Today on the Analytics & Site Intelligence blog, I’d like to introduce a brand new feature that may change the way you think about your report data.

Raise your hand if you’ve ever sorted by the Bounce Rate column within your Google Analytics account, only to be disappointed with the sheer number of single visit bounce rates at 100%! I know I have. Additionally, have you ever  re-sorted that Bounce Rate column (clicked on the column heading a second time) and saw single visit bounce rates at 0%? How useful was that information?

Last week, the Google Analytics team introduced Weighted Sort, which applies statistical significance to column sorting. Now, when you sort your report table by Bounce Rate (or, any other computed metric, like Goal Conversion rate, Ecommerce Conversion Rate, or %New Visits), you will see a new check box that will appear above the data columns labeled Weighted Sort. When this check box is clicked, your data will no longer be sorted by Bounce Rate (or your computed metric of choice) – your data will now be sorted by its rank, or, its weight (hence the name!)

Let me show you what I mean, visually. First, the image directly below this sentence shows you a cross-section of the All Traffic Sources report, within the Traffic Sources section in Google Analytics. Notice that – by default – the report is sorted in descending order by Visits (symbolized by the downward-pointing arrow):

Instead of viewing my All Traffic Sources report sorted by visits, I want to view the report sorted by Bounce Rate. So in this second image, I have clicked on the Bounce Rate column heading:

As expected, I am seeing 100% Bounce Rate traffic sources with a few visits listed for each – which traditionally has not been very helpful. However, with the new Weighted Sort check box (as shown at the top of the image above), I can tell Google Analytics to disregard the traditional sorting method and apply statistical significance to give me a better read out of how my traffic sources are performing. Now, in the next image, check out the results:

Even though some traffic sources with higher bounce rates are listed higher up within the report table now than other traffic sources, Google Analytics takes the volume of traffic (visits) into consideration with Weighted Sort. You’ll need to force yourself into the habit of looking at the far left of the report table, where the rows are numbered, to know where each item on your report ranks when you use weighted sort. Look at the very left of this last image and you’ll see each row numbered from 1 to however many rows of data your report contains:

Even though I used the All Traffic Sources report as my example for this blog post, you can use virtually any report in Google Analytics and enable Weighted Sort on it (for example, the Keywords report). Weighted Sort should give you a much better perspective as to how your data ranks from a statistical standpoint than the previous column sorting / ranking method that Google Analytics traditionally used.

Google Analytics’ new Weighted Sort feature should help take even more  guesswork out of your day-to-day analysis equation – who doesn’t want that?

We truly, madly, deeply love having multiple options to choose from here at MoreVisibility. So when my colleague Emily MacNair forwarded me a recent post on the Google Webmaster Tools blog about a shiny new option for website owners to verify their websites, my Friday was made!

Website owners can now verify their websites using the new “async” Google Analytics Tracking Code, which makes a website owner’s life a lot easier.

Previous to this announcement, a website owner would need to add a meta tag to their site’s source code, upload an HTML verification file, or add a DNS record to verify a website with Google Webmaster Tools. Now, if the email address that’s used to log-in to Google Webmaster Tools has Administrative Access to a Google Analytics account – AND – the website is using the new “async” Google Analytics Tracking Code, a website can be verified without code-bloating meta tags, extra HTML files or DNS entries.

If you’re an administrator on your Google Analytics account and if you’re using the new “async” code, then all you have to do is click on Verify as shown in the image above.

Thanks to the Google Webmaster Tools team, you now have one additional reason to update to the new “async” Google Analytics tracking code, other than the new code being lighter, faster, and technologically superior to the previous code models.

Go and upgrade today – and verify your website while you’re at it .

We here at the Analytics & Site Intelligence blog at MoreVisibility don’t spend as much time as we should talking about pay-per-click. After all, pay-per-click advertising is a multi-billion dollar industry that’s only getting larger by the click.

Recently, Google AdWords announced a new keyword targeting option for advertisers globally called Modified Broad Match; this announcement coming on the heels of a re-branding effort for their Content Network, which is now called the Google Display Network.

With modified broad match, advertisers can further refine their keyword search audience without having to use phrase or exact match. Regular broad match (or, non-modified broad match) is still the keyword matching option that will allow advertisers to cast the widest possible net on Google search and their partners. Advertisers bidding on a keyword like “brown shoes” using regular broad match will have their ads appear for search queries such as “formal dress shoes”, “men’s brown shoes”, “wingtip shoes for men”, and many other variations. Advertisers who choose to use modified broad match will allow themselves the opportunity to capture misspellings while blocking out possibly irrelevant search queries by inserting a plus-sign symbol in front of every word in the search term the advertiser bids for.

