The ROI Revolution Blog

Mixed Type Custom Variables in Google Analytics

June 28, 2011

It's a mix tape!Google Analytics features 3 types of custom variables: page-level, session-level, and visitor-level. The official Google Code documentation on custom variables is pretty explicit about the fact that it's best not to mix types:

"Generally it is not recommended to mix the same custom variable slot with different types as it can lead to strange metric calculations."

What isn't exactly clear is what happens if you do decide to mix types. Google Code provides two cases, but surely there are additional cases. To this end, I decided to test 9 total cases:

Handling Email Referrals in Google Analytics

January 24, 2011

If you've spent any time looking through your traffic sources in Google Analytics, particularly your referral sources, you may have noticed a lot of your traffic coming various mail sources:


Clearly it's not terribly useful to see your traffic broken out this way. At the very least, you would want to consolidate all of those sources.

But if you think about it, it probably doesn't matter a whole lot which email service provider a visitor happened to be using when they clicked to your site. Perhaps it'd be better if we just consolidate all of those email sources into one entry. Not only would this significantly clean up reports, but it would also allow you to see the overall impact of traffic coming from email to your site.

The easiest way to handle this is by using filters:

Google Analytics Subdomain Tracking

January 5, 2011

submarine.jpgIf 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search on "Google Analytics Subdomain Tracking", you may have noticed that many of the top results are either woefully out of date or rather confusing.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', '']);
_gaq.push(['_setAllowHash', false]);

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', '']);
_gaq.push(['_addIgnoredRef', '']);

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:

Updates to AdWords Search Funnels Reports

October 14, 2010

funnel.jpgOne 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.

GARE: Updated Google Analytics Dimensions Drop-down

August 9, 2010

falling drop

If you've been following GARE since the beginning, you know that the very first thing GARE ever did was add additional dimensions to the segment (now dimension) drop-down and make these available for nearly every report. As time moved on, more and more segments were added, and the list began to get rather long and unwieldy.

Well, a few weeks back, the dimensions drop-down in Google Analytics underwent a fairly major overhaul. If you haven't seen it yet, it looks something like this:

new dimension drop-down

Clicking the above image will display a larger, more readable image.

I'd like to point out several excellent features in the new drop-down:

Converting To Asynchronous Code

June 30, 2010

A sinking bowl: fill it with water and use it to track time

There's a pretty strong push now for everyone to move to the new Asynchronous Google Analytics Tracking Code. It's the only code that's available from the interface now, and nearly all of the documentation includes examples of this as the primary code to be used. Converting your code to the new async code might seem like it's just a hassle, but there are benefit to using the new code. Because the code loads asynchronously, there's no longer any danger that it will interfere with the loading of the rest of your page. This means that the code can now be placed up in the header of your pages rather than right before the closing </body> tag. The result is that you'll be able to track a greater percentage of your visitors than your were previously, which will improve the accuracy of your reports in Google Analytics. Now if your setup isn't too complex, converting won't be too big of an issue. Your old code might look something like this:

GARE: Default Applied Advanced Segments

April 6, 2010

daas.gifI was thinking the other day about some of the problems with Advanced Segments in Google Analytics. Don't get me wrong, I like the feature quite a bit and use it all the time. The main problem I have is that advanced segments require an extra step.

What I mean is that when you view a profile's report, if you want to apply an Advanced Segment, you have to expand the drop down or click the link in the left nav, click a few more things, and then finally it's applied.

That's OK if you need that advanced segment infrequently. But what if you have an Advanced Segment you use constantly, all the time, maybe even every time you view a particular profile? Then this process becomes a bit of a hassle.

Enter Default Applied Advanced Segments.

Why You Shouldn't Use the Top Landing Pages Report in Google Analytics

March 18, 2010

landing_pages_that_grab.gifIf you're trying to get landing pages that really grab your visitors, there's one Google Analytics report you absolutely cannot live without. And guess what?

It's not Top Landing Pages.

Before I unveil the report that ROIers use to do quick landing page analysis, let's find out why we're not big fans of the built-in Top Landing Pages report:

  • It only shows entrances, bounces, and bounce rate
  • It doesn't tell us conversion data for our landing pages
  • It can't show the revenue generated by our landing pages


Thankfully, there is a way to get what we need for robust landing page analysis out of GA. Hit the jump to find out how.

State Popularity: the latest addition to the GARE

February 22, 2010

patchwork-US-map.gifWe have another new addition to the Google Analytics Report Enhancer, thanks to Ophir Prusak of Google Analytics Authorized Consulting firm POP. This metric helps to interpret the significance of visit counts at the US State level. You can hear the rest of the story by reading Ophir's excellent post on the metric.

Now that State Popularity has joined the GARE family, it's a great time to download the latest version of the Report Enhancer. Here are the steps:

  1. Get Firefox
  2. Get Greasemonkey
  3. Get the GARE

In addition to the new metric, I've also been able to improve the way additional metrics are added to tables, including better sorting and handling of advanced segments and compare to past.

So how is State Popularity calculated anyway? I'm glad you asked!

Our 8 Most Popular Analytics Posts of 2009

December 29, 2009

The end of the year is a nice time to take a look back over all that was accomplished throughout the year. To that end, I'm going to give you a list of our top 8 Analytics Blog Posts of 2009. As we go through the list, I'll give you a short description of each post as well as any random thoughts I have about the post.

Enjoy the posts and have a Happy New Year!

Get More from the Navigation Summary and Pivot Tables

December 1, 2009

Back in August, a tip was released on the Official Google Analytics Blog that allows you to export more than 500 rows from a report. In the post, this technique was used to export more than 500 rows worth of keyword data. Here we often use this technique to export more than 500 rows worth of pages from the Top Content report.

What you may not realize is that you can also use this trick to export more than 10 previous and next pages from the Navigation Summary report. As you may recall, the navigation summary report looks something like this:


In some case, 10 previous and next pages may be just what you need. But what if you want more?

Are Long Page Load Times Driving Your Visitors Away?

November 25, 2009

You're making my Mee-Maw sadYou're always checking on your landing pages, right? You read the blogs, run experiments, and generally try to make your site as user-friendly as possible.

But chances are, if you're reading the ROI Revolution blog, you're on a high speed internet connection. If your webpages are loading in nanoseconds with your T1, how are they faring for those visitors who aren't as lucky as you? You know, the ones on crappy cable modems and DSL and (gasp!) the dreaded dial-up?

Does it matter? Well, it depends. If you're a gaming website or Internet marketing blog, most of your audience is probably on broadband. But if you're running a site for a retirement community in Florida, then my grandma is hitting your Flash-encrusted site in her AOL browser and she's waiting. And waiting. And waiting. She's a patient old gal, my Meemaw, but she's not going to wait all day. She's going to point her browser and her pension elsewhere.

Aside from your visitors, your site's load time is also important to Google. Not only does page load time affect your AdWords Quality Score, but according to Matt Cutts, it's going to be playing a bigger role in the organic search ranking.

So read on to learn how to optimize your landing pages' load times, and maybe make a few bucks off my Meemaw.

Need Your Own Google Analytics Greasemonkey Script?

November 9, 2009

support I write most of my Greasemonkey scripts with the idea that they will be useful to as many Google Analytics admins and users as possible.

But what if you need a script that's very specific to your business needs? Or maybe you've heard about the Google Analytics API and you'd like to use it to tie your Google Analytics report data with data from your back end. You might even just need some custom modifications to your Google Analytics Tracking Code and general setup to get that one bit of data that can make or break your business.

At ROI Revolution, we offer support plans that can be used for nearly any type of Google Analytics project you can think up. You can also use your support time to have us help you effectively configure optimal tracking for your business goals, get a second opinion on that those thorny configuration issues, or just to audit your Google Analytics account setup and make sure everything's working just as it should.

And if you just want your own Greasemonkey script, we can make that happen too.

Learn more about our Google Analytics technical support offerings.

ROI Revolution Attends 3rd Annual GAAC Summit

October 30, 2009

Hey, look! It's a gaggle of GAACs!
Every year when autumn rolls around, you'll find the ROI Revolution Analytics Team hard at work planning our strategy. Not for clients (we do that all year 'round, of course) but for the strange and fun activities planned at the annual Google Analytics Authorized Consultant Summit. Last year, it was Rock Band. This year, trampoline dodgeball.

