If you’re not familiar with the Goal Copy Firefox extension, you can read the original post here.
It seems like everyone I know is using Chrome now. It’s fast, it’s simple, it has developer tools built right in. It’s a fantastic browser and it deserves every bit of browser share that it’s taking away from the Big Two (Firefox and IE).
That being said, I do almost all of my Google Analytics debugging in Firefox. I love HttpFox and you’ll pry Firebug (and, to a lesser extent, Firecookie) from my cold, dead hands. Maybe I’m just set in my ways, but it’s the way I do things, and while I love Chrome for everyday browsing, I do all my heavy lifting with the ‘Fox.
Which is why I keep updating GoalCopy. This latest version works with Firefox 9. It still only works with the old interface, but an update for GA v5 should be ready in a few weeks.
For now, just download the latest version of GoalCopy here and get to copying! You might encounter a weird glitch where only the Find/Replace toolbar shows and the Copy/Paste options are nowhere to be found. Just re-enable it through the new Firefox menu as shown below:
What about you? Have you made the switch to Chrome, or are you sticking with Mozilla? What sort of features do you want to see in a Google Analytics add-on? Please leave a comment below and let me know!
Everyone can agree: Google Analytics’ custom variables are a great feature. It lets you label your visitors with all sorts of fun stuff. Male or female? Member or non-member? Cat person or dog person? If you can identify your visitors’ answers to these sorts of questions, you can tag them with a custom variable.
But sometimes website owners implement the custom variable code and start gathering these valuable segments of traffic, completely unaware that the numbers aren’t very accurate. What could be causing such a heinous mistake?
Believe it or not, Google warns against the issue right in those instructions there, but they don’t call it out quite enough for my taste. It’s extremely important that you “call the _setCustomVar() function when it can be set prior to a pageview or event GIF request” (emphasis mine). Here are the details:
In certain cases this might not be possible, and you will need to set another _trackPageview() request after setting a custom variable. This is typically only necessary in those situations where the user triggers a session- or visit-level custom var, where it is not possible to bundle that method with a pageview, event, or ecommerce tracking call.
What exactly does this mean? Well, if a visitor fills out a survey on your site, hits submit, and you run _setCustomVar() after the _trackPageview() of the submission success page, that _setCustomVar() call just sits there in deep space, waiting for another _trackPageview() or _trackEvent() function to carry it along to Google’s servers. If that is the visitor’s final pageview in the session, then the call floats away forever, never to be heard from again.
The worst part, though, is if the visitor goes to another page, then the _setCustomVar() will tag along with any subsequent GIF requests. This means that it may appear as if the custom variable is working just fine, according to the reports in Google Analytics, but the numbers are just inaccurate.
So, to ensure that you are tracking your custom variables as precisely as possible, make sure that you always run the _setCustomVar() function before the calls to _trackPageview() or _trackEvent(). If this isn’t possible–you have an include at the top of every page, for instance, and can’t modify it–then be sure to include a second pageview or event after the _setCustomVar() function, like this:
_gaq.push(['_setCustomVar', 1, 'membership', 'gold', 1]);
_gaq.push(['_trackEvent', 'Tow Truck', 'go', '-', 0, true]);
This will ensure that every single time that function runs, it gets counted. Guaranteed!
Update: Tyson Kirksey, of Vertical Nerve, reminded me to set the event to non-interaction mode so that it won’t influence bounce rate, pages/visit, time on page, etc. I’ve also borrowed his clever naming convention for the event. Thanks, Tyson!
If you’ve been to one of our Google Analytics trainings, you may have heard me say this: tracking visitors from one domain to another is a huge pain in the neck. Whenever someone goes from domain1.com to domain2.com, you have to take their cookie data and pass it over to the second domain via the URL. If you don’t, the visitor generates a new visit and their referral data gets jacked up.
Normally, this is a tedious, manual procedure. After making a minor change to your Google Analytics Tracking Code, you then have to modify every link on domain1.com that takes a person to domain2.com. If you have a few links, no big deal. But what if you have thousands of them?
