Joost de Valk is a seasoned online marketer who specializes in Web Development and SEO. Joost frequently contributes to his blog Yoast.com, and is co-host of the weekly WordPress "blog improvement" podcast WP-Community.

Jump to: Joost's Analytics Hack

Will Critchlow is the Founder and Chief Strategist of Distilled Internet Marketing London. You can find a myriad of Will's best Google Analytics Hacks here and you can also sign up for an in-depth enterprise analytics conference call.

Jump to: Will's Analytics Hack

Vanessa Fox is a SEO expert and consultant best known for creating Google Webmaster Central. She writes on customer acquisition via organic search at ninebyblue.com, provides search-friendly design patterns at janeandrobot.com and is the author of Marketing in the Age of Google: Your Online Strategy IS Your Business Strategy.

Jump to: Vanessa's Analytics Tips

Ian Lurie is CEO of Portent Interactive, a Seattle-based Internet marketing and search engine optimization firm. He also writes the Internet marketing blog Conversation Marketing, and is co-author of the Web Marketing All-In-One Desk Reference for Dummies.

Jump to: Ian's Analytics Hacks

Larry Kim is Founder and VP of Product Development at WordStream, a provider of PPC management software and SEO tools for inbound marketing efforts.

 Jump to: Larry's Analytics Tip

John Hossack is President/CEO at VKI Studios and is a frequent speaker at speaking at events, such as the American Marketing Association, Web Analytics Association, eMetrics conference, Internet Marketing Conference Vancouver as event Chair and speaker.

Jump to: John's Analytics Hack

Justin Cutroni is the Director of Digital intelligence for WebShare, an online marketing firm in Phoenix, and has written two books: Google Analytics (for advanced GA users) and Performance Marketing with Google Analytics (for more novice GA users). Justin also blogs at Analytics Talk.

Jump to: Justin's Analytics Hacks

Manoj Jasra is a Web Analytics Analyst and President of Jasra, Inc and the Senior Search Marketing Strategist at Shaw Communications. Manoj also runs the popular Web Analytics World blog and recently launched a kids iPad app called Josh & Emma.

Jump to: Manoj's Analytics Hacks

Bas van den Beld is a Web strategist, international search specialist, trainer and respected blogger. He owns Stateofsearch.com, with news and views on what's next in search. He also owns NetTraject, a Dutch search engine marketing company, and founded Searchcowboys.com.

Jump to: Bas's Analytics Tips

Joost de Valk

Advanced Data Tracking

- If you haven't yet, switch to the new asynchronous tracking. It's faster & more reliable, so there's simply no reason not too.

- If you use Google Analytics on a  WordPress site, use Yoast's Google Analytics for WordPress plugin, it allows you to track loads of meta data and the only thing you'll have to do is authenticate with Google and select the right site to track.

- Using the new custom variables functionality you can track very interesting meta data. For instance, you could track the age of pages as a custom var on the page level. That way you can see whether older pages are still receiving traffic. Or you could use the custom variable to track the author of pages, that way you can segment by author and see which authors do better in search, for instance.  An example of how this works with the asynchronous tracking code:

var _gaq = _gaq || [];
_gaq.push(['_setAccount','UA-12345-1']);
_gaq.push(['_setCustomVar',1,'author','joost-de-valk',3],['_trackPageview']);
(function() {
    var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
    ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
    var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
})();
 

Will Critchlow

How to do First Touch Tracking

By adding some custom JS code to write information about referrer, landing page etc. to custom variables only on the first visit, we can run conversion/e-commerce reports by first touch instead of last touch. This means that rather than seeing all conversions allocated to direct visits, email and branded search, we can see the long-tail unbranded searches that led searchers to discover the site in the first place. Both these views have their place, but this is the first step on the road to econometric models (massively overkill for most SMEs).

The main point can be summed up by the chart below showing the visits to convert report from Google Analytics:

The point is not what those exact values are, but simply that a significant number (in this case more than half) of all conversions come from visits that aren’t the first!

Today’s post, however, is all about the details: how to get first touch tracking working to get you actionable data about real acquisition costs from Google Analytics.