Not all of our time at Google is spent jumping around on trampolines and pegging each other with balls. For four days, Google Partners from around the world convene in Mountain View to talk about the state of analytics and optimization, learn from one another, and push the limit when it comes to supporting our favorite free analytics platform.

Click for a rundown of what we covered...

Universal Conversion Code For Google Website Optimizer

October 13, 2009

it's universal

We've been using a piece of code for a while that makes it easier to set up multiple Google Website Optimizer experiments. These experiments could be one right after the other, or even several experiments running simultaneously. The only requirement is that you should have a single conversion point for all of your Google Website Optimizer experiments. You may be able to adapt this code to situations with multiple conversion points, but that's likely to get rather complicated. So why use this code? Oftentimes your conversion point is a page that you're not really wanting to edit a lot, or may even be able to edit a lot. Instead of having to update your conversion page every time you set up a new experiment, you just add this code to your conversion page once and forget about it. It will register a conversion for all current and future experiments, and will even accommodate visitors who may be part of more than one experiment. So here's the code:

Check Landing Page Performance by Browser

October 6, 2009

browsers.jpgEvery browser is different.* Ask any web designer about their craft and you'll eventually get them talking passionately about these differences. How Internet Explorer 6 renders CSS pseudo-elements (badly) and handles padding and spaces (randomly). How IE7 ignores CSS drop shadows. How floating divs never seem to work the same way in any of the browsers. These peculiarities have driven many a developer to strong drink.

When it comes to testing new webpage designs in Google Website Optimizer, speed can be essential. You want to get the experiment out the door as soon as possible so you can get preliminary data. Sometimes this means that things slip through QA. Browser testing is exceptionally finicky and time consuming. Not every office has a spare Mac sitting around, and with three different versions of Internet Explorer still in wide use—and no easy way to install all three versions on a single PC—it's no small feat to make your page variations all work perfectly in every popular browser.

With just a few Google Analytics Advanced Segments in your arsenal, however, you'll be able to see whether or not your new pages are functioning fine in all the right browsers. Hit the jump for details.

Five Google Analytics FAILS

August 21, 2009

FAIL Stamp
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.

utm_nooverride FAIL

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.

ecomfail.jpgYou'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.

Copy Filters in Google Analytics

August 6, 2009

copy_filter.gifThe Copy Profiles Greasemonkey script now allows you to copy filters from one Google Analytics account to another. Simply go to the Google Analytics account that has the filters you want to copy. Go to the Filter Manager. Check off the boxes for the filters you wish to copy and hit the "Copy" link located in the column header.

Once you've done this, navigate to the Google Analytics account that you want to paste the filters into. Go to the Filter Manager again and click the "Paste Filters" button.

Now sit back and watch it go.

Again, this script is actually an addition to the Copy Profiles script. If you already have the Copy Profiles script, you'll want to download it again to get the filter copy feature. Here are the steps for everyone else:

  1. Get Firefox
  2. Get Greasemonkey
  3. Get the Copy Profiles script

Both this post and the previous post will give you the same script. For those who haven't been following along, this script is a separate script from the GARE, at least for now.

That's it! I'm fresh out of scripts. If you think of an improvement to this script or find a bug, let me know. I wouldn't mind hearing from you if you've just plain found this script useful either :)

Copy Profiles in Google Analytics

copy_profile.gifI've written a Greasemonkey script that allows you to copy and paste profile settings from one profile to another. This includes main website profile information, goals, filters, and users. Hopefully this will save you some time in situations where you need to create multiple profiles that share a lot of the same attributes.

The best way to understand exactly what this script does is to download it and try it out:

  1. Get Firefox
  2. Get Greasemonkey
  3. Get the Copy Profiles script

The profiles have to be in the same account, but hopefully that won't be too limiting to anyone. I actually spent a significant amount of time getting this to work across accounts, but decided that wouldn't be the best for several reasons:
  • The main profile settings are rarely the same for profiles across accounts.
  • The goals are rarely the same for profiles across account. If you want to copy goals across accounts, I would recommend getting Lunametrics' Goal Copy add-on.
  • Some filters may be the same across accounts, but there's a danger of accidentally copying filters that reveal too much about a particular account if you simply copy all filters from one profile to the other.
  • Ditto for users.

If you think I'm wrong and you'd really like to be able to copy profiles across accounts, let me know why and I'll see what I can do. Or if you're into writing Greasemonkey scripts, you could always write the script yourself. I'd be very interested to see it when you get done.

I purposefully wrote this script so that it wouldn't break in the way that these types of scripts would normally break. It's possible it could break in other ways, so let me know if you see any issues.

You should have no problems using this alongside the GARE. It will most likely be included at some point depending on the response I get.

I have one additional script idea that I may release today, tomorrow, later, or not at all. It might be easier to guess this one.

Refresh Rate: the latest addition to the GARE

August 5, 2009

Img-water.gifAs some of you may have noticed (Amit), there has recently been a new addition to the Google Analytics Report Enhancer. Refresh Rate is a new metric that was conceived of by Caleb Whitmore of Google Analytics Authorized Consulting firm Analytics Pros. This metric gives you a great way to measure user engagement at the pageview level. I could say more, but Caleb has written a fantastic post that gives the whole story on Refresh Rate, of which the inclusion into the Report Enhancer is but a small part.

Now that Refresh Rate has joined the GARE family, it's a great time to download the latest version of the Report Enhancer. Here are the steps:

  1. Get Firefox
  2. Get Greasemonkey
  3. Get the GARE

The latest updates to the GARE include:

  • Refresh Rate
  • New Dimensions:
    • Market (Thanks to Caleb again for this one)
    • Hour of the day
    • Day
    • Week
    • Month
  • Additional Segments for Secondary Segmentation and Pivot Tables
  • Improved Advanced Segment handling
  • Improved Data Sampling Handling
  • Deselect All Visits for two or more Advanced Segments

And just in case that wasn't enough for some of you (Amit), I'm planning on doing another post either late today or early tomorrow to reveal a new Greasemonkey script that I've decided to release independently of the GARE for now. So you may want to stay tuned :)

Tracking Transactions back to the Initial Referrer with Google Analytics

May 21, 2009

first touch

Google Analytics, by default, will attribute transactions to the last referrer. While this is all fine and good, there are some situations where you would really like to be able to track these transactions back to the initial referrer rather than the last referrer. For example, you may be spending money on AdWords traffic to get visitors to the site initially, but many of the actual transactions aren't occurring until later when they've returned to the site organically. You can change your Google Analytics Tracking Code so that it credits these transactions to the initial referrer rather than the last referrer, allowing you to get a better handle on the return for your paid marketing efforts. One issue with changing your Google Analytics code so that it gives transaction credit to the first referrer rather than the last referrer, however, is that this is a permanent change affecting all profiles. You can't have one profile that gives first referrer credit and another profile that gives last referrer credit because both profiles will use the same set of cookies, even if those profiles use separate account numbers. You can work around this, however, by using a local, modified version of ga.js. The original ga.js modification and idea comes from John Henson at Lunametrics, though I've tweaked a few things for my own purposes. His post that I'm referencing isn't directly related to this modification, but there are some tie-ins to the overall idea of using different cookies. If you want to switch all of your profiles over to track initial referrer rather than last referrer, you can just use the following code:

5 Advanced Segments for Ecommerce Analysis

May 15, 2009


Back in the day when I was but a wee web analyst, if I wanted to segment my website traffic data with Google Analytics, I had to use filters. This meant a lot of upfront work, a flimsy and fragile analysis environment, and way too many profiles.

It was also pretty limited. I could segment by dimensions and a select handful of metrics only. If I wanted to see only the traffic that came from a specific source and then bought a high priced item from my online store, I was out of luck.

Now, though... Now we have Advanced Segments. You kids are so lucky these days with your iPhones and text messages and Advanced Segments. Why, in my time we had to work for our segmentation.

Instead of complaining about the past, though, I guess I'll just look to the future with five advanced segments that can help you breeze through your own analytics ecommerce data. Hit the jump for more information on how you can start slicing and dicing your way toward better insights about your sales.

Get ga.js code for your Google Website Optimizer experiments

January 9, 2009

roi_logo.gifAs part of the expanding scope of the Google Analytics Report Enhancer, you will now be able to see the ga.js equivalent code for your Google Website Optimizer experiments.

In addition, I have also added checkboxes that will allow many of your to quickly modify your code for tracking across subdomains and/or multiple domains. These options will also be available whenever you create new profiles in Google Analytics or check the status of your profile data.