If you have a large number of keywords in your campaigns, inserting a plus-sign symbol in front of every word of every search term would be a monumentally boring and nightmarish task to complete. Since this isn’t your first rodeo, you already know that using Google AdWords Editor saves you time, energy, and lets you make changes across multiple campaigns or ad groups offline without having to toggle between campaigns like you have to do on the live web interface. It’s also a great way to make sweeping changes to your keyword match types, specifically, from broad match to modified broad match.

To show you an example, let’s say that you wanted to make the switch from broad to modified broad, and you wanted to use a plus-sign symbol in front of every word within all of your keywords. First, you’d want to log-in to open AdWords Editor and download recent changes (ALWAYS download recent changes before doing anything in AdWords Editor). Next, click on the keywords tab and highlight all of the keywords using the CTRL + A function on your keyboard.

Next, click on the link at the bottom of the AdWords Editor interface that reads Replace text. This will create a pop-up window like the one in the image below. You’ll want to find the space character (one hit on your keyboard’s space bar) in keywords, and replace it with a space and the plus-sign symbol. Click on Find Matches to update your keywords.

What you should see after you click on Find matches is plus-sign symbols between each word of your keyword. However, you may wonder what you should do about one-word keywords and the first word of every keyword, since those won’t have plus-signs in front of them. For all of those instances (and to fully change all keywords from broad match to modified broad match), click on the Append text link, which is right next to the Replace text link on the bottom of the interface. Then, do what I did in the following image (select “Keywords” and enter in the plus-sign symbol underneath it, while ensuring that you’ve selected Before existing text) and you’ll be good to go:

Of course, don’t forget to click on Post Changes while making sure you select All Campaigns when you’re finished in order to post your changes live to Google AdWords. You wouldn’t want your quick, efficient work to stay offline, would you?

This chart, from the Google AdWords Blog Inside AdWords, visually explains how modified broad match differs from the other match types that are currently available.

Whoa! The title of this blog post should have hit you like a ton of bricks. You see, I’m combining three different sub-industries together:

SEO = Search Engine Optimization
A/B testing = Well…A/B testing! (Like you can do with Google Website Optimizer)
Google Analytics = Web Analytics

Now, how in the world do we do A/B testing on our SEO efforts while using Google Analytics to evaluate the results?

On June 8th of this year, Google rolled out a new search index called Caffeine. This new search index collects and processes information across the web at a much faster rate of speed and accuracy than the previous search index. This means that you can update your website with new content and it is almost immediately indexed and available to be searched for on Google. Website owners who perform frequent updates to their site benefit the most, as Google will pretty much always have the latest version of your website in their search index.

A new search index that instantly updates itself also means that you can perform A/B testing on your organic search results and use a web analytics platform like Google Analytics to determine the rate of success or failure of your experiment. For example, let’s say that you are the owner of HardwareStore.com, and when a person searches for “hardware shop“, they see this organic listing:

As you know from reading our Search Engine Optimization blog over the years, the listings that you see in organic search results derive from the relevant web page’s “meta” tags (specifically, the title tag and the description tag). Before the launch of Google Caffeine, it would be several weeks, sometimes months, for your organic listings to be updated to reflect changes performed on your meta tags. Now, the changes are practically immediate. You can swap out the title and the description meta tags to deliver a different search engine result to your future website visitors who are searching for you on Google. Essentially, you’re running an A/B experiment to see which organic listing produces the best results.

Then what you can do in about one to two weeks after you’ve updated your meta tags is log-in to your web analytics tool and perform a date-range comparison to see what affect your change had on your site performance and task completion metrics, like in this example from Google Analytics:

As you analyze the above image, you can see that the change in your organic listings resulted in higher revenue and a higher conversion rate, which means that you should most likely keep the new meta tags for a while (but keep an eye on that average order value and crunch the numbers to determine if you really are more profitable in the long-term with a lower average order value and per-visit value).

Presto! You’ve successfully performed an A/B experiment with your SEO efforts, while using web analytics to measure the results!

About a year and a half ago, I wrote an article for our monthly newsletter that it “takes a village to raise a culture of web analytics” in an organization. One person – regardless of how motivated and hard-working he or she is – cannot create a culture of analytics and insights alone. It takes people from within your own organization, across organizations, and on your executive team to buy in to the analytics program and truly become an organization which values insights and data analysis.