We’ve posted before about automating the cross-domain tracking process, but a lot has happened since then. Namely, Google Analytics has a sexy new asynchronous tracking code. So we finally got around to creating a script that automatically links domains using the new code syntax.
Not only that, but this script tracks outbound link clicks and downloads, all automatically. They’ll show up as events.
We’re pretty proud of it, and since it’s so darn useful to us, we figured we’d share it with you. Give it a try and let us know how it works for you!
Step 1: Modify Your Google Analytics Tracking Code
First, you’ll need to make sure that your Google Analytics Tracking Code is set up to allow for cross-domain tracking. The
_setAllowLinker methods are required for this to work:
var _gaq = _gaq || ;
Make sure that
_setDomainName is set to the second-level domain that the tracking code resides on.
Step 2: Download and Modify the Script
Click here to download the script, then modify the domains and file types you’d like to track.
If I wanted to track the domains lunametrics.com and lunametricsstore.com, I’d modify line 5 to read:
var domains=["lunametrics.com", "lunametricsstore.com"];
And if I wanted to automatically track downloads for PowerPoint presentations, I’d add .ppt to the list on line 6:
var fileTypes=[".doc", ".xls", ".exe", ".zip", ".pdf", ".mov", ".mp3", ".ppt"];
Step 3: Upload Script and Include on Pages
Upload the xdomain.js file to your web server and then reference it on all pages of your site. Place the reference below your Google Analytics Tracking Code:
Because the script relies on jQuery, you will also have to reference the jQuery library at some point before the call to the script. You can download a copy of the jQuery library and host it on your web server, or just reference the one hosted by jQuery:
Step 4: Test It!
To make sure the script is working, click on one of the links that takes a visitor from one domain to the other. Check the URL that displays in your browser location field after the new page loads. You should see a string of information in the query string:
You can also view your cookies (I use Firebug and Firecookie). Check out __utmb. The number after the first period is the pageview count. If cross-domain tracking isn’t configured properly, then it will reset when you hit the secondary domain.
__utmz should also maintain the proper referral. If you visit your primary domain directly and then move to your secondary domain, __utmz should still reflect this:
Hopefully this helps you set up cross-domain tracking (and outbound link tracking and file download tracking) on your site easily, without a lot of headaches.
This script was a collaborative effort by myself and Phil Anderson, who did most of the heavy lifting in jQuery. It’s supplied as-is. We’ve tested it internally, but it’s your responsibility to make sure it works on your own sites. And if you notice anything that doesn’t seem to be working, you’re free to correct the code. It’s released under the terms of the GNU General Public License, so feel free to modify and redistribute. We just ask that you keep the copyright notice on the top, and that you share any cool additions with us so we can use ‘em too!
We recently ran into a very strange issue here at LunaMetrics. Specifically, my co-worker Dorcas Alexander noticed something odd in one of her client’s reports. While checking out the Multi-Channel Funnels report, Dorcas realized that the number of transactions listed with a path length of 1 (e.g., the transaction occurred on the visitor’s first interaction with the site) were different than the number of transactions listed as “1 visit to transaction” in the Visits to Transaction report.
Initially, it seems like the two reports should show the same, or very similar, numbers. But we were seeing discrepancies of 100%, with Visits to Transaction always higher by a huge margin.
Interactions are defined as “clicks/referrals from channels” by Google. And a Visit, of course, is the number of sessions that users have on your site. Why is there a difference between the two, and why is it so vast?
After some digging, and some help from former Director of Online Intelligence, Jonathan Weber, we think we may have put this issue to bed.
It looks like Visits to Transaction only counts visits from the most recent campaign update, whereas Multi-Channel Funnels counts all visits over the past 30 days.
Let’s take a look at some specific cases. Let’s say we have a visitor with the following visit path:
In this case, because the direct visit doesn’t update the __utmz cookie, then both reports will show the same data. But what if that cookie is updated?
Here, Multi-Channel Funnels will show a 2 interaction path length, but Visits to Transaction only shows 1, because the count is only from the last update of __utmz.
Finally, in this example, we only have a single interaction in the Multi-Channel Funnels path length, because it only counts for the last 30 days. But we have 2 Visits to Transaction, because the cookie was never updated (direct visits don’t overwrite).
