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Google Analytics Adds Weighted Sort

Saturday, August 28th, 2010 by Nick Iyengar
Google Buzz

The stream of new Google Analytics features coming out of the Googleplex continues, and that’s what we like. Recently Google announced a helpful feature called Weighted Sort, which helps efficiently surface actionable data while helping you avoid meaningless outliers.

One of the innate issues with using ratio-based metrics (bounce rate, conversion rate, etc.) is that when you sort, you return all of the outliers – the 100%’s and 0%’s, even when the sample size is tiny. Let’s say you want to figure out which AdWords keywords have high bounce rates, so you can adjust your bidding, landing pages, etc. Sorting by bounce rate, you’ll get something like this:

Of course, this isn’t what you were trying to do. What you actually want to know is: which keywords most need the most optimization attention? In the past, you would have had to manually create an advanced filter to specify that all returned results have more than X number of visits. That works fine, but it takes more effort, and we don’t like that.

Now, we can simply check the “Weighted Sort” button and – voilà - Google’s new sorting algorithm automatically surfaces the most significant results!

That’s really all there is to it. A couple of things to keep in mind:

  • You can use weighted sorts on other metrics, too: conversion rate, exit rate, % new visits, etc.
  • You’ll notice that the entries in your table are no longer strictly in order. Of course, that’s because you’re no longer sorting based only on the metric – you’ve asked Google to take other factors, like sample size, into account.

Questions? Cool use cases? Leave them in the comments for us, and for more tips, tricks, and updates, don’t forget to subscribe to our feed and follow us on Twitter!



Nick Iyengar
Nick is a senior analytics and web intelligence analyst with WebShare. You can find out more about Nick here.

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Posted in Google Analytics 101 | No Comments »

How do I track that little Facebook “Like” button in Google Analytics?

Friday, August 27th, 2010 by David Booth
Google Buzz

We get asked very often how to track Facebook “Like” buttons inside Google Analytics, so here’s a post that will show you how to do it.  There are basically three steps – first, you need to get the Like button on your pages using the XFBML / Javascript version of the Like Button.  Next, you’ll need to fire some Google Analytics code in a Facebook event that tells us when a successful “like” action has occurred.  Lastly, you need to find where it all ends up in Google Analytics and take action based on your new data!

1. Get a Facebook Like Button on your page(s)

The first step is to actually get a Facebook Like Button on your page. The quickest way to do this is to go here:

http://developers.facebook.com/docs/reference/plugins/like

Just fill out the form and click the “Get Code” button…you’ll see something like this pop up:

Tracking Facebook Like Buttons with Google Analytics

Now, you’ve got two options here. The iFrame version is admittedly the easiest to install, but unfortunately you don’t have any way to track when someone actually clicks and successfully “likes” your page as a result. There’s no onClick event you can use for an <iframe>, or for a <fb:> tag for that matter. And even if you could, the click itself doesn’t tell you if someone actually successfully liked your page or not – remember, they have to log into Facebook first, via a popup that might even be blocked in some browsers, so your click and Like counts may be very different.

So instead, we’re going to use the XFBML version (highlighted).

To implement this, you’re going to need to use the Facebook Javascript SDK – basically it works like this (and you can view the source of this page – you’re looking at a working example):

  • Update your <html> tag to include

    • xmlns:fb='http://developers.facebook.com/schema/' xmlns:og='http://opengraphprotocol.org/schema/'

  • Add the proper Open Graph Protocol meta tags – this is not necessarily required but a good thing to do.
  • Reference the Facebook Javascript library – we recommend you use the following asynchronous version (make sure to put your own App ID in there):


    • <div id="fb-root"></div>
    <script>
    window.fbAsyncInit = function() {
    FB.init({appId: 'INSERT YOUR APP ID HERE', status: true, cookie: true,
    xfbml: true});
    };

    (function() {
    var e = document.createElement('script'); e.async = true;
    e.src = document.location.protocol +
    '//connect.facebook.net/en_US/all.js';
    document.getElementById('fb-root').appendChild(e);
    }());
    </script>