I postulate that the same culture-driven approach can be applied to your company – no matter how big or how small – to create an environment where testing, experimentation, and optimization come first. As you know from reading our blog over the years, we here at MoreVisibility love Google Website Optimizer, a free A/B and multivariate experimentation tool. With Google Website Optimizer, you can create experiments rather quickly and efficiently and get excellent insights as to how your visitors are reacting to the new pages or new variations that you’re sending their way.

Creating a Google Website Optimizer experiment involves some important people that either work directly for you or that you’ve hired to do work for you (depending on your situation). It also involves six steps – from creating the account to installing the JavaScript snippets to launching your experiment – that you and your fellow colleagues, companies or vendors must participate in to ensure that your Google Website Optimizer experiment is a success.

Today, I’m outlining the six critical steps that need to be taken to successfully create and initiate your Google Website Optimizer experiment. Let’s begin!

Step 1: Deciding What to Test
People Needed: Site Owner, IT / Webmaster, Marketer, Web Analyst, Web Designer
Objective: To come up with a crystal-clear picture of what will be tested (what page, what section, what page is the conversion page) and what type of experiment will be run (A/B or Multivariate).
What You Need to Know: This first step should be a meeting with everyone that will be involved in this process, because it is a team effort. Everyone from the owner of the website to the IT guru should be heard and should have something to say about the upcoming experiment. At this step, you’ll decide on two major things: what you will be testing and what type of experiment you want to run with. If you want to do a simple experiment involving an original page and a variation (or “B” page), then the A/B experiment is your best bet. If you have lots of ideas that you want to test on a single page, go with the multivariate experiment. If you’re not sure, you can’t miss by choosing an A/B experiment.

Step 2: Creating the Necessary Pages or Variations
People Needed: IT / Webmaster, Web Designer, Site Owner
Objective: To actually create and upload the variation pages or variation sections (image and text) to use in the forthcoming experiment.
What You Need to Know: Once everything has been decided on, your web designer will actually create the variation page(s) or variation sections for use in your experiment. Once the web designer has done their work, the site owner should be involved to give the green light on any images or mock-ups to proceed. Once the site owner OK’s the variations, they need to be uploaded to the web server (Google Website Optimizer needs to verify that the variation page(s) exist).

Step 3: Creating the experiment in Google Website Optimizer
People Needed: Web Analyst or Marketer
Objective: Creating the Google Website Optimizer experiment and verifying that the pages to be used are on the web (uploaded to your web server).
What You Need to Know: The person who will be in charge of creating the experiment in Google Website Optimizer, which is almost always the web analyst or the marketing person, will go in and start creating the experiment within Google Website Optimizer. They will enter in the URLs of the original, variation, and conversion pages for verification, and grab the JavaScript snippets for the IT / Webmaster to install.

Step 4: Installing the JavaScript Snippets
People Needed: Web Analyst or Marketer, IT / Webmaster
Objective: Working with the IT department or Webmaster to install and verify the JavaScript snippets on the experiment pages.
What You Need to Know: The IT / Webmaster will follow the on-screen instructions provided by the web analyst or marketer and install the JavaScript snippets that need to be installed on all pages involved in the experiment. They will work with the web analyst or marketer to confirm that this has been done exactly as outlined by Google Website Optimizer.

Step 5: Reviewing the Experiment
People Needed: Web Analyst or Marketer
Objective: To review the entire experiment set-up and preview experiment pages before launch.
What You Need to Know: This is the time to review that everything looks good and that there are no design flaws or broken HTML on the experiment pages. If everything looks okay, the web analyst or marketer will launch the experiment!

Step 6: Launching the Experiment
People Needed: Web Analytics or Marketer, Site Owner
Objective: To activate the Google Website Optimizer experiment!
What You Need to Know: Once the Google Website Optimizer experiment launches, it’s important that the owner of the website is made aware that some visitors to his or her site will start to experience different variations of the site. It’s also important to let the experiment run its course naturally (without influencing it by making changes to the web pages involved in the experiment). After a few weeks, everyone on the Google Website Optimizer experiment team should meet and review the report data that the web analyst and marketer will love to analyze and derive insight from.

By following these six steps with the members of your organization, you are destined to succeed, while at the same time, creating a new culture of optimization and experimentation in your company!