You will need to be able to:

• Import a custom .js file
• Modify the Google Analytics embed code across your website
• Create custom reports in GA

Note that this is going to set custom variables. If you are already using this functionality, you should be very careful with how you integrate this. Oh, and all of this is provided as is, with no warranty. I hope it will help you out, but only you are responsible for changes you make to your website and tracking code.

By default, GA attributes conversions to the last touch – i.e. the source of the visit that led to the conversion. I’m going to show you how to get the source of their first visit to your site.

Step 1

Embed a JavaScript file defining three functions:

• distilledCheckAnalyticsCookie – in order to track first touch information, we only want to record details to custom variables on someone’s first visit. This function checks for the __utma visitor cookie
• distilledTruncate – as I discuss in more detail over on SearchEngineLand, Google won’t allow you to set custom variables of longer than 64 characters (including the variable name) after URL encoding so this function is a slightly long way round of truncating the variable information
• distilledFirstTouch – the heavy lifting – this is the function that sets the four variables outlined in more detail below

You can embed this with the following code anywhere above the Google Analytics code script in your page code:

<script type="text/javascript" src="http://attributiontrackingga.googlecode.com /svn/trunk/distilled.FirstTouch.js"></script>

It’s a little clunky at the moment and I want to refine it a little to cope better with combinations of Google Analytics and Website Optimizer. If anyone has any good ideas for this, feel free to drop me a line or raise issues over at Google Code.

Step 2

Move your GA code above any Website Optimizer code or anything from Google that might write a visitor (__utma) cookie and look for:

var pageTracker = _gat._getTracker("UA-XXXXXXX-X"); pageTracker._trackPageview();

In between those two lines, you want to put the following code:

distilledFirstTouch(pageTracker);

So that your trackpageview code looks like this:

var pageTracker = _gat._getTracker("UA-XXXXXXX-X"); // Distilled first touch tracking distilledFirstTouch(pageTracker); pageTracker._trackPageview();

Make sure you use your own UA-XXXXXXX-X identifier string!

This writes 4 custom variables (apologies for the ridiculous naming conventions – Google limits the whole of the variable name + value to 64 characters!):

• l : original landing page (no query string)
• s : original landing page query string
• r : original referrer
• q : if q=keyword+keyword is found, this contains that part of the referrer (it’s actually more complicated than that – I have taken the full list of keyword delimiters from Google help and attempted to pull them out into the fourth variable in case the full referrer is truncated by the character limit).

Step 3

The detail of this is probably best reserved for another day / another post, but suffice it to say that I have found that custom reports exported to Excel are probably the best way of analysing the data this method produces. Far be it from me to tell you what reports to create, but I suggest something like conversions or revenue by original referring keywords might be interesting!

I have found the Visitors –> Custom Variables report in GA to be flaky at best. I would advise avoiding that and creating your own reports.

Step 4

Work a tiny bit of Excel magic.

Because (as described above) Google encodes the data on the way into GA, you need to decode it to make real sense of it. I have made the assumption that Google’s URLEncode function works like JavaScript’s encodeURIComponent() function and written an Excel formula to help:

=SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(SUBSTITUTE(A1," ;%2F","/"), "%2C", ","), "%3F", "?"), "%3A", ":"), "%40", "@"), "%26", "&"), "%3D", "="), "%2B", "+"), "%24", "$"), "%23", "#")

Just paste this formula into an empty cell and place the information you want to decode into cell A1. Manipulate as necessary. You’re welcome. And yes, I’m a (tiny bit) sorry for the nastiness of that formula.

original source

Vanessa Fox

Link Building via Referred Links, Segmenting Analytics through Keyword Clusters

Two questions I get asked all the time are about measuring link building efforts and monitoring organic search rankings. I point people to their web analytics for answers to both of these questions.

For link building, content owners want to know how successful their efforts have been to create compelling content that others will link to and they want to know if the links they are attracting are seen as valuable by Google and help to improve their PageRank. The link reporting tools that exist can be out-of-date, inaccurate, incomplete, or report links from different sections of the web with each update. Because of these issues, it's difficult to use these tools for this type of monitoring. Even Google Webmaster Tools, which provides link data directly from the source, doesn't provide a complete list of incoming links.