This is an extension of Shawn's valuable post on installing Website Optimizer if you use Google Analytics. The Google Analytics Report Enhancer can simplify this process, but you should still refer to the post for additional details on where everything goes, how everything works, and handling specific situations.

If you need the latest version of the GAREnhancer, click here.

The GAREnhancer is a Greasemonkey script. If you don't have Greasemonkey, you can get it by clicking here.

If you have no clue what the GAREnhancer does, you can read the original article by clicking here

I have also added a feature to alert you if a critical update for the script is available. If you see the words "Update Needed!" next to the Report Enhancer logo in the header, you can click them to download the latest version of the script. Once you've installed the updated script and refreshed the page, the image should no longer be visible.

There's probably a lot of ways this new feature can be improved, so leave a comment if you think something else should be added, or if you found this script particularly useful.

If you would like some additional help with the topics discussed today, you might want to check out the versatile Support Plans we offer.

Excluding Robot Traffic in Urchin 6

December 19, 2008

robo_16.gifIf you are using the IP+User+Agent method to track visitors in Urchin 6, you've probably noticed that quite a bit of your traffic is actually robot traffic:

While it's interesting to see this activity broken out, most of the time you're better off excluding it from your reports.

Website Optimizer Wednesdays - Google Website Optimizer and Google Analytics Renew Their Vows

November 19, 2008

woacrings.jpgMore than a year and a half ago, my co-worker Shawn Purtell and I were on a red-eye flight to Raleigh. We had just spent two days at the Googleplex immersed in Google Analytics and Google Website Optimizer and our minds were reeling. While I tried unsuccessfully to get some much-needed sleep, Shawn kept going on about combining the multivariate experiment data from Google Website Optimizer with the more detailed metrics in Google Analytics.

I'm pretty sure that I slept most of the weekend (I don't take jet lag very well), but Shawn went straight to work on figuring out the GWO JavaScript and getting to the bottom of the combination algorithm. He returned to the office on Monday with the whole thing pretty much figured out. After a few days of testing, Shawn shared his method for inserting Google Website Optimizer combination data into Google Analytics reports:

Google Website Optimizer uses a single metric, conversion rate, to determine which combination of variations is king. But what about other metrics that may be just as valuable, like Page Value, Avg. Time, Conversion Rates for multiple goals, Bounce Rate, Exit %, and Full Navigation Analysis? What if you want to segment your traffic or filter out internal hits? Well, now you can find out just about everything you want to know about combinations by using Google Analytics.

He raises a great point. Google Website Optimizer is all about conversion rate, but in many cases, that's not the best metric for the job. Since posting his script back in April of 2007, we've had thousands of downloads. It's clear that others agree with Shawn. So does Google, it appears, because they've just made it a lot easier to integrate Google Website Optimizer and Google Analytics.

Read on for more about official updates to the marriage between Google Analytics and Google Website Optimizer.

Website Optimizer Wednesdays - Excluding Internal Traffic

October 22, 2008

Google Website Optimizer experiments use 4 different types of scripts. In a nutshell:

  • Control script - Determines which combo to serve up
  • Section scripts - Determines which areas to swap out
  • Tracking script - Registers visit
  • Conversion script - Registers conversion

To exclude ourselves from the reports, we only need to modify the tracking script and the conversion script. By only modifying these sections, we can see the page exactly as our visitors see it without skewing our test results.

Here's the way your tracking script looks "out of the box":

If we're already using Google Analytics, we'll want to properly integrate our Google Website Optimizer code with our Google Analytics Tracking Code. Check out Shawn's excellent post on the subject if you want to know exactly how to do this. For simplicity's sake, we'll use the above code as our base.

Now let's say we are excluding our own traffic by setting the user defined value to "internal". When we do this, the user defined value is stored under a cookie name "__utmv".

Using regular expressions, we can check for the existence of this cookie and its value and only run the Google Website Optimizer tracking script when the cookie exists with the correct value:

Note that our conversion script should be the same as above, only replace "/test", with "/goal".

Now if you have a static ip address, you can also exclude based on that ip address, but this will take some server side code. We'll use php as an example:

This would exclude all traffic from Google Website Optimizer tests coming from the IP address 12.34.567.890.

As a footnote, these same ideas that we explored above can be used to do even more with our Google Website Optimizer experiments. We could, for example, modify the scripts so that only AdWords traffic shows up in our Google Website Optimizer reports. For a heavily AdWords-driven business, this would help tailor experiments to more closely match the most often used Google Analytics reports.

To learn more useful testing tips sign up for our Google Website Optimizer Training Series starting January 8th. This two session training series will encompass landing page principles, an intro to testing and advanced testing. Join us for the GWO Training Series!

Want more of Website Optimizer Wednesdays? Check out the rest of the series!

Exclude Internal Traffic from GWO | Optimize Your Call to Action | Landing Page Relevance | Choosing the Right Test Page | GWO and GA Renew Their Vows

Google Analytics Report Enhancer Updates

October 21, 2008

BREAKING UPDATE! I had to make an update to the GAREnhancer Monday, March 9 at 10:00am ET due to recent interface changes. If the script is broken is broken for you, re-download the script and you should be all set.

It's handy!

I've decided to create a separate entry for some of the latest updates to the GAREnhancer Greasemonkey script. Most of these are just small things that can make your Google Analytics (and now Google Website Optimizer) life a little easier.

If you need the latest version of the GAREnhancer, click here.

The GAREnhancer is a Greasemonkey script. If you don't have Greasemonkey, you can get it by clicking here.

If you have no clue what the GAREnhancer does, you can read the original article by clicking here

Here's a quick summary of the most recent changes:

Tracking a Section with Google Analytics

October 16, 2008


If you've read Shawn's Article about tracking autoresponders, you know that Google Analytics' Site Search tool can be utilized to track secondary sources. Toward the end of this post I'll give you a way to use Site Search to track the effectiveness and value of a section, such as a blog section, as well as a page's contribution to conversion rate as a member of that section.

But first, a little background info:

If you've spent any time in the Google Analytics reports, you've probably noticed the $index field in the Top Content reports that somehow represents a page's relative worth. This field can be a great way to get an idea of a page's contribution to the success of your goals and ecommerce revenue.

But where do the numbers for $index even come from? If you click the question mark button next to $Index in the Top Content report, you will receive the following explanation:

"The average value of this page or set of pages. $Index is (Ecommerce revenue + Total Goal Value) divided by Pageviews for the page(s)."

Now it turns out that there are a few subtleties that are not indicated by the definition. For starters, the formula is actually using unique pageviews rather than pageviews.

Second, if you look at the $index of a page and compare it to the Per Visit Goal Value or Per Visit Value of that page (depending on whether you have a lead gen site or an ecommerce site) after drilling down into the page and segmenting by source (or medium, or source/medium if you've installed my Greasemonkey script), chances are very good that the two values are relatively close, but certainly not equal.

Why is that? Here's why:

Urchin 6 Update

August 7, 2008

urchin.gifGoogle has just released Urchin 6 - Service Pack 1. There are some very important additions to this new version of Urchin 6.

First, several of the old Urchin 5 helper scripts have been revised and modified for Urchin 6:

Email Yourself Reports! - You can use this script to retrieve data from the urchin.cgi engine and print a text-based report, which can be emailed, converted to HTML, etc.

Discover Processing Errors - This script will parse the Urchin 6 scheduler history file for errors for a particular date and print a notification if any profile exits with a non-zero exit status.If desired, the runtime output from each failed task can be printed inline.

Manage Your Logs! - If you are in need of a system of log management, this script will be very handy. This script rotates the specified logs and names them with yesterday's date. The script also restarts the web server with a specified command and optionally compresses old logs and removes them after a certain period.

In addition to these scripts, a totally new feature has been added which enables you to perform user management at the command line. Using the uconf-manager, you can add, delete, and update user records without having to go into the Urchin Administration Interface.

The uconf-manager also allows you to reset the admin password and move users to a different account, tasks that cannot be done using the Urchin Administration Interface. You can also use the uconf-manager to automate the process of user creation, saving you valuable time and eliminating frustration.

ROI Revolution is an Urchin 6 reseller and so if you are ready for Urchin 6, go to to purchase or upgrade to Urchin 6 today!

Google Analytics Report Enhancer

June 26, 2008

UPDATE: You can read about the most recent updates to the GAREnhancer here, but the same script is available from both this post and the new one.