  • Add the XFBML that you generated above (make sure to update it with your own page URL as the source and add any available attributes you might want) where you’d like your button to appear on your page:


    • <fb:like href="http://www.somesite.com/somepage"></fb:like>

2. Fire a Google Analytics Event when a “Like” action occurs

OK, at this point you’ve got your Like button up and running. Now in order to track these in Google Analytics, we’re going to use Event Tracking to fire an event whenever someone successfully Likes the page. You can choose to set this up in whatever hierarchy you like, but here’s one you might want to use:

Category: “facebook”
Action: “like”
Label: URL of the page that was “liked”

Using the _trackEvent() method of the pageTracker object, the Google Analytics javascript code would look like this:


pageTracker._trackEvent('facebook','like', href);

Note: This is the synchronous version of the Google Analytics code and assumes a javascript variable called href contains the URL of the page that’s being “liked”

So the last step in this process is to actually fire this code only when a successful Facebook like occurs. To do this, we’re going to subscribe to an event that Facebook exposes to us when the successful “like” action occurs. When we detect that event, we’ll fire our _trackEvent code. Here’s the code that will do it:


<script>
FB.Event.subscribe('edge.create', function(href, widget) {
pageTracker._trackEvent('facebook','like', href);
});
</script>

Note: The safest placement of this code is somewhere BELOW your standard Google Analytics tracking code – this will ensure that the pageTracker object has been defined before you try to use it

That’s it!  Feel free to get creative here…want to use a Custom Variable to create a segment of either visitors (scope = 1) or sessions (scope = 2) that “Liked” something?  Then all you would have to do is something like this (make sure your slot 1 is available and you want this at a visitor scope for the exact code below):


<script>
FB.Event.subscribe('edge.create', function(href, widget) {
pageTracker._setCustomVar(1,'facebookLiker','true',1);
pageTracker._trackEvent('facebook','like', href);
});
</script>

Want to stick this data into a database so you can use it for any number of customized reasons? Just fire some AJAX in there. Just about anything you can accomplish with Javascript can be done with each Like event.

3. Find that data in Google Analytics and USE it!

Now, you can log into your Google Analytics account and head over to the Content > Event Tracking reports and take a look at the Categories, Actions and Labels as you’ve defined them:

Event Tracking for Facebook Like Buttons in Google Analytics

Note that here we’ve drilled down to the Category of “facebook” and the action of “like” – now we’re looking at a list of the URL’s we passed in – or in our case the actual blog posts that people “liked.” They’re a bit ugly since they’ve been formatted for proper URL encoding, but hovering over the label itself will let you see the URL that was “liked” pretty clearly.

So what do we do with it?

Well, this is one more set of data that can be used to identify what content resonates with your user base.  Which are the popular themes of blogs?  Which are the authors that our visitors like the best?  Which topics do people like to read about?  We can look at the Site Usage tab right here to understand if people who like certain blog posts are any more engaged (think bounce rate, time on site, average pageviews per visit) than others.  We can look at our Ecommerce tab and find out if people who like certain pages are more or less likely to, say, sign up for one of our live Google Analytics or Website Optimizer Seminars for Success trainings.  With this knowledge, we can tailor the content that we write to the things that people like the best and the things that get people to engage with our site and convert on our goals.

And don’t forget about your Advanced Segments! Below you can see a quick Advanced Segment configuration that will quickly let you compare those Facebook Likers to any other segment of traffic you care to define:

Google Analytics Advanced Segment for Facebook Like Button users

Hope this helps a few of you out, and we’d love to hear how you’re using this in the comments!



David Booth
David is a co-founder and principal consultant at WebShare. You can find out more about David here.

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Posted in Google Analytics | 8 Comments »

Are These Design Elements Providing the Expected Value Add?

Thursday, August 26th, 2010 by David Evans
Google Buzz

We help answer questions like this all the time! And with this simple method, you can too.