However, you can use the referring link information in analytics to learn which content is attracting the most links and which of those links are bringing you the most traffic. This information will both help measure how well your efforts to create compelling content are going as well as gain insight on how valuable search engines such as Google likely see those incoming links.

For search rankings, rankings reports with hundreds or thousands of keywords are not only against Google's terms of service, but are increasingly inaccurate and not highly actionable. Personalized search means that each searcher sees a different set of results, and universal search elements such as images, video, and the local onebox make it difficult to translate an organic ranking into where that result falls on the page and what percentage of clicks it's likely to get. In addition, a mere ranking doesn't tell you if searchers are clicking through to your page and converting.

However, you can create analytics reports by keyword cluster to find out if you're gaining or losing search traffic for those keywords and better understand the behavior of those searchers on your site. For instance, if you sell rubber duckies, you can set up reports to see how well the site performs for those searching for yellow vs. other color duckies, those searching to rubber duckies vs. those looking for reviews and those looking for particularly functionality, such as the ability to float.

That type of data not only gives you much of the same insight you'd get from rankings reports, but it provides information that's much more useful and actionable. Do those who look for blue rubber duckies never buy? Are lots of people looking for green rubber duckies but you don't sell them? Clustering keywords and tracking visitor behavior can help you not only measure your organic search efforts, but can help improve your overall product strategy.

Ian Lurie

Google Analytics Cheatsheet

Google Analytics has a ton of features, and even more tricks and hacks that folks have developed over the years. So this two-page cheat sheet, which took three days and nights to pull together, is a tiny sliver of the whole system.

But it does cover the stuff that I'd want my staff to use.
 

Download it free:

• Version with links: The Google Analytics Cheatsheet
• Printer-friendly version: The Google Analytics Cheatsheet, Printer Friendly

original source

Larry Kim

How to Track Outbound Clicks

One of my favorite Google Analytic hacks is to help me track clicks on links that lead visitors away from my website. Links that lead away from your site are not automatically tracked in Google Analytics so to track this activity you need to tag links you want to track with som custom Javascript. I'll walk you through the steps.

1) Set up Event Tracking in your Analytics Tracking code.

You're going to add the following line to the tracking code for your pages after the page tracking object is set up:

    var pageTracker = _gat._getTracker('UA-XXXXX-X');
    pageTracker._trackPageview();

2) Add JavaScript in the <head> of your document to delay the outbound click.

Not to worry...this delay is only a fraction of a second and will hardly be noticeable by the user. But the delay does provide the browser more time load the tracking code. Without this delay, the user may click on the outgoing link before the tracking code loads, in which case the event isn't going to get recorded. Here's the JavaScript code you'll add in the <head> section (NOTE: this script assumes you will use your own tracking code ID):

    <script type="text/javascript">
    function recordOutboundLink(link, category, action) {
      try {
        var pageTracker=_gat._getTracker("UA-XXXXX-X");
        pageTracker._trackEvent(category, action);
        setTimeout('document.location = "' + link.href + '"', 100)
      }catch(err){}
    }
    </script>

3) Update the outbound links you want to track to call the new function without following the link first.

For example, to log every click on a particular link to www.someothersite.com, you would use the _trackEvent() method in the link's <a> tag, like so:

    <a href="http://www.someothersite.com" onClick="recordOutboundLink(this, 'Outbound Links', 'example.com');return false;">

NOTE: In the above example, I'm using the category label "Outbound Links," which is a logical category for all outbound links in my Event Tracking reports. It sets the specific name of the website as the second parameter in the call. With this structure in place, I'm able to see "Outbound Links" as one of my event categories and drill down to see which particular outbound links are the most clicked on.

John Hossack

Tracking Error 404 Pages and Broken Links

Whether you are an ecommerce site, lead generation site, or publishing site (even a blog)... you will likely have the occasional technical problem with your site. Sometime your site may throw a 4XX (client error) or 5XX (Server Error). These errors are often created as a result of broken links within your site, so you will want to find them and fix them ASAP.

Setup: Placing the GATC in your Error 404's, 500's, etc.

To track error pages you will need to have the Google Analytics Tracking Code (GATC) added to your error page template(s) (contact your webmaster to complete this task). Without the tracking code on the error pages you will not be able report on these pages or find their associated broken links.