It's HandyA few weeks ago, Shawn wrote an article on true time on site and how you can calculate it. You may also know that for a while, Google Analytics actually calculated time on site using this method before reverting back to the calculation method used now.Several weeks ago I came out with an article on a Greasemonkey script I'd written which added several segments to the usual segment drop down.

I'm about to tie all of these together.

Introducing, the Google Analytics Report Enhancer!


Segmenting by Source/Medium and other stories

May 9, 2008

segment by source/mediumUPDATE: This script has been superseded by the GAREnhancer. All future updates will be made to this new script.

Have you ever gone to segment the content detail of a page by source/medium, only to find that you can segment by source or medium, but not both? Well those days of frustration are over, thanks to a Greasemonkey script I wrote just the other day.

Not only that, but you will also be able to segment by transaction, adgroup, and referral path anytime a segmenting opportunity comes up. Now you can see exactly which transactions are attributed to each source, medium, source/medium, keyword, campaign, new or returning visitors, and more. I'm sure everyone can think of some good uses for this.

To expand your segmenting abilities, first download the latest greasemonkey firefox add-on. Then download my script right here. You should be able to just click and install it if you already have the Greasemonkey firefox add-on installed.

A couple notes here about the script:

1. If you segment by one of the fields, then try and segment by another field, you may find that your options are once again limited. To fix this, segment by "none" first and then you should get the additional fields back. UPDATE: This issue has been resolved as of 06/06/08. Just re-download the script.
2. You can also segment by Product, Product SKU, and Product Category, but this may not work as well as anticipated. If that's the case, you can drill down into a product and segment by source/medium or whatever report you were looking at and see the data from the other direction.

If you've found this tool useful or if you have any suggestions for improvement, please leave a comment. Thanks!

UPDATE: I have a new script which adds a few additional fields to segment by, such as exit pages, page titles, browser and OS combined, and others. There are also some more obscure fields whose purpose is not obvious, so if you find one of them useful then let me know how you used it! Here's the script.

Note that if you have both scripts enabled at the same time, the second script in the list will override the first. Also, this second script makes your segment drop down rather long, so you may just want to stick with the first. I felt I should provide it, though, for completeness.

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Google Website Optimizer Graduates from Google Beta

April 16, 2008

Google Website Optimizer GraduatesThey grow up so fast, don't they? Today at ad:tech in San Francisco, Google announced that its multivariate testing tool, Google Website Optimizer, was coming out of beta and getting its own digs. Here's the official announcement.

Up until recently, the only way to use Google's free tool to test and improve your website's content was through a tab in AdWords. Now that Google Website Optimizer has moved on to the big leagues, it has a new standalone website independent of AdWords, where you can log on and start running tests right away.

Here's a look at the new multivariate walkthrough:

Google Website Optimizer Screenshot Thumbnail
Google Website Optimizer Screenshot 2 Thumbnail
Google Website Optimizer Screenshot 3 Thumbnail

Read on for a list of new improvements and support options...

Tracking Subdomains

March 27, 2008

Dive Subdomain, Dive!One of the most important things to consider when trying to set up Google Analytics for your site is the integrity of your visitors' source/medium data. Keeping this data as accurate as possible will go a long way to helping you make useful decisions about your marketing efforts.

That being said, there is a silent enemy threatening to destroy the harmony of your Google Analytics data: the self-referral. You may first see it rear its ugly in head in the All Traffic Sources report. Not only is it rather disconcerting to see your own site as a visitor's referrer, but this entry in your reports represents irrevocably lost data. What's worse, you may even notice that the conversion rate for this segment of traffic is actually quite good. You may be putting lots of time and money in SEO, paid online adversing, e-mail campaigns and print ads, but when someone asks which of these was responsible for the conversion, you really don't know. Some of those sources may be getting overwritten by your self-referrals.

If your site has subdomains ( and, for instance), this might be causing the self-referrals to show up in your reports. The standard Google Analytics Tracking code is only good for sites with a single domain and no other structural complications. Anything beyond this and you'll need to make some kind of modification to the script. Subdomains are one such complication.

Whenever a visitor comes to your site, the Google Analytics Tracking Code on your pages asks the visitor's browser a question:

Google Analytics Keyword Sleuth vs Search Query Performance Report

March 24, 2008

If you've been following this blog, you've likely heard several references to the Google Analytics Keyword Sleuth that Michael Harrison wrote back in April of 2007. This is a tool that anyone in paid search should be using. Basically, it captures and displays an ongoing list of new keywords and phrases straight from your customer's mind. We're often advised to "imagine what your customers are typing before they see your ads, then bid on those keywords." With the Keyword Sleuth in place, you don't have to imagine anything. They've already told you.

For a long time, Google, Yahoo!, MSN and others would not reveal exact search queries, and still don't for the most part. They'll tell you the bid keyword, but not the exact search query. In May 2007, Google stepped up and created the Search Query Performance Report (SQPR), which now shows this data within the Adwords reporting tab. There was a wave of excitement when Google released the SQPR, and it's become a popular report for Adwords users.

Both the Keyword Sleuth and the SQPR were developed to do essentially the same thing, but in reality, they can be worlds apart for the PPC manager. In explaining the Keyword Sleuth to other PPC professionals, I'm often asked how it's different than the Adwords SQPR. There is a lot that is different. A side-by-side comparison between these two tools is long overdue.

First, I'll run Google's SQPR. When that's done, I'll retrieve the same data using Michael's Exact Keyword Sleuth. In summary, I'm gathering the same data from the same Adwords campaign and the same time frame (one month), using two different methods. My teammate Matt will time it from the moment I touch the keyboard to the moment the report is viewable on screen.

The results...

Google Analytics Benchmarking in Beta

March 5, 2008

ScalesToday, Google announced new benchmarking functionality within Google Analytics. Combined with a new data-sharing option, this will allow Google Analytics users to compare their site's data against aggregate data from other sites in various industries. These two new features are in beta, but should begin to show up in all Google Analytics accounts throughout the day.

Click to enlarge

Also briefly mentioned was the unveiling of the Audio Ads integration, with an official blog post to come tomorrow.

For more information, check out the official announcement at the Google Analytics blog, the benchmarking FAQs, and the data-sharing FAQs.

Update to Matching Specific Transactions to Specific Keywords

February 18, 2008

Money ShirtShawn wrote an article back in May which showed you how to use filters in Google Analytics to modify your transaction list to see source, medium and keyword data for each transaction. As many of you have noticed by now, there have been some issues since January 15th involving custom fields which have caused this and other advanced filters to stop working.

Since then, we have found a way around using custom fields for this particular set of filters. Your reports will look and function as before.

Here are the details:

Exact Keyword Tracking with ga.js

February 14, 2008

Sleuth! Magnifying glass icon.Last April, I posted a script that allowed paid search advertisers to view the exact search queries of their visitors. This was essentially a free tool that gave website owners the ability to weed out ineffective keywords and put more money toward the precise phrases that were really driving their business.

Google Analytics doesn't do this out of the box. It will tell you exact search queries for visits from organic listings, but for paid search, you're stuck with the keywords that you're bidding on. With broad and phrase matching, these could vary pretty drastically from what the visitors typed into the search engine.

We've gotten a lot of requests to update the script for the new version of the Google Analytics JavaScript, ga.js. Always happy to oblige, we've been hard at work on our new version of the Google Analytics Keyword Sleuth. Call it a Valentine's Day gift from ROI Revolution to you.

Keep Track of Changes to Your Profiles

January 16, 2008

we're painting the people redIt's hard to get things right the first time. You may come up with a brilliant plan for your Google Analytics setup and think that you've thought of everything, only to have the data start coming in and realize that things are not looking quite like you hoped they would. Or perhaps your analytics just need a modification and you need to change your goal steps or create new ones. When these kinds of things happen, you may need to alter your Google Analytics profile settings.

And that's OK. While we recommend setting up a "sandbox" profile where you can test what effect changes to your profile might have on your data before editing your main profile, at some point you'll have to make those changes live in order to reap the benefits of cleaner, better data. When this happens, you will want to record those changes.

Some Thoughts on Exit Rate and Bounce Rate

January 8, 2008

chimpanzee_thinking_poster.jpgI was thinking the other day about the relationship between exit rate and bounce rate. It's often assumed that there's some type of mystical relationship between these two metrics, so I thought it would be worthwhile to dig deeper into this relationship to see what's actually going on.