With WebShare redesign projects, we do more than just build pretty websites. A truly good website is a combination of being aesthetically pleasing, functional and highly measurable. The purpose of the site has to be clearly defined and the results must be tracked, tested and analyzed in order to make informed decisions to better serve its purpose. Testing, measuring, analyzing: This is what we do.

We recently completed development on the new C3 Concerts website (www.c3concerts.com) and have configured some very common additional Google Analytics tracking to provide the necessary insights to make better decisions about the site. After collecting enough data, seeing how effective various design elements are on the site is a snap!

Example: There are two banners on the home page to showcase various events, promotions or news articles. An internal debate exists over the necessity and/or effectiveness of these banners.

Enter WebShare and Google Analytics. In their native state, these banners are simply links to other pages within the website. Clicks on these banners send the user to the expected page and GA records a standard pageview of that resulting page. However, while this shows how many visitors are viewing a particular page, the method doesn’t provide the insights of how I got to that page (other than knowing I came from the home page). For C3 Concerts, we add virtual pageviews to the onclick event of the anchor tag that links to the target page.

Using an organized naming convention for virtual pageviews makes it very easy to see in the Content Drilldown reports:

  • A banner was clicked
  • Which banner was clicked (1 or 2)
  • What type of announcement (event, news, promotion)
  • Info about the specific announcement

For example, Banner 1 links to a specific event:

<a onclick="_gaq.push(['_trackPageview', '/vpv/banners/banner1/event/name-of-event']);"
href="event.html" >BANNER</a>

Note the “vpv” that leads it off…by putting all virtual pageviews that we create in this base “folder”, we can easily create profiles in Google Analytics that filter this “fake” data out so as not to throw off our true pageview counts, bounce rates, etc…

In Google Analytics, a few clicks through the Content Drilldown report provides the answers needed to make decisions:

  • How many banners were clicked?
  • Which banner was clicked more often?
  • How many events, news or promotions were clicked via banners?
  • How many click-thrus per promotion?

About C3 Concerts

C3 creates, books, markets, and produces live experiences, concerts, events, and just about anything that makes people stand up and cheer. Among others, C3 produces the Austin City Limits Music Festival, Lollapalooza, as well as more than 800 shows nationwide. In additon, C3 offers representation services and publicity to artist and entertainers.



David Evans
David heads up software and web design efforts at WebShare. You can find out more about David here.

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Posted in Google Analytics 101, Website Design | No Comments »

Quick Reference – language codes for Google Analytics reports

Wednesday, August 18th, 2010 by David Booth
Google Buzz

Here’s a quick list of the language codes that Google Analytics uses in the Visitors > Languages report:

http://www.websharedesign.com/tools/google-analytics-language-codes/

While you might know most of the ones you routinely see in your reports, every once in a while it’s nice to have a quick reference handy for that one you don’t recognize or just aren’t sure of, so bookmark away!



David Booth
David is a co-founder and principal consultant at WebShare. You can find out more about David here.

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Posted in Google Analytics | No Comments »

Limits to Advanced Segmentation in Google Analytics

Thursday, August 5th, 2010 by Nick Iyengar
Google Buzz

Today I stumbled upon an undocumented (or at best, minimally-publicized) limitation to Google Analytics’ advanced segmentation feature. It’s hard for me to knock what I think is GA’s best feature, but I’ve found that I can only create 100 advanced segments at a time. That may sound like a lot, but when you have more than a few Google Analytics accounts, it’s easy to start creating a lot of segments for yourself. In case you run into this like we often do at WebShare, here’s what you need to know and a workaround you can use.

In addition to the limitation to the number of segments, there’s an annoying little glitch when you try to create your 101st segment. Let’s say you’ve laid out your segment, named it, and tested it, as shown below:

Once you try to save your segment, you’ll end up receiving the following error. Notice how in addition to giving you the error message, Google wipes out your segment. It’s a minor thing, but it would be nice for Google to preserve our segments so that we could open up a profile in another tab and delete a pre-existing segment.

To be fair, there actually is a small warning notification when you try to create a 101st segment. It’s not very visible, though, so be careful.