As a reference, here is the code:

<script type="text/javascript">
Var gaJsHost = (("https:" == document.location.protocal) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E"));
</script>
<script tupe="text/javascript">
Var pageTracker = _gat.getTracker("UA-xxxxx-x");
pageTracker._trackPageview();
</script>

Note: Be sure to use your own number under gat.getTracker()

With the GATC on your error pages they will now be tracked as page views. Since these error pages will be considered page views you will want to create a filter that will allow you to view them in isolation from each other.

One important aspect to setting up your error report properly is the naming convention that you use for your error pages' in the HTML "title" tag. All of the title tags need to be created in a consistent manner so that a single filter will be able to identify them. An example title tag would be: Error 404 Page.

For other errors you would just replace the '404' with the appropriate error number. An example of a custom filter that will track the above format would be:

Filter Type: Advanced
Field A -> Extract A | Page Title | (Error [0-9][0-9][0-9].+)
Field B -> Extract B | Request URI | (.*)
Output To -> Constructor | Request URI | $A1$B1
Field A Required: Yes
Field B Required: Yes
Override Output Field: Yes
Case Sensitive: No

An alternative version of the Field A regular expression is: (Error [0-9]{3}.+) Once you have the GATC on your error pages and set up your filter to help differentiate the different type of error pages from each other it is time to figure out where your error pages are and which links (broken links) sent your visitors to these nonexistent pages.

Creating the Report in Top Content

To create your error pages report you will go to the top content report and then filter by the term "error" (assuming you had this word in your error page title tags as we did above). This will bring up all of your error pages and let you see the associated Content Performance metrics associated with them (pageviews, unique pageviews, bounce rate...)

Now that you have identified the error pages we need to track down the broken links that created the error. To do this you will click on an error page in the report to view the content details of that page. From the content details page you will then click on the "Navigation Summary" link on the right side. Once on the Navigation Summary page you will be able to see the page your visitor was on prior to visiting your error page. A quick visit to these pages and you should be able to figure out where your broken links are. Sometimes the pages with the broken links will not be within your site and you will need to contact someone else and ask them to correct the link, or set up a 301 redirect on your site to redirect the inbound visitor to the correct URL.

This is a great report for your webmaster or IT team to review regularly so that you can fix broken links as quickly as possible and reduce the number of error pages that your visitors will see.

original source

Other resources John recommends:

• Tracking Slow Load Times
• Integrating Google Website Optimizer w/ Google Analytics

Justin Cutroni

Google Analytics and CRM Integration

Hands-down this is one of my favorite things to do is adding Google Analytics data to a CRM. It’s a beautiful marriage of data. GA explains a visitor’s on-site behavior while CRM data XXXXXX.

I’m  going to cover the integration from a high level. I’m not going to include any actual code, as every implementation is different. If you’re technically inclined you should be able to crank out some code after reading this post. If you’re not technically inclined point your IT team to this post and they should be able to develop a solution for your site.

The usual integration technique involves mining the data in the Google Analytics tracking cookies and passing it to the CRM. The GA tracking cookies hold some pretty cool information, including where the visitor came from and how many times they’ve been to the site.

Imagine you rely on the website for leads. Wouldn’t you like to know which specific marketing activities lead to a lead? Or how many visits were required before a lead was submitted?

There are two steps to this hack and both are coding intensive:

1. Extract information from the GA tracking cookies
2. Pass data to the  CRM system

As I mentioned above, the GA tracking cookies contain some pretty juicy data. The data can be extracted from the cookies two different ways.

You can use client side code, like JavaScript, or you can use server side code, like PHP or Java. The actual implementation is up to you. One method does not yield more data than the other. So you can choose the implementation technique that’s going to work best for your site.

Let’s look at the GA cookies and identify useful information. I like to use FireCookie in FireFox to view cookies, but you can use your favorite cookies viewing tool.