First, we can define these measurements using rather simple equations.

exit rate = exits / pageviews
bounce rate = bounces / entrances

Now if we think about it, every visit to your site has an entrance. And unless you have visitors who stay active on your site 24/7, taking 15 minute power naps in lieu of actual sleep just to keep their current session alive, every visit to your site will also have an exit. Therefore, if we're talking about the exit rate and bounce rate of your site, we can say that entrances = visits = exits and make the appropriate substitutions in the above equations:

exit rate for the site = visits / pageviews
bounce rate for the site = bounces / visits

This would seem to indicate that if the number of visits increase then exit rate will increase while bounce rate will decrease, and alternatively, if the number of visits decrease then exit rate will decrease while bounce rate will increase. Of course, this assumes that visits are independent of both pageviews and bounces, which they aren't. So to understand this relationship, we have to think about the quality of visits that we're getting to the site.

Goal Matching Revisited

December 26, 2007

Almost a year and a half ago, I posted a brief guide on the different match types that Google Analytics uses to define goals. For something that is so integral to a successful Google Analytics configuration, goals are easily one of the more confusing aspects of the tool, and we get more questions about goals than perhaps anything else.

Last week, Google quietly updated the Google Analytics Goal Settings page. They rearranged the order of the fields, and also clarified something that has long been somewhat under-emphasized. In the explanation text for the Goal URL:

For the goal page "
/thankyou.html" enter "/thankyou.html"

Previously, the example text basically told users to just copy and paste the entire URL from their conversion page. Now, only the Request URI is required.

Actually, this isn't a change to the way that Google Analytics recognizes goals. It's always worked this way, targeting only the Request URI. It would simply discard anything in the Goal URL that wasn't part of the Request URI (anything after the dot-com, basically) and match what was left.

Now that the official recommendation is to use the Request URI, it looks like old-school goals are still backwards-compatible and will function with the whole URL. But for future reference, for a goal URL of:

You only need to put:


Into the Goal URL field.

How do you use Google Analytics' Goal Matches? Are you a regular expressions junkie, or do you stick to tried-and-true exact match? Leave us a comment!

Google Analytics ROI Calculation Macro

November 26, 2007

Glue Gun!If you have used the ROI Calculator Spreadsheet tool that Shawn came out with before, you know that it takes several steps to get to the point where you can start entering in cost data and seeing that ROI. If your need for ROI data is only occasional, then this works great. In addition, if you click on the appropriate link below, you can download the latest version of this spreadsheet, which eliminates step 4 from Shawn's procedure.

Microsoft Excel 2007 Version
Microsoft Excel 97-2003 Version

If, however, you find yourself running through these steps again and again on a frequent basis with no shortcut in sight, there is hope!

Introducing...the ROI Calculation Macro.

Custom Segmentation: It Slices, It Dices (Your Data)

October 28, 2007

cheeseslice.jpgSo, a few months back I posted on how to view the exact AdWords search queries your visitors use to reach your site (a feature that is, so far, unsupported out of the box with Google Analytics). My method involved grabbing that keyword phrase and storing it within Google Analytics' User Defined field. In the article, I said:

"There are lots of great applications for the User Defined variable... If you can get by without using it, you can then save the User Defined field for something else that might prove more powerful. Like tracking search terms. :)"

I'll be the first to admit that this statement is a little wishy-washy. What are these great applications? Why save it for tracking exact search queries? What precisely does the User Defined variable do?

In a nutshell, you use the User Defined variable to perform custom segmentation on your visitors. Google Analytics already provides a number of built-in segmentation features. It's so intuitive, most users probably aren't even aware that what they're doing is segmentation. From your Traffic Sources report, you see a specific group of visitors that came in from a specific source, and you click the hyperlink. Now, you're looking solely at the data for that source. Congratulations! You've sliced and diced your data down to a very specific segment of traffic.

So, you can segment your traffic by visitor type (new or returning), by source (where, how, why they came to your site), by organic search queries, by browsers or screen resolutions or Internet speed... but what if you want to get a little more specific?

Tales of Overanalysis: My Organic Traffic Has Tanked!

September 4, 2007

Take a pill, dude Dear Michael,
I just implemented AdWords autotagging for my website, and now my organic Google traffic has dropped dramatically. What gives? Is Google Analytics ruining my search rankings? Who do I blame for this? Can you fix it?

Okay. Calm down and breathe. There's nothing to worry about.

First, the bad news: your organic search traffic wasn't all it was cracked up to be.

But, the good news: now that you've turned on autotagging, your Google Analytics profile is more accurate than it has ever been.

More Work For the Webmasters

August 3, 2007

The Peon Says, 'More Work?'This post is dedicated to all of those hard working webmasters out there who have enough to worry about as it is without the marketing staff breathing down their necks about campaign tracking and revenue analysis and all sorts of other stuff.

Look, I'm a code monkey, too. I understand the dilemma. No one likes to ask permission from fifteen different people before they make the slightest change to a site.

But here's the thing: Google Analytics is script-based, and it collects live traffic and conversion data. If it's not on a page, and someone visits that page, they don't get counted. It's not rocket science (but I'm no rocket scientist, so I must defer to someone who is).

So if you know that the site you're working with has the Google Analytics script on it, then think twice before you make any major changes. Here's a quick list of what to consider...

Google Analytics Graphs and Charts

June 15, 2007

The Google Analytics Pie ChartOne of the new features of Google Analytics that hasn't really seen too much press in the past month (has it really been that long?) is the new and improved graph and chart view. These graphs and charts don't vary drastically from those seen in the old interface, but they're still different enough to warrant a bit of explanation.

The Google Analytics 'Views'Basically, all of the data tables in Google Analytics have alternate graph displays for easier visual analysis of your data. Accessing these additional reports is easy. There's a series of little "Views" buttons at the top right of your data table, and each button offers you a new view for your data.

More info on each view after the jump.

New Google Analytics Features

June 13, 2007

New Google Analytics Features Include These Clickable URLsAs first reported on the Official Google Analytics Blog, and then picked up pretty much everywhere else other than our own blog here, Google Analytics has seen its first minor feature update since the launch of the new user interface. While we certainly weren't first to break the news†, due mostly to putting the finishing touches on our updated Google Analytics training series, I did want to post my top three favorite improvements after the jump.

Google Analytics: Extreme Makeover Edition

May 8, 2007

thumb1.gifYes, Google Analytics has been redesigned. Please do not panic.

As several folks noticed last week, Google has redesigned Google Analytics. Log into your account and you'll be met by an announcement:

Over the next several weeks, we will be migrating all existing Analytics accounts to the new Google Analytics interface. You will be notified by email once your account has been migrated. For an entire month you will be able to access both the original interface and the new interface. During the migration, you should experience no interruption in service and you’ll be able to see all of your data regardless of which interface you use. For a sneak peek at the new Google Analytics, take a look at the following resources.

Change can be a tough thing to come to terms with. Some people might wonder why Google is changing everything just as they've started to get used to it.

We loved the old interface, too. Don't get me wrong. It's kind of like those ridiculous makeover shows on TV. Sure, you love your mom before she gets her wardrobe rebooted, but no one's complaining when she comes back minus the muumuu.

Let me assure you, this redesign is a very good thing. We've been using the new interface for over two months now, and it's made day-to-day analysis a breeze. I've had lots of time working with both, and the new one is superior in almost every way.

View Entire Referring URL in Google Analytics

Jesper Rønn-Jensen, a usability specialist who writes for one of the best blogs on UI and web standards, takes a look at the new Google Analytics interface. Jesper's still a little concerned about the number of clicks it takes to show you referring URLs down to the referral path.

We've had the chance to work with the new interface for a couple of month and I have to assure Jesper and others that it is now a bit easier to find this information. Now, on the new Referring Site report, instead of clicking on the now-missing Analysis Options icon (the little purple guy over to the left of each line item) and choosing Content from the dropdown, you just click on the referring site. This immediately shows you all referral paths from that specific domain. Very handy, in my opinion.

Check out some screenshots after the jump.

Desktop Widget for Google Analytics

April 30, 2007

vivalytics.gifWhile the ROI team were out at Mountain View last month, enjoying our training session with the Google Analytics team, we got the chance to meet Michael Whitaker of Monitus, LLC for sushi. Michael is the brains behind the Monitus Yahoo! Store Tools, which includes a really cool Web Analytics Connector that actually makes Google Analytics possible with Yahoo! Stores.