As a workaround, you can create a “dummy” second login to use for GA. For example, if your username is user@example.com and you’ve run out of segments, create a new username for yourself under “user+1@example.com” or something similar. Note that this works for any GMail account, but may not work on other email platforms. If that doesn’t work for you, simply create an entirely new login to get beyond 100 segments.



Nick Iyengar
Nick is a senior analytics and web intelligence analyst with WebShare. You can find out more about Nick here.

See more posts by Nick Iyengar

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Posted in Google Analytics | 4 Comments »

New AdWords Reporting in Google Analytics: An In-Depth Look

Tuesday, June 29th, 2010 by Nick Iyengar
Google Buzz

Many of you may have recently noticed a new addition to your Google Analytics account: a revamped AdWords reporting suite. In the past, GA provided AdWords reporting via two reports: the AdWords Campaigns report and the Keyword Positions report. These were, and are, two of the most powerful reports for AdWords advertisers, but Google has now created a new, expanded set of AdWords report. Today we’ll be taking a detailed walk through the entire AdWords reporting suite, looking at the following new features. Feel free to skip ahead to the parts that interest you most!

  1. New AdWords “Overview” Page
  2. Changes to “AdWords Campaigns” Report
  3. Additional Segmentation Options (dimensions)
  4. New AdWords Reports

First, a quick refresher on how to find these new reports: after you log into GA, click on “Traffic Sources,” then click on the AdWords (Beta) section, as shown below.

New AdWords “Overview” page

When you navigate to the new AdWords section of GA, the first thing you’ll notice is that it now has an “Overview” report, just like the other main sections of GA (e.g. Visitors, Traffic Sources, Content, etc.). This tells you something about the importance of AdWords in Google’s eyes, but it also provides a much-improved ability to get high-level AdWords data at a glance. By default, instead of seeing simply visits plotted out over time, you’ll now see your AdWords click-through rate (CTR) plotted against your website’s bounce rate. This gives you the ability to immediately understand the efficiency of both your AdWords campaigns and your AdWords landing pages. Of course, you can customize the metrics that are displayed, and you can easily opt to simply view one metric at a time rather than two. Below the line graph, you’ll also get a snapshot of a series of key metrics: visits/clicks, conversions, revenue, and return on investment (ROI).

Changes to “AdWords Campaigns” Report

To analyze AdWords on a campaign-by-campaign basis, the AdWords Campaigns report will still be your “headquarters.” Note that it’s been renamed; it’s now simply the “Campaigns” report, but structurally it’s the same as it has always been, in that it allows you to drill down from campaign to ad group to keyword. So what’s substantively different?

First, you’ll notice that the metrics you see on the Site Usage tab have changed. A big part of what Google is trying to do is help GA users streamline their analysis processes. By including Goal Completions (conversions) and Revenue on the Site Usage tab, you no longer have to navigate through three tabs to get these metrics for a given AdWords campaign. It’s not a complex change, but it certainly helps you work more quickly and efficiently.

The biggest and most exciting change to the Campaigns report, though, is the addition of several new segmentation options (also known as dimensions) that are extremely helpful.

Additional Segmentation Options (Dimensions)

Google Analytics has long been known for the segmentation flexibility it provides, but that doesn’t mean we don’t always want more options. Fortunately for us, Google has now opened up nine – count ‘em! – dimensions for marketers and analysts to use when analyzing AdWords. Today we’ll take a look at several of these and examine how they can be useful for us.

Ad Distribution Network

As many of you know, you can use your AdWords campaigns to distribute your ads across three major platforms: Google.com search, Google search partners like AOL and Ask, and the Google Content Network (recently renamed the Google Display Network). These platforms often perform very differently for different advertisers, so it’s crucial to understand exactly where your ads are being shown and how they’re performing. Now that we can segment by Ad Distribution Network, it’s very easy and efficient to do this analysis.

Here we can see that for this particular advertiser, Google search is most efficient from a Per Visit Value standpoint, followed by Google search partners and finally the Content/Display Network. Of course, you can drill down from the account level to an individual campaign, ad group, or even keyword! Performing this kind of analysis has major implications for your AdWords budgeting, bidding, and targeting decisions.

