The ROI Revolution Blog
Articles Tagged with 'Tracking'
Google Analytics Subdomain Tracking
January 5, 2011
If you do a quick search on "Google Analytics Subdomain Tracking", you may have noticed that many of the top results are either woefully out of date or rather confusing. The purpose of this post is to provide my recommendations for Google Analytics subdomain tracking as of the current version of the asynchronous Google Analytics Tracking Code.
Currently there's no specific article on Google Code dedicated to Google Analytics subdomain tracking. The closest is this, which recommends the following:
//Tracking code customizations only
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-12345-1']);
_gaq.push(['_setDomainName', '.example-petstore.com']);
_gaq.push(['_setAllowHash', false]);
_gaq.push(['_trackPageview']);
I propose that instead, for the vast majority of sites with subdomains, you should use the following:
//Tracking code customizations only
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-12345-1']);
_gaq.push(['_setDomainName', 'example-petstore.com']);
_gaq.push(['_addIgnoredRef', 'example-petstore.com']);
_gaq.push(['_trackPageview']);
So what's wrong with the code recommended on Google Code? It turns out there are three issues with the code that cause unnecessary problems:
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Updates to AdWords Search Funnels Reports
October 14, 2010
One of my biggest complaints about Google AdWords and Google Analytics has always been the oversimplified attribution models they use. Last touch attribution sucks. It completely ignores upper funnel search visits to your site—first-time visitors who use broader search terms to get there. These are people who are curious about your products or offers, but not quite ready to buy.
Thankfully, Google is not oblivious to the need for more in-depth attribution funnel analysis. This past spring, they introduced AdWords Search Funnels, which finally gave AdWords advertisers the ability to drill down and see the search paths that visitors use when clicking through to their sites.
And last week, Google added additional features to these reports, including an increase in the conversion history window and a way to sanitize conversions that were potentially affected by cookie deletion bias.
Are you using the AdWords Search Funnels yet? If not, read on to find out why you should.
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Five Google Analytics FAILS
August 21, 2009
Here at the ROI Revolution blog, we usually strive to provide you with helpful how-tos and the best examples on making your Google Analytics accounts lean, clean, and useful. Today, we're going a different route in the hope that instead of teaching by example, we can show what not to do.
Ladies and gentlemen, I present to you our top five Google Analytics FAILs. These are real life examples that our intrepid Google Analytics support staff have encountered in the line of duty. They are not pretty. You have been warned.
1. There Can Be Only One: utm_nooverride=1
We've talked at length about utm_nooverride before. We're big fans of using the utm_nooverride query parameter to make sure that branded and email traffic doesn't overwrite more important long tail referral data.
But there's really only one parameter value to use in this situation. One. It's one. The only one is one. Does that make sense?
No? Ok. Well, see the screenshot to the left? That's what you shouldn't use.
First of all, you should never see the utm_nooverride parameter in your Google Analytics reports. Secondly, you should spell it correctly. Third, don't pass "2" as a value. It doesn't work. Just follow Shawn's instructions in his three-part series on using utm_nooverride and you won't FAIL.
2. You Are Not Selling Medium Green T-Shirts
At the very least, you're not selling only medium green t-shirts, right? Well, maybe you are. Who am I to judge?
The example provided in the Google Analytics Help Center article on e-commerce is just that: an example. But I'd be lying if I said that I hadn't seen people cut and paste that example script right onto their receipt pages, then called it a day.
Google Analytics can't figure out what you've sold unless you tell it. You need to roll up your sleeves and find the variables that contain a visitor's transaction data. Then pass that data to Google Analytics. It's like a relay race, except you're passing product names and revenue figures.
Place a test order. If you view your receipt page's source code and you don't see the correct order total or the products you purchased (or if your code says you bought a medium green t-shirt), then you've got more work to do.
You'll probably also want to check out the values you're passing. We've seen some pretty hinky stuff show up in the Google Analytics e-commerce reports because someone threw too many numbers into the revenue or shipping fields (see left).
Start by checking out Caitlin's article about de-stressing your Google Analytics e-commerce setup. If you're still mired in FAIL, you can always hire us.