It was great to actually put a face to Michael's great reputation in the Yahoo! Store development field.

vivalytics2.gifMichael surprised us, though, with a sneak peek at his cool new VivAlytics Widget. This little tool allows you to track defined Key Performance Indicators for multiple Google Analytics accounts, profiles, reports, whatever. Find out whether a specific metric has increased or decreased over a given week or month. It's a really great resource for people who might be too busy to log into their Google Analytics account every day, but who still want to see how their websites are performing.

Not too long after we got back to Raleigh, Michael quietly made Vivalytics public over at It's a free download, it's cross-platform (Mac and PC), and just requires the (also free) Yahoo! Widget Engine. Do yourself a favor and take it for a test drive.

Exact Keyword Tracking with Google Analytics, Revisited

April 23, 2007

title.gifUPDATE: We have posted a new version of the script mentioned in this article at Exact Keyword Tracking for ga.js.

Last November, Jim Newsome of Omega Digital Media and the
GA Experts blog, posted a really clever trick on how to view detailed keyword information within Google Analytics. If you've ever searched through your AdWords Bid Terms and wondered what the actual Search Terms were, then you know why such a filter was in great demand. For PPC marketers, it's a great opportunity to weed out ineffectual broad match keyword phrases, and hone in on the most popular user search queries.

Here's an example: you've got a shoe store and you're running Broad Match AdWords ads for "shoes". When a visitor searches Google for "blue suede shoes", your ad shows up. This is all well and good, but what if you don't sell blue suede shoes?

Read on to find out how to track exactly what your visitors are searching for before they see your PPC ad and click on over to your site...

Google Analytics: Get It Right the First Time

April 19, 2007

Bad Google Analytics Source DataWe have a client that recently came on board with us after having installed Google Analytics themselves nearly a year ago. Back then, they were skeptical about our services: "Do people really need help setting up Google Analytics? It's so easy!" We had to agree that, yes, for a lot of sites, this is true: configuration is easy. Sign up, take the script, put it on all of your pages, and then sit back and start collecting data.

Unfortunately, its simplicity can be a little deceiving. There are a lot of little ifs and buts with Google Analytics. If you set up your Google Analytics profile incorrectly, it can mean huge repercussions for your data, weeks, months, even years down the road.

So when Client X finally hired us, we hopped right into their account and audited their Google Analytics profiles. What we found just further confirmed what any Google Analytics Authorized Consultant already know: setting up Google Analytics is not always a cakewalk.

Here's what happened, and let it stand as a warning to ye who may venture forth in similar fashion. Our client has a single site with multiple subdomains. For those playing along at home, this requires the addition of a parameter to tell Google Analytics how to assign and manage cookie data.

Here's to Avinash!

March 6, 2007

Avinash KaushikAvinash Kaushik has been blogging for nearly a year, and in that relatively short amount of time, he's cemented himself as one of the premier web analytics experts in the blogosphere. Today, Avinash announced on his blog that he'll be leaving Intuit, where he has worked as Director of Web Research and Analytics since 2003, and will be striking out as an independent consultant.

We'd like to congratulate Avinash on this exciting new opportunity. It takes a lot of guts to go indy, but if this means more time for him to write more great blog articles, then I don't think Avi has anything to worry about. Plus, his first assignment is working as an Analytics Evangelist for Google. He's going to be spreading the word about analytics, and working with the Google Analytics team on speaking and education engagements. I can't really think of any better representation for the tool.

All this just a couple of months away from the release of his much-anticipated new book, Web Analytics: An Hour a Day. If you need proof of how great a guy Avinash is, he's donating all proceeds from this book to two great charities, The Smile Train and Doctors Without Borders. We've already pre-ordered two copies for the office, and if you have any interest in web marketing or analytics, you should head over to Amazon and do the same. For more information on the book, check out its official page: Web Analytics: An Hour a Day, by Avinash Kaushik.

Breaking Up Is Hard To Do

Barbie 'n KenYesterday, I wrote about tracking your website's visits to both Google Analytics and Urchin. Today, I'll answer a different question: can you track visits from a single website in multiple Google Analytics accounts? Certainly not as popular of a question, but still one that we're asked from time to time.

First things first, you'll need to understand the difference between a Google Analytics account and a Google Analytics profile.

Your GA account is tied into your Google Account, which is a single-entry login point that gives you access to most of Google's free services (Personalized Homepage, Personalized Search, Google Groups, etc.) If you're logging into Google Analytics, then you already have a Google account (but, contrary to popular belief, this does not necessarily mean that you have a Gmail account).

Your Choice: Urchin, Google Analytics... or Both?

March 5, 2007

Ayyyyy!A lot of our Google Analytics clients are Urchin Software users of old. Many of them hopped on the script-based bandwagon when Urchin introduced its UTM method, which combined traditional log-based tracking with a snippet of JavaScript that wrote and parsed cookies for greater accuracy over multiple sessions.

The natural progression was then to Urchin On Demand, which was entirely hosted and exclusively dependant on JavaScript. When UOD was rebranded as Google Analytics, we helped many of these clients migrate over. Because many had purchased Urchin, or had an Urchin installation through their hosting provider, they wished to track their sites on both the new Google Analytics service, as well as via tried-and-true Urchin.

If you're analyzing logfile traffic in Urchin using the "IP + User Agent" tracking method, you're fine. The standard Google Analytics tracking code will integrate seamlessly with your website. If, however, you are using the UTM method, you will need to make a few minor modifications on your site.

Tracking PayPal Transactions in Google Analytics

February 13, 2007

00_paypal.gifWe've had a lot of people enrolled in our Google Analytics Quick-Start Courses asking about PayPal. We've helped a few of our clients track PayPal e-commerce within Google Analytics, thanks to the Payment Data Transfer function and a bit of scripting on the back-end.

This method has only been tested with Buy Now buttons, and in all fairness, isn't much more than a hack. There are a couple of drawbacks. Because you cannot tag PayPal pages with the Google Analytics JavaScript, you will not have accurate funnel data for your e-commerce conversion goal. All converting visitors will leave your site (and move to PayPal) before coming back and registering their transaction. This will also result in an artificial hike in your total visits. That being said, it gets PayPal transaction data into Google Analytics, and is also relatively easy for those who are familiar with HTML, scripting, and general web development. Not everyone is going to understand this stuff, and if you find the whole mess a little too much, we're happy to help out with one of our Google Analytics support plans. Otherwise, read on and learn about how to track your PayPal transactions in Google Analytics.

Track AdSense

January 30, 2007

We've had quite a few questions about how to track outbound AdSense clicks from a website using Google Analytics. There's an older post (from 2005) over on Aaron Wall's SEOBook blog, but it should still work. Check out how to track Google AdSense clicks in Google Analytics.

Understanding Google Analytics' Data Over Time Report

November 1, 2006

headline.gifWhile the Google Analytics Help Center is, for the most part, well-written and comprehensive, I've gotten a lot of questions in the past about the Analysis Options feature. In case you're unfamiliar (and if you are, you're really missing out... this little options.gif button is one of the most powerful features of Google Analytics), I'll quote from the official source:

The Analysis Options icon provides access to:
  • Data Over Time shows the values for the selected page over a selected date range.
  • Overlay Page loads the Site Overlay report for the selected page.
  • To-date Lifetime Value calculates that page's values since Analytics tracking began.
  • Cross Segment Performance breaks the page's data down by the specified variable.

That's actually the entirety of the article that deals with Analysis Options. That's it. There's nothing more. Which is unfortunate, because it's such a downright effective tool. I get a lot of questions about each Analysis Option, so I'm going to spend some time over the next couple weeks detailing each individual report.

To start with, we'll go over Data Over Time. Contrary to the explanation given by Google, Data Over Time does more than display values "for the selected page" over time. You can also use it to measure visitor segments, campaign conversion rates, average revenue, and product performance, all over a customized period of time. This is very useful for trending, and for a quick at-a-glance view of your site's performance over the days and months.

Using Google Analytics to Track Google Checkout Orders

October 13, 2006

googcheckout.gifSome really great news over at the Official Google Analytics Blog. Merchants using Google Checkout can now track purchases made on their site with Google Analytics. The procedure is outlined here.

Guess this is just another example of "features, not products".

Tracking Multiple Domains

September 26, 2006

Justin Cutroni has yet another great series of articles over at his blog, all about common Google Analytics configuration mistakes. His most recent post discusses third party domains, and getting Google Analytics to track across them. As usual, it's well-written and very informative.

