that Referrer might not be very valuable.  The advertising dollars spent on that Referrer might be better spent elsewhere.

References:

Blue Martini Software, (2002) Blue Martini Business Intelligence delivers unparalleled insight into user behavior at the Debenhams Web site. Retrieved January 19, 2015 from http://ai.stanford.edu/~ronnyk/debenhams_Study.pdf

Kaushik, A. (2010). Web analytics 2.0: The art of online accountability & science of customer centricity. Indianapolis, IN: Wiley Publishing. ISBN# 978-0470529393

Kaushik, A. (2010b, April 19). Web analytics 101: Definitions: Goals, metrics, KPIs, dimensions, targets. Occam’s Razor Blog. Retrieved on March 25, 2012 from http://www.kaushik.net/avinash/web-analytics-101-definitions-goals-metrics-kpis-dimensions-targets/.

Reed College of Media, WVU. (2015). Lesson 2: Basic Web Analytics. [login required]. Retrieved from: https://ecampus.wvu.edu/

Bounce Rate: Why are you leaving so soon?

In the wonderful world of Web metrics, Bounce Rate is considered an engagement metric that shows the “percentage of sessions on your website with only one page view” (Kaushik, 2010).  This metric is valuable in that it is included in many analytic sites, it is actionable on multiple levels, and it measures customer behavior (Kaushik, 2010).

Bounce Rate should be measured in two ways.

1. The overall rate of the entire site
2. Top landing pages

Measuring the Bounce Rate of both of these areas will help determine which pages are leading people away from the site and not further into it.  A company’s landing page is not necessarily their homepage.  This page could be any page that signifies the beginning of a visit.  In essence, it could be any page on a Web site as long as that is the first page a customer sees. 

Landing pages may be the first impression a company provides to the viewer.  If a customer clicks on a Facebook link for women’s yoga apparel, they may be taken directly to the women’s section of the Web site and not the homepage.  If that is the first page a customer sees, the company needs to make sure that the content, navigation, and action items are easy for the customer to navigate.  If not, they’ll leave the page without looking for more content and will most likely not make a purchase.

According to Kissmetrics.com (n.d.), the average bounce rate for a Web site is 40.5% but varies based on the industry.  Similarly, the average Bounce Rate for blogs is 40%-50% (Shafee, 2013).  The James R. Connor University Center at UW-Whitewater used this metric, in addition to time on page, to help determine the success of their blog and make adjustments to the layout and content provided.

James R. Connor University Center Blog

This student union blog is almost entirely student managed and produced.  A team of 10 students from departments across the organization post content between two and four times per weeks.  The blog topics stem from events and connections to the University Center (including two University Center related series posts) however; writers have creative room to write about topics that are important to students on campus.  This content generation process creates diverse topics that may only apply to targeted demographics on campus.

Each week, the team looks at the Web metrics for the site to evaluate the successfulness of their content. The team expects a higher Bounce Rate based on the nature of their content, but balance that metric with Time on Page to determine success.  Based on the information provided, the team can gather that their content is being consumed by visitors that arrive via a direct link (Facebook, Twitter, etc.), but viewers are not engaging with additional content on the site. 

The team was also able to see that the “authors” page of the site was one of the most viewed.  Before beginning the Spring 2015 semester, a side bar was added to all of the pages that featured not only the most recent posts, but also content organized by author.  It is the team’s hope that offering this additional information will lower the Bounce Rate of the overall site.

Bounce Rate is a metric that provides essential information about user engagement, but cannot be measured in isolation.  Determining Web goals is essential to defining success and should be measure across multiple metrics.

References:

Kaushik, A. (2010). Web analytics 2.0: The art of online accountability & science of customer centricity. Indianapolis, IN: Wiley Publishing. ISBN# 978-0470529393

Kissmetrics.com (n.d.) Bounce rate demystified. Retrieved January 19, 2015 from https://blog.kissmetrics.com/bounce-rate/

Shaffee, A., (2013, December 16) What is the average bounce rate for blogs. Retrieved from http://www.bloggingspell.com/average-bounce-rate/