Match Type

Google provides three match types for buying keywords. Broad Match gives Google the freedom to automatically show your ads for search terms it thinks are relevant to you. Phrase Match forces Google to only show your ads for queries that include the bid phrase intact. Exact Match, as the name suggests, forces Google to display your ads only when the user’s search query exactly matches the bid term. For years, marketing gurus have broadcast theories and “best practices” regarding which match types you should be using. Now you can free yourself from opinions and let the data speak for itself! Which match types work best for you?

For this advertiser, Exact Match is working most efficiently in terms of Per Visit Value, followed by Broad and Phrase. When you do this analysis for yourself, you may find something very different. You may even find that different match types work best for different campaigns you’re running. Regardless of what you see, you’ll be newly armed with information that’s critical to bidding on keywords efficiently and effectively.

Matched Search Query

This is a big one, people. If you’ve been involved with AdWords for longer than a few months, you’ve probably had a moment where you thought something along these lines: “Google was showing my ads for those keywords? I’m not bidding on those!” Broad match can be a great feature in that it saves you time (you don’t have to bid on every single possible search query) and helps you find new keywords, but just as Broad Match giveth, Broad Match taketh away.

Here’s an example. Let’s say you’re bidding on the Broad Match keyword “Florida vacation.” On the plus side, Broad Match will automatically show your ads when people search for “Florida vacations,” “vacations in Florida,” and other similar variations. However, Google is not perfect. Your ads could be displayed to people looking for things that are only vaguely relevant (“Florida flights”), or even completely irrelevant (“Cancun all-inclusive”).

Google’s gotten a lot better about providing transparency into their Broad Match technology. The Search Query Report in Google AdWords is a nice report that shows you the exact term that a user types in, regardless of what your bid term actually was. But the SQR only goes so far. It can’t show you metrics like bounce rate, revenue, and per visit value. Now that we can segment our GA data by Matched Search Query though, this Dark Age is finally over!

Even though I’ve used scare tactics to get you interested in this new segmentation option, don’t forget that this kind of analysis can also help you find great new keywords that you didn’t know about. Use this report to beef up negative keyword lists, but also to find hidden gems that can make your AdWords campaigns more profitable.

These three dimensions are probably going to be the most useful additions for most people, but be aware that you can also segment your GA data in six more new ways:

Placement Domain

Placement URL

Ad Format (text vs. image, etc.)

Targeting Type (keyword vs. placement, etc.)

Display URL

Destination URL

New AdWords Reports

On top of all the new segmentation options Google just gave us, we’re also getting a series of entirely new reports: Keywords, Day Parts, Destination URLs, and Placements. They’re pretty self-explanatory, but let’s take a quick look and understand how they help us.

Keywords

This report simply shows us our AdWords keywords regardless of campaign. In the past, if I wanted to analyze my top 10 (by traffic) AdWords keywords, I’d have to do one of two things. I could either create an advanced segment, then use the generic Keywords report under Traffic Sources, or use the AdWords campaigns, and drill into individual campaigns until I found my top 10 keywords. Now, however, Google’s streamlined this process by simply providing a report that does this for us.

Day Parts

Don’t let the simplicity of this report fool you into thinking it’s not extremely useful. GA now makes it very easy to see how your AdWords ads perform based on the hour of the day. Of course, AdWords allows us to alter our bids (or even turn off our ads entirely) based on the hour of the day. Using the Day Parts report, you’ll be able to quickly decide which hours are your “peak” hours, and which hours are the ones where you should scale back your bids, or pause your ads. I’ve managed tens of millions of dollars in AdWords spend over the last several years, and at least 50% of the companies I’ve worked with didn’t use the ad scheduling feature, so use this report, and once again arm yourself with the information you need to run your campaigns more efficiently and profitably.

Destination URLs

This is a nice, basic report that helps us quickly understand which landing pages are working and which aren’t. Struggling to figure out which pages you should test with Google Website Optimizer? This report will point you in the right direction.