Hit the jump for three more epic Google Analytics FAILures.
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AdWords Conversions: The One vs. Many-Per-Click Breakdown
June 25, 2009
There's a lot of confusion regarding Google's
recent change to conversion metrics with the AdWords conversion tracker. Previously a "1" in the "Conversion" column would tell you there was at least one conversion that happened within 30 days of that date. You were happy with this limited knowledge.
Messy and/or complex data was disguised as clean & simple data. The "1" was all you knew. If the user clicked an ad and purchased something, you'd see a "1." If the user bookmarked the page with the conversion tracking script and went back to it a week later, you'd still see a "1." If another purchase was made two weeks later, you'd still see a "1." Simple, right?
In early April, Google exposed some of the potential mess to be more in line with the way conversions and transactions are tabulated in DoubleClick and other online ad platforms. They changed the name of "Conversions" to "Conversions (1-per-click)" and added a new metric called "Conversions (many-per-click)". While the 1-per-click conversion spot can only be filled once, the many-per-click conversions are incremented whenever any of your conversion scripts run within 30 days after a click.
Under the new system, consider the following scenarios and what conversions would be tracked for each:
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Understanding Correlations in Google Analytics
May 28, 2009
Website traffic does not exist in a vacuum. Here's a simple example: Jack comes to your website on Monday after seeing one of your AdWords content ads and he likes what he sees. He's a careful shopper though, so he's not ready to commit quite yet and leaves the site for the day. He takes some time and does some comparison shopping throughout the week, talks to some of his friends and comes back to your site again after typing your company name into Google and clicking on an organic result. He sees an offer for a 10% off coupon if he signs up for your newsletter, so he does, and then leaves the site again. In a week, he gets an email about a sale you are having, and clicks on a link within the email, finally making a purchase on this, his third visit.
So the big question is - how does this show up in Google Analytics? Does AdWords get any credit for the sale? The simple answer is no. Depending on if you are tracking your emails in Google Analytics (and how you are doing it), you'll either see a conversion for the email, the organic branded search or even a direct visit. Wouldn't it be nice to know that at one point AdWords had something to do with the sale? Better yet, wouldn't you like to know the Campaign, Ad Group and Keyword that was responsible?
Jack's example is a very common one, and pretty simple in comparison to the way a lot of people use the Internet, so it is important to try and understand the relationships between your different traffic sources.
Still don't care? Let me give you a real-world example of what can happen if you ignore it:
Case Study: A company that deals in a software product noticed that it was getting what looked like a pretty poor return on Content Network traffic from AdWords (responsible for what Google Analytics reported as roughly 5% of daily revenue). In an attempt to reduce costs, they decided to pause this traffic completely. The result was that almost immediately they noticed a 15-20% drop in daily revenue!
What the heck happened? Well, it turns out a large percentage of that content traffic was coming back as either organic branded traffic or direct traffic. They never bothered to look at the relationship between their content traffic and other traffic sources, and it cost them.
Conversely, by understanding this relationship, they have been able to not only gain back the 15-20% that they lost, but improve the return even further!
So how can you learn from their mistake? Here are a few things you can do, ranging from fairly simple to more complex, to help you grasp the relationship between your marketing sources and mediums:
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6 Tools You Can Use to Troubleshoot Google Analytics Yourself
April 17, 2009
It's nice to be able to find the tools you need when you need them. It's true for farmers and it's true for web analysts. Even if you aren't a web analyst, you have access to a lot of great tools on the web that can help you figure out if Google Analytics is working properly on your site. While my last article focused on
tools you can use to get the most out of the reports in Google Analytics, this article is more for those of you that want to make sure that the data is right before it even gets there.
Bury your Google Analytics problems.
Read on for a list of 6 tools that you can use to find out for yourself what's going on with Google Analytics.
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Installing Website Optimizer if you use Google Analytics
September 17, 2008
Ok, so back when I declared that Google Website Optimizer and Google Analytics represented 'A Perfect Marriage', I was overlooking some of the early bumps the newlyweds would experience before they lived happily ever after.
That being said, there are some things to look out for if you are using Google Analytics and are considering Google Website Optimizer as your testing platform of choice. Or maybe you have already noticed some strange things trying to use them together?
