When people come to your site from a search engine, the search engine tells you what term people came from through the referring string. Your Web analytics tools uses the referring string to determine how visitors found your site. This can be very helpful to understand what people are searching for, how they ultimately find you, and so on. You have a lot more flexibility when using paid search in terms of what you can pass into your Web analytics tool, but with organic search you are really limited to what the search engines pass you.
Recently, though, Google recently made a change to the referring string. Brett Crosby, a group product marketing manager on the Google Analytics team, wrote a post detailing how a new referring URL format will be rolling out in the coming days. He describes the change in the referring URL format with the example of someone searching on "flowers," then clicking to your site from the Google search results page:
Before the change, the referring URL looks like this:
With the change, the referring URL will now look like this:
A few key things to note in Crosby's post about changes to the referring URL string:
Look again at the new referring URL above. The "cd=" parameter in the string is what's interesting. It can change the way you analyze and understand your organic search and identify opportunities to improve your SEO (define) and maximize your search impact.
After some speculation, Google confirmed it is now passing ranking data (using the "cd=" parameter) through the referring string. Now this might not seem like a big deal, but it has considerable implications in terms of analyzing and understanding the impact of your SEO ranking and how that traffic performs on your site. Does a number-one ranking drive much more traffic? Does a number-two ranking drive more traffic that converts? Or does a number-four ranking drive the highest average order value? Getting this granular view can help search and Web analytics professionals maximize their understanding of their organic search listings' effectiveness and those different spots' effectiveness on site performance.
So instead of looking at how a term like "flowers" converted people on your site, you will be able to understand how "flowers" performs when you are the top organic results versus the sixth organic result. Or 20th organic result. You could also look across all your search referring terms to see how all the number-three rankings are doing compared to the numbers four, five, and six.
Recently I spoke with Rich Devine, our agency's director of search marketing, on this latest development and its potential impact for online marketers.
Jason Burby: How significant is this change for SEO professionals?
Rich Devine: Immensely significant. It allows for more efficient and accurate keyword research and targeting, as well as being able to precisely estimate and measure the monetized impact and performance of individual keyword optimization efforts.
JB: Can't you already see what SERP (define) people are referred from?
RD: Yes, currently Google passes the keyword and SERP page (page 1, 2, 3, etc.). Page number, however, is not that helpful for us because the difference in performance value between rank position one and rank position seven on the first page is too wide. It's like comparing LeBron James to Adam Morrison [backup forward for the Los Angeles Lakers]. Yes, they both play in the NBA, but LeBron scores 28 a game and Morrison scores 4 points a game. They don't belong in the same conversation.
JB: How would you use this type of information?
RD: With specified rank data, we can accurately tie individual keyword rank to individual keyword performance. This is huge for assessing current keyword value and informing opportunity targets for keyword improvement.
If I focus on optimizing a referring term that generated $500 per month in revenue at rank position five, increased that term's position to rank position three, and saw monthly revenue jump to $2,500 per month, that's a 500 percent performance increase. Imagine being able to aggregate rank improvements across a site. On average, how big is the performance jump between positions five and three for my site? How big is the historic performance between positions three and one? If I tie rank potential to monetized site performance, I can prioritize my optimization efforts based what will likely bring the greatest ROI. It allows me to focus and prioritize my efforts on LeBron-performing keywords, so that I don't waste my time on Morrison keywords.
After our interview, Devine shared with me that smart SEO professionals already do this to some extent. But to date, they must use educated guesses and match their own ranking data with blunt keyword analytics data. He concluded, "But if Google wants to validate our optimization efforts and provide precise measurement potential at the keyword level, I'm all for that and it will make an impact on maximizing search ROI."
So there are clearly going to be ways to leverage this new information. Start by talking with your search team about getting more extensive analysis in place to begin to identify the opportunities. In addition, talk to your Web analytics team about segmenting analysis based on this to see if you can find any opportunities for a better understanding of what truly impacts your conversion. Both ideas have the potential to make you more effective online and maximize your site ROI.
Join us for a one-day Online Marketing Summit in a city near you from May 5, 2009, to July 1, 2009. Choose from one of 11 one-day events designed to help interactive marketers do their jobs more effectively. All sessions are new this year and cover such topics as social media, e-mail marketing, search, and integrated marketing. Register 30 days in advance and get a $40 discount!
Know your Ambiguous Customer: Effective Multi-Channel Tracking
Wednesday, June 5 at 1pm ET - Learn why a move from the "batch and blast" email approach enables better conversations with your customers.
Register today - don't miss this free webinar!
As the Chief Performance Marketing Officer for POSSIBLE, Jason supports the agency's global Marketing Sciences and Media Services programs.
His primary role is to help POSSIBLE teams and clients use data to craft digital strategies that attract, convert, and retain customers - maximizing ongoing ROI across paid, earned, and owned channels. He believes that brands can better serve their customers by understanding audience behavior, and that messaging should be targeted to individual customers through the use of testing, behavioral targeting, and CRM initiatives.
Jason has written extensively about digital analytics, optimization and digital strategy, including an ongoing column at ClickZ.com. He is the co-author of "Actionable Web Analytics: Using Data to Make Smart Business Decisions," which is one of the leading texts in the field of digital analytics. His client roster includes Microsoft, Nike, Nokia, Dell, Ford, Sony, PayPal/eBay, P&G, Alcoa, Expedia, Mazda, Intel, and Motorola, and more. Jason is a frequent speaker at conferences and seminars around the world ranging from the Cannes Lions, Adobe Omniture Summits, eMetrics, SES, ad:tech, BazaarVoice, and many other WPP events.
Follow him on Twitter @JasonBurby.
June 5, 2013
1:00pm ET / 10:00am PT
June 20, 2013
1:00pm ET / 10:00am PT