Placements

If you’re running ads on the Content/Display network, and using placement targeting rather than contextual targeting, you’ll know that up until now, your placements actually showed up as part of the Keywords report. A quirk of GA that did not fall in the “charming” category! Now you have a report where you can easily split out your placements.

If you’ve been using the new AdWords reports to your advantage, tell us how in the comments! And don’t forget to subscribe to our feed our follow us on Twitter to get more WebShare tips and tricks.



Nick Iyengar
Nick is a senior analytics and web intelligence analyst with WebShare. You can find out more about Nick here.

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Posted in Google Analytics | No Comments »

Google Places Updates Dashboard But We Still Want Google Analytics Integration

Thursday, June 3rd, 2010 by Dave Reichenbacher
Google Buzz

It looks like Google Places made a couple minor changes today to their dashboard interface. Besides a slight design change incorporating good use of background contrast, the big modifications were:

1) Showing some statistics right in the dashboard

Google Places Statistics in Dashboard2) An alert bar and status messages for individual business listings

Google Places Actions in Dashboard

Subtle but decent improvements nonetheless.  Google also updated their help document to reflect these changes. As I mentioned when the new dashboard first came out, I still wish they would integrate your Google Places pre-click data with your Google Analytics account (similar to AdWords and AdSense).  Fingers crossed.



Dave Reichenbacher
DR directs program management and operations at WebShare. He also is one of our Seminars for Success instructors and has an affinity toward local search marketing. You can find out more about Dave here.

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Posted in Google Analytics, Local Search / Google Places | No Comments »

Capturing First-Touch Source Information with Custom Variables

Wednesday, May 19th, 2010 by Nick Iyengar
Google Buzz

Since Google Analytics released custom variables last October, we’ve been finding all kinds of ways to use this flexible, powerful feature. From accomplishing content groupings to tracking the count of purchases by repeat buyers, custom variables have opened the door to both new data in GA and new abilities to segment our data.

One of our favorite uses for custom variables is storing first-touch traffic source information. As you may know, the default model for conversion attribution in Google Analytics is last-touch. In other words, recorded conversions and transactions are attributed to the last traffic source (with the notable exception of direct traffic, which will not override another traffic source). Therefore, it’s difficult to get an understanding of how other traffic sources contribute to conversions. Custom variables have made it much easier to get as this kind of insight with Google Analytics.

Beware this issue!

When deploying custom variables to track first touch, we’ve uncovered an interesting aspect of Google’s 64-character limit for custom variables. First, some background: to record and store first-touch source information, you need to parse GA’s _utmz cookie and store the relevant information in the _utmv cookie, which is dedicated to custom variables. In doing so, it’s easy to hit the character limit (consider that you’re potentially storing source, medium, campaign, keyword, and ad content information).

Here’s the rub: if you try to store more than 64 characters’ worth of information in the _utmv cookie, Google doesn’t simply cut you off at 64 characters and send as much data back as possible. Google flat-out won’t send your custom variable at all!

To avoid this, here are some tips:

1. Choose a short name for your custom variable’s “key,” like “FT” for first touch. The custom variable uses a “key/value” structure in which the key is basically a category of data; in this use case, your key is just first touch, while the value is something like google/organic/big blue widgets. By choosing a short name for your key, you’ll save as many characters as possible for your actual value.

2. Perform a RegEx (regular expression) search-and-replace on the value of your key/value pair to keep only characters that do not require URL encoding. You’ll save yourself many characters by avoiding the need to URL-encode some characters.

3. Trim the length of the value string to 64 characters minus the length of the key. In other words: Value = 64 – (Key length).

4. Finally, go ahead and call setCustomVar() to store the first-touch data in a custom variable.

Here’s the code you’ll need to parse the _utmz cookie and then accomplish steps 2 through 4!