One thing that many people don't know, however, is that, by default, Google Analytics will track only the request URI of its tagged pages.

What's the URI, you ask? Take a look at the URL below:

Hostname and URI explained

You see that the part of the URL that is surrounded by red is "/index.htm". So, when a visitor hits the page above, Google Analytics registers a unique visit to "/index.htm". Because the majority of Google Analytics profiles are focused on only one domain, the hostname (surrounded by blue) is ignored in the reports.

But what if you have two domains? And what if you have pages on both domains that have the very same URI?

View Visitor IP Address in Google Analytics

September 20, 2006

View Visitor IP Address in Google AnalyticsThere's no way to view your visitors IP addresses right out of the box with Google Analytics. You can view visitor location and ISP in Marketing Optimization > Visitor Segment Performance, under the Domains and Geo Location reports.

But surely Google Analytics must collect the IP address, or there's no way that it could calculate visitor location and ISP.

In fact, it does collect this data from each visitor that accesses your site. Better still, the data is easily accessible with a fairly straightforward Advanced Filter and the User Defined variable. Here's how.

Google Analytics Gadget for Google Desktop

September 11, 2006

analyticsgadget.gifCamden Daily and Chris McKeever have whipped up this nifty little Gadget for the Google Desktop program. It doesn't give in-depth analysis of your GA data, but it's worthwhile if you're interested in keeping an eye on hourly and daily numbers without logging into your account:

See your visitor statistics in real time without leaving the comfort of your desktop. This little guy plugs right into your desktop and pulls all your Google Analytic profile Data in daily and hourly views.

Click to download.

More Profiles Means More Control

August 1, 2006

It's official. Google has increased the number of default profiles for a Google Analytics account from 5 to 10. Why does that mean more control?

Well, with more profiles comes the ability to restrict a user to only those sites for which they need access. You can track subdomains and subdirectories separately in a new profile, and if you've filled up the four goals available in your main profile, just create a new one for the same website and set up some new goals. You don't even need to change the tracking script on your webpage.

Which Match Type Do I Use For My Goals?

July 25, 2006

When you set up a goal within Google Analytics, you have the option of including a funnel. The funnel is a series of the pages leading up to your goal action: each step in the path to requesting a whitepaper, for example, or the checkout procedure of your online store.

With traditional static websites, coming up with a funnel is a painless process. You plug in the static URL from your site into each field, give it a label, and then you're done. But if you're running a database-driven dynamic site, or need to include more than one page within a single step, you may be interested in the additional Match Types available for funnel creation.

Below the Define Funnel form of each Goal Settings page is a section called Additional Settings. Here you'll find a number of options to help you closely identify the steps of your website funnel, even if those steps are a bit more complicated than a series of URLs.

New AdWords Keyword Positions Report

June 27, 2006

The Google Analytics team have really been busy, it seems. In addition to the extremely useful AdWords Analysis report released early this month, it looks like they have unveiled a new tool for AdWords advertisers: the AdWords Keyword Positions Report.

Where do your AdWords ads appear on Google search results pages? How does each position convert for your particular keywords? Drill down from any keyword to see its display position: T1 through T3 indicate that your ad was promoted to the top of the search results page. Positions 1 and higher indicate a position in the right-hand location.

So you can see how your ads perform while in specific positions and use Position Preference from within AdWords to target your highest-converting spot.

This is some very powerful stuff here. Two really great reports in just one month. Anyone else wondering what else is up their sleeves?

Hat tip to Andy

Transform Google Analytics Reports into PowerPoint Slides

June 20, 2006

Robbin Steif details a pretty cool application that takes Google Analytics xml data and builds a set of PowerPoint slides detailing the reports of the profile. While Google Analytics has an easy-to-use Dashboard for Executive, Marketing, and Webmaster staff, this tool is great for presenting a dataset to folks who may not have access to GA itself. It's definitely worth checking out.

Via LunaMetrics

Google Analytics and the Extended Sales Cycle

June 9, 2006

Some organizations have extended sales cycles spanning multiple visits to the site, with unusually large amounts of back-and-forth between the site and the user. Typically, knowing what drove a visitor to the site immediately prior to their conversion is what's important to a marketing team, but what if we want to keep track of what initially led the visitor to the site? In these cases, the initial referrer is more valuable than what got them to the site the second, third, and final time. It provides essential intelligence about attrition rate, customer loyalty, and ROI.

In our experience with such clients, we have encountered some very intriguing challenges while implementing Google Analytics. One of these clients, a leading physician in his field who performs elective operations on patients who travel from all over North America to see him, receives a large amount of paid traffic from many of the major search engines.

Sounds like every other website, doesn't it? Well, here's the rub. The client's sales cycle is long enough that visitors are hitting the site multiple times before their final conversion. There are a number of steps along the way where our referral information can get overwritten. Let's take a quick look at the entire process.

New Google Analytics AdWords Analysis Report

June 2, 2006

New Google Analytics AdWords Analysis ReportSome very exciting news for Google AdWords customers currently using Google Analytics to monitor CPC performance. Google has added a new report to the Marketing Optimization set that gives a very quick and easy drilldown into all AdWords campaigns, ad groups, and keywords. Behold the brand new, immensely useful AdWords Analysis report.

Impressions, Cost, Clicks, CTR... everything available from within the AdWords Campaign Summary is here, but you also get the great Revenue and Cost-Per-Conversion stats that Google Analytics offers, all in an intuitive, easy-to-use interface.

Say Goodbye to Expensive Analytics

May 19, 2006

istock_000000289638smaller.jpgIntuit's Avinash Kaushik started blogging earlier this week. The blog is called Occam's Razor after William of Ockham's famous principle: "Entities should not be multiplied beyond necessity."

Kaushik's blog has already proven to be a keenly written and enlightening read. In his latest post, Kaushik offers a few suggestions to those spending a boatload on web analytics:

  1. Apply for a free Google Analytics account at GA Sign Up Page
  2. Once you get the code implement Google Analytics on your website in parallel with your favorite expensive analytics tool
  3. Get a comfort level for delta between the two sets of key numbers (you know visitors, conversions, page views etc etc) and create a multiplier (my tool shows visitors 10% higher and page views 10% lower than Google). You will use this multiplier in future to compare year over year trends if you want to.
  4. Cancel the contract with your favorite expensive analytics vendor and take that $50k or $100k or $200k and: 1) Hire a smart analyst for between $50k to whatever maybe your areas great salary 2) Put the rest of the money in your pocket.

Makes a lot of sense when put that way, doesn't it? You can save a lot of money, just by switching to a free utility like Google Analytics. As Kaushik says, "Your smart analyst will be able to extract just as much value from GA than your old tool, in fact my prediction is that it will be a lot more."

So, basically, don't multiple your entities--in this case, your web analytics spend--beyond necessity. Turns out William of Ockham knew a thing or two about web analytics.

Hat tip to Andy Beal

Lee Odden Interviews Eric T. Peterson

May 17, 2006

Over at the Online Marketing Blog, Lee Odden has posted an interview with Web Analytics Demystified author Eric T. Peterson. As Odden writes:

"When you think of authorities on web analytics, one person that should be on your list is Eric T. Peterson."

Couldn't have said it better myself. Anyway, great questions from Odden, and, as usual, Peterson's clear, well-informed answers about the field make for enlightening reading.

Read the interview.

Customize Your Google Analytics Dashboard

May 12, 2006

UPDATE: This blog post refers to an older version of Google Analytics that is no longer available.

With over 80 comprehensive reports right out of the box, Google Analytics can get a little overwhelming for the average user. Since there is data within each Google Analytics account that can benefit each and every department of the typical organization, though, it's important that everyone have quick and easy access to the information that they need most.

That's why there are three handy predefined Dashboards available in every profile: Executive, Marketer, and Webmaster. Each provides a hand-picked selection of the most applicable Google Analytics reports for any given job. The Executive Dashboard gives fast, top-view analysis of a website's performance. Marketer Dashboard focuses on the various advertising and media campaigns driving to the traffic. The Webmaster Dashboard is a great resource for the creative department, giving them a snapshot of design-centric visitors metrics: screen resolution, browser version, operating system, etc. Each of these Dashboards gives quick and clear answers to the questions that every member of your organization has about your website, all in an attractive, easy-to-read format.