The __utma cookie stores information about the visitor, including the number of visits the visitor has made to the site. Here’s a sample  __utma cookie. The last number, in bold below,  is the number of visits this visitor has made to the site:

32856364.1071264929.1282659543.1282659543.1282659543.1

We want to grab that number and store it in the CRM. What’s the business value? It tells us how many times the visitor has been the site. If we grab this data when the visitor submits a contact form, etc., we can asses  before performing some action how long it takes to get people to take action and we can adjust our marketing activities to move more people through the funnel.

Now let’s turn our attention to where people come from.

The __utmz cookie stores where the visitor came from in  a series of name-value pairs. Let’s take a look at a sample __utmz cookie and describe these name-value pairs.

32856364.1282659573.1.2.utmcsr=google|utmccn=(organic)|utmcmd=organic|utmctr=justin cutroni

This cookie was generated after I visited my site from a google organic search for “Justin Cutroni” (yes, I’m incredibly vain ;) ) Don’t worry about all the numerical junk at the beginning of the cookie. Focus on the (somewhat) human-readable part.

You can see that my search information is actually embedded in the cookie. You can easily pick out the words “organic”, “google” and “justin cutroni”. The information is in a “name=value” format, with different pairs separated by a pipe character.

We want to grab the values associated with utmcsr, utmccn, utmcmd and utmctr. These parts of the cookies hold specific information about where the visitor came from. Here’s a brief description about each part of the __utmz cookie.

• utmcsr: Campaign Source. This part of the cookie holds the value of the utm_source link tagging parameter. If no utm_source parameter is used GA will use the name of the organic search engine for organic traffic (google, yahoo, etc.),  the domain name for any referral traffic and (direct) for direct traffic.
• utmccn: Campaign Name. This part of the cookie holds the value of the utm_campaign parameter. If not utm_campaign parameter is present GA will use (not set).
• utmcmd: Campaign Medium. This part of the cookie holds the value of the utm_medium parameter. If no utm_medium is present GA will use ‘organic’ for organic traffic, ‘referrall’ for a referring website and ‘(none)’ for direct traffic.
• utmctr: The keyword or search term. Obviously this parameter holds the keyword from paid and organic search. For traffic sources other than search this parameter will have a value of (not set).

• How many time the visitor has been to the site (from the __utma cookie)
• Where the visitor came from (from the __utmz cookie)
• Any custom visitor information (from the __utmv cookie)

Once you grab all of the values it’s time to put them in your CRM. Again, the exact implementation will depend on your CRM. If you’ve got a home-grown solution you may just need to create extra fields in a database. This is where your expertise and knowledege of your CRM come into play. You may need to create new fields in the CRM database or some other structure to hold the data. The key is to store this information along with the other information coming from the website.

When you grab the cookie values is also an issue. It’s easiest to grab these values when the visitor submits some type of form or engages in some mechanism that includes identifiable information. For example, when a visitor submits a contact form, you can parse the GA cookies and send the data back to your CRM with the rest of the form data. Then insert it into the CRM.

 

And that’s basically it. Easy right? ;) Hopefully this post gives you a road-map that you can follow for your specific implementation.
 

Manoj Jasra

Site Search Without the Query String, Export Hundreds of Data Rows

My two favorite Google Analytic hacks which I use very often (both of which by no means originated from me) are: Capturing site search when there isn't a querystring present and secondly exporting more than 500 rows of data.

Site search without a query string:
 
1)  Add the following line of code to your Google Analitics code:
pageTracker._trackPageview('/searchresults?query=[SearchPhrase]');  Replace [SearchPhrase] with the actual keyword being searched for. In PHP it would be: pageTracker._trackPageview('/searchresults?query=<?php echo $keyword; ?>');

2) As you normally would, iInsert ‘query’ into the “Query Paramater” textbox within the site search section of Google Analytics.
 
Export 500+ Rows

1. Navigate to your report
2. Append "&limit=5000" to the URL and hit enter
3. Select export to CSV format and voila! 500+ rows

Bas van den Beld

Bas's Google Analytics Tips

First off, I use the "Better Google Analytics" add on for Firefox, which gives me some good insights in some social media numbers, something which GA isn't sufficient enough in themselves.

Second, the Google Analytics plugin by Yoast is a must have for everyone working with GA and Wordpress. Saves loads of time.

Third, something I saw this week, which I do not recommend doing, but for a read it's good fun: Google analytics bombing.