Here are the things to look out for:
1. Are you using urchin.js or ga.js?
2a. Are you setting _udn="something" (for urchin.js) or _setDomainName('something') (for ga.js)?
2b. Are you setting _uhash="off" (for urchin.js) or _setAllowHash(false) (for ga.js)?
3. If you are using urchin.js, are you tracking Ecommerce?
As long as you've got the above four things accounted for, everything should work fine. So I'm going to address each one in detail so that you know exactly what to do.
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New and Improved: Google AdWords Conversion Tracking by Type
June 4, 2008
Are you sure that the conversions you see tracked in the Google AdWords Campaign Summary page are really the conversions you're hoping for? How do you know what types of conversions your AdWords campaigns are generating if you have the AdWords Conversion Tracking script on many of your site's success pages?
It's best practice to send a searcher to a landing page that has one clearly defined action that you would like them to take, say filling out a Contact Us form. But what happens when that Contact Us page links to another page on your site with a completely different desired action, say a newsletter sign up? If the searcher clicks on an ad that takes them to the Contact Us landing page but somehow moves over to the newsletter page and signs up there, you've still got a conversion reported for your Contact Us campaign. The problem is that it's the wrong type!
Now, when you look in your Contact Us campaign, you think you're only generating leads for people raising their hands to be contacted, but you've actually got people who are just interested in reading your newsletter lumped in there as well. It can be very misleading.
Google AdWords has created a way to track your conversions by type.
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Using Website Optimizer with Google Analytics NEW!!
May 12, 2008
You may remember that back in April of '07, I came up with a way to get your
Google Website Optimizer multivariate experiment data to show up in Google Analytics. While useful, there were a few drawbacks that I'm sure some of you have noticed, and it wasn't the easiest thing to implement. After getting a lot of great feedback from users, I've come up with a new script that has many advantages over the old method:
- Uses easier implementation
- Works with both ga.js and urchin.js (make sure you use the right instructions below for Step 2)
- Includes error-handling so that a JavaScript error no longer occurs if an experiment is not yet running or is paused, stopped, or completed
- Features automatic page name tracking - no more changing the Google Analytics code on the page
- No longer replaces regular page reporting
As a refresher, the whole point of this integration is to allow you to make the most of your experiments. While Google Website Optimizer by itself can give you a quick look at which combination is best at improving conversion, it tells you nothing about transactions, revenue, micro-conversions, navigation, segmentation by source, and bounce rate. If you integrate Google Analytics into your Google Website Optimizer experiments, you will get much richer data, and be able to get a true idea of how your test is doing.
Again, this integration is designed for multivariate experiments only - you do not need to use any special tools to be able to get A/B test data from Google Analytics.
The first thing to do is find out if you are using ga.js or urchin.js. Depending on which version of the Google Analytics code you are using, you'll want to use different instructions.
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Google Analytics for Blogger in Private Beta
May 2, 2008
On Wednesday, Google announced that there will be a new Google Analytics interface for Blogger.
Measure Map, which was acquired by Google in February of 2007, has already done quite a bit for Google Analytics, which had its interface completely revamped. It looks like now the team is applying some of its lessons from that experience over to the blogosphere.
Although Google Analytics is already available to everyone, as a blog writer it's nice to have easy access to metrics that are tailored to your specific needs. Google seems to be addressing these needs with a new Google Analytics integration designed specifically for Blogger users.
According to Jeff Veen, Measure Map will be available 'as an integrated feature of both Google Analytics and Blogger'. That sounds pretty exciting to those of us that are obsessed with our blog statistics. And if the integration is being designed by the same folks that brought us the new Google Analytics interface, that means it should be simple to navigate and extremely useful.
This new interface is now in private beta (which means you probably won't notice it yet), but it looks like Google has plans to migrate all existing Measure Map users over to the new Google Analytics system. That means it could be a few months or even a year before it's rolled out to everyone - there's really no way to know at this stage. Since it's in beta, there's a good chance there will be some kinks to iron out.
So if you use Blogger for your blog, be sure to stay on the lookout for this neat new feature!