Now, for the great news for Google Analytics users: you can now customize the Default Dashboard of a specific Google Analytics user, giving them immediate access to the information they need to do their job. Here are the details:

Collecting Web Data: A Look at Web Analytics Methodology

May 1, 2006

A few months back, I posted briefly on Script-Based Versus Log-Based Tracking, discussing the differences between various web analytics data collection methods. With more and more questions cropping up about reporting discrepencies between the two types, I felt the time was right to revisit the topic and put some key concerns to rest.

Logfile Analysis, the older of the two methods, simply counts the hits made in the web server logs and stores the data in an easily-readable, easily-managable format. This method is based on server-side data collection; there is nothing stored on the visitor's computer, nothing that runs in their browser.

In the late 1990s, search engine spiders were increasingly present on the web, and made a considerable impact on the logfiles of the sites they crawled. Along with web proxies, the popularity of consumer Internet service (and subsequent rise in dynamic IP assignment), and browse caching, it became apparent that logfile analysis needed a breath of fresh air. Supplementing logfile analysis with cookie tracking and robot exclude lists helped to solve some of the problem, but a second method was already being developed.

Interview with Google Analytics' Alden DeSoto

April 20, 2006

Alden DeSotoWe had the opportunity to interview Alden DeSoto, Editor of the Google Analytics Conversion University and the Voice of Urchin (so named because Alden was the
narrator of the Urchin tour on, and asked him some questions about the move to Mountain View, the mission of Conversion University, and the importance of web analytics to sites large and small.

ROI Revolution: It's been just over a year since the Urchin team moved from the former home of Urchin in San Diego, CA (due to Google's purchase of Urchin Software) to Google headquarters in Mountain View, CA. What's it been like over the last 12 months?

Alden DeSoto: Hard work, but fun and incredibly stimulating. I feel like we get to do really big things here. Like rolling out Google Analytics to everyone who wants it, and for free. We're helping so many businesses this way and I love meeting customers and hearing about their successes. And, Google itself is an amazing place. There are a lot of brilliant and really passionate people around here. It's one of these places where you'll sit down to lunch at a table with someone you don't know and end up having a fascinating conversation. And, we get authors and speakers doing presentations at Google all the time. Some of these people are my personal heroes--Jimmy Carter and last week, Al Gore. So, I'd say I get continually re-inspired here at Google. It's hard to imagine being anyplace else.

ROI: What's your background, Alden, and how has your role changed since the Urchin buyout by Google?

AD: My background is in communications. Before Urchin (I joined Urchin in October of 2003), I was a writer at Sun Microsystems and Siebel Systems, here in Silicon Valley. I also spent a year in Guatemala working for an NGO, developing and teaching a computer literacy curriculum for Guatemalan high school students. I basically like to use my writing ability to help people.

At Urchin, my job was copywriter-technical writer-corporate communications all rolled into one. But, my mission was to help people understand how they could use Urchin to be more successful online. And, as editor of Conversion University, that is still basically my mission here at Google. The more information that is out there on how to actually use Google Analytics to market more effectively, to build a better site, to create more compelling content, the better businesses are going to do. And, the more useful the web will be to your average person or consumer. I have to admit, I'm looking forward to the day that when I click on a search result, I can always expect to land on a landing page that shows me what I'm looking for, without having to hunt around. It's frustrating for me (and it makes me sad for the business), when I end up leaving a poorly designed site because I can't find what I'm looking for. So, I guess I'm trying to help create a better experience for myself and everyone else!

Google Analytics Feature Updates

April 13, 2006

Some exciting news from the developers about some great feature additions to Google Analytics. Here's the official announcement at the Help Center, and here's a quick overview of what has been added:

  • Localized time zone: Now you don't have to convert your data from Pacific Standard Time.
  • Rename Your Accounts: If "UA-12345" isn't descriptive enough, now you can change it to whatever you want.
  • Language Preference Support: Change your UI language setting with the new My Account link at the top of each Google Analytics page.

The best part of the announcement, though:

"We're adding support for more users and sending new invites all the time."

There has been such a huge demand for this free tool that, as Timothy posted last week, Google Analytics invitation codes have started showing up on eBay. With increased capacity for new accounts, this might mean that new sign-ups won't have to wait quite as long as before to get a peek into their website's performance, and they might not have to resort to bidding wars. So, if (for whatever reason) you've been waiting to sign up, now's the time.

All the above changes are being rolled out to all Google Analytics users and should be available in their accounts currently, or within the next few days.

What do you think about the new features? How are you planning on using them in your current Google Analytics setup? Any feature requests that didn't make it into this round of updates? We'd love to hear what you have to say.

Tracking Downloads with Google Analytics

April 4, 2006

With log-based web analytics utilities like Urchin Software, tracking downloaded files is easy. Your web logs register a hit whenever someone grabs a pdf or views a movie.

With a script-based package like Google Analytics, it's not possible to call the Javascript from pdfs, wmvs, avis, etc. So how can you tell when someone has taken the time to watch that video it took you days to create, or read your pdf whitepaper outlining the benefits your business offers over its competition?

Exclude Internal Visits from Google Analytics

February 22, 2006

Back in November, Amit Agarwal wrote about preventing Google Analytics from tracking visits via an edit to the Windows Host file. This is an effective work-around for excluding traffic from internal PCs with dynamic IP addresses, but tweaking the Hosts file is a bit tricky for the average user. Plus, if you've got dozens or hundreds of employees, it's really not practical.

Using Google Analytics' Visitor Segmentation, you can achieve the same result, much more efficiently and with a lot less work on your internal users' end.

Google Acquires Measure Map

February 14, 2006

If you're a blogger looking for a way to connect with your audience, you might be interested in Google's Acquisition of Measure Map, an analytics service that focuses on weblogs. It should very intriguing, watching what they do with this already-popular utility. Go check out Measure Map now and sign-up for an invitation code.

Tracking Email Campaigns with Google Analytics

January 25, 2006

NOTE: Please see the UPDATE at the bottom of the article.

If you've ever sent out a mass email newsletter to your clients, you've probably found yourself pausing before clicking "Send" and wondering just how many people will actually open the thing, and of those, how many will find their way onto your site.

Google Analytics can help answer those questions, and a number of others, with its easy email tracking features. Open rate, click-through rate, and conversions can all be tracked within Google Analytics. You can even measure the effectiveness of your email campaign against your CPC, banner, and print campaigns.

Google Analytics Link Tagging 101

January 13, 2006

The only way for you to see which advertising media are actually returning your investment is to tag your ads. It's an extremely simple process with Google Analytics, once you're prepared with the basic knowledge on how to categorize your various campaigns.

First, understand that you only tag what you need to tag. Don't confuse yourself, or add unnecessary work. For example, if you need to track a Google AdWords account that is linked with your Google Analytics account, you don't need to tag your AdWords URLs at all. Google Analytics does it automatically. Other paid marketing campaigns like banners, and unpaid media like email campaigns should definitely be tagged.

Script-Based Versus Log-Based Tracking

January 6, 2006

There's an interesting post over at the Search Engine Roundtable Forums about the reliability of Google Analytics data versus data generated by Urchin 5.7 software. Barry Schwartz points out a 20% hike in traffic stats through Urchin when viewing data for one of his sites.

It's important to remember that different web analytics products may use various means to track visits to your site. If you opt to run two analytics packages simultaneously, be prepared for discrepancies in your reports. Google Analytics uses a script-based method to gather traffic stats, while Urchin relies primarily on your server logs. Many bots count as hits on these server logs, but don't trigger the JavaScript tracker. They'll pass undetected through Google Analytics, but clamber through your site just like a human user would, at least according to an Urchin install that relies entirely on web server logs.

Filtering Your Data

January 4, 2006

Control is everything when it comes to web site analytics. You want to make sure you're tracking the right data, and you need to make sure you're tracking the data right. With traffic filters, you can control exactly which data are flowing into your Google Analytics profile, and which aren't.

There are three predefined filters that you can use, right out of the box:

  • Exclude all clicks from a domain (hostname), which can be used to exclude all clicks originating from one network. Get rid of the hits from your internal office network. Just plug in your hostname here and apply to your profile.
  • Exclude all clicks from an IP address, which is great for removing any clicks from a single IP address, or even a range of IP addresses. Take a visit to, then plug in the IP address here to exclude any computer that has a static IP address from your data results.
  • Include only traffic from a subdirectory will allow you to set your profile to only report on a subdomain or a subdirectory. Use this to only see traffic to your nonfiction titles ( or to your user's section (

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