<script type=’text/javascript’>
//Used to obtain a value from a string of key/value pairs
function _uGC(l,n,s) {
if (!l || l==”" || !n || n==”" || !s || s==”") return “-”;
var i,i2,i3,c=”-”;
i=l.indexOf(n);
i3=n.indexOf(“=”)+1;
if (i > -1) {
i2=l.indexOf(s,i); if (i2 < 0) { i2=l.length; }
c=l.substring((i+i3),i2);
}
return c;
}
//Retrieve campaign and referrer info from the _utmz cookie
var z = _uGC(document.cookie, ‘__utmz=’, ‘;’);
var source  = _uGC(z, ‘utmcsr=’, ‘|’);
var medium  = _uGC(z, ‘utmcmd=’, ‘|’);
var term    = _uGC(z, ‘utmctr=’, ‘|’);
var content = _uGC(z, ‘utmcct=’, ‘|’);
var campaign = _uGC(z, ‘utmccn=’, ‘|’);
var gclid   = _uGC(z, ‘utmgclid=’, ‘|’);
//Replace empty values (marked by a dash) with an empty string
if(source==”-”){source=”"};
if(medium==”-”){medium=”"};
if(term==”-”){term=”"};
if(content==”-”){content=”"};
if(campaign==”-”){campaign=”"};
//If gclid is present, explicitly set source/medium to google/cpc
if (gclid !==”-”) {
source = ‘google’;
medium = ‘cpc’;
}
//Build utmString
var utmString = source;
utmString=utmString+”!”+medium;
utmString=utmString+”!”+campaign;
utmString=utmString+”!”+term;
utmString=utmString+”!”+content;
//Replace URL-encoded ’spaces’ with dashes
utmString=utmString.replace(‘%20′,’-');
//RegEx to retain only whitelisted characters
utmString=utmString.replace(/[^a-zA-Z0-9-~!*_.]/g,”);
//Set string to specific length
utmString=utmString.substr(0,62);
//Set first touch information if not already there, using slot 3
var fT=pageTracker._getVisitorCustomVar(3);
if(!fT){
pageTracker._setCustomVar(3,’FT’,utmString,1);
}

</script>

Finally, a word on why first-touch traffic source information can be so valuable. GA’s default attribution model gives you only one view of how valuable various traffic sources are for you. Getting another view can only help you, especially because GA’s default model tends to undervalue traffic sources that may not be as prone to immediate direct response, but could still be adding value for you. Examples of this kind of traffic commonly include display advertising (e.g. Google content network, other banner campaigns) and social networking. By storing first-touch source information, you give yourself the ability to perform a more holistic assessment of the value of these kinds of traffic.

Be aware that this does not only apply to storing first touch information in the cookie. You should always make sure that your cookie length is not too long and does not contain any special characters.

If you have questions on first-touch source information or our solution above, feel free to leave them in the comments. To get more analytics tips and tricks, don’t forget to subscribe to our feed and follow us on Twitter!


Nick Iyengar
Nick is a senior analytics and web intelligence analyst with WebShare. You can find out more about Nick here.

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Posted in Google Analytics | 4 Comments »

New Changes to Google Analytics

Tuesday, May 4th, 2010 by Justin Cutroni
Google Buzz

Brett Crosby from the Google Analytics team talked about a number of new and recently announced features to Google Analytics. To recap the announcement here’s a quick video that Justin created. Look for more blog posts in the next couple of weeks talking about these changes. Overall, some really cool stuff, especially the new AdWords reports.



Justin Cutroni
Justin heads up WebShare's analytics & web intelligence efforts. You can read more about Justin here.

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Posted in Google Analytics, Webshare Videos | No Comments »

WebSharian Justin Cutroni to appear on WebmasterRadio.fm Podcast

Tuesday, April 20th, 2010 by Justin Cutroni
Google Buzz

Just a quick note, I’ll be appearing on the Wordpress Community Podcast with my buddy Joost de Valk today, April 20, at 5:00 PM EDT. We’ll be talking about blogs, Google Analytics and how bloggers can leverage the amazing amount of data in GA. Hope to see you there!



Justin Cutroni
Justin heads up WebShare's analytics & web intelligence efforts. You can read more about Justin here.

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