Hopefully this will help to explain strange discrepancies in your own reports. Remember: usually there’s an explanation for weird stuff like this. Sometimes you have to dig a bit to get to the bottom, though.
Testing a paid search ad is easy. You create two ad creatives, set your ad network to split traffic evenly between the two, and sit back and let the data collect. This isn’t tough to do because you have full control over what is displayed on the results page when a user searches. Once you’ve got enough data collected, you know what works and what doesn’t, and you can go in and change the ad creative appropriately.
The organic results pages are different, though. You can’t just tell Google to split between your two creatives. You can modify your titles and meta descriptions, but you have no idea when Google is going to crawl your site and update its index. And changes to your page titles can severely affect that page’s ranking.
Fortunately, Google freely admits that meta descriptions don’t impact your ranking on the SERPs. So you can change them to your heart’s content and they won’t cause any issues.
So theoretically, if you were to modify your page’s meta description, and then find out when Google started running with the new description, you could check your data in Google Analytics and start analyzing which version was better at getting people to your site.
You can get a pretty good idea of when the Googlebot crawls your site with Google Webmaster Tools, but determining when the SERPs are updated with your site description is something you’ll need to do manually. One easy way to find out when Google updated your page in its index is by viewing the cached version.
Just do a search that will include your page in the results, and then click the “Cached” link to the right of the URL:
You’ll see a box at the top of this page that tells you when this snapshot occurred:
This is the most recent date and time that Google cached your site, which will allow you to annotate your Google Analytics data with the start of your “Version B” site description.
Now the fun begins. After a few weeks, do some date comparisons from before the new version went live versus after. Look at traffic from Google and analyze the effect that your new SEO “creative” has had on visits. Are they higher or lower quality visitors? Check out the keywords they’re using to find your site. Are there any queries that have had big jumps in traffic? Drastic declines?
Sure, a dedicated split-testing tool built into Google Webmaster Tools would be pretty sweet. But until then, we can hack it a bit and get a lot of insight into what draws searchers to our sites. Give it a try and see what you find out!
(Update: I have been corrected. This is not actually a split test, because it is run over two different periods of time. I’ve updated the article to reflect this. Regardless, I still think there’s some insight to be gained from running experiments like this, and until Google starts letting people do actual A/B tests, it’s one way to do it.)
(Coke/Pepsi photo by kreg.steppe)
If you’re not familiar with the Goal Copy Firefox extension, read the original post.
To stay informed of future updates to the GoalCopy Firefox extension, join this email list for a notification of when to update your extension.
Firefox’s new rapid release schedule means new versions every couple of months. Now 6 is out, and you know what that means: a new GoalCopy!
If you’ve upgraded to Firefox 6, just download the latest version here and get to copying! You might encounter a weird glitch where only the Find/Replace toolbar shows and the Copy/Paste options are nowhere to be found. Just re-enable it through the new Firefox menu as shown below:
Note: GoalCopy currently only works with the old version of the Google Analytics interface.
By now, you’ve probably heard. Google has released Multi-Channel Funnels to everyone. Everyone rejoice, for the days of last-click attribution are passed.
Well, not completely. For the moment, Multi-Channel Funnels remains sequestered away in its own special report section under the My Conversions tab. Once we have the ability to segment other reports by first-click source, or add custom weighting to existing Traffic Sources reports, then we can celebrate. ‘Til then, we have a lot to learn about Multi-Channel Funnels and how our current mode of thinking about traffic quality must change.
Back in April, during Multi-Channel Funnels’ soft launch, I posted about the different reports available, and since then, there have been countless blog articles about how useful all of these new reports are. But I haven’t really seen a lot about the Channel Groupings feature. And because I think they’re pretty much the new hotness, I decided to rectify that.
What are Channel Groupings? Click into the Top Conversion Paths report in Multi-Channel Funnels. Instead of seeing a bunch of source/medium combinations, you see all those nifty colored labels down in the data table? Yeah, those are Channel Groupings. Do you want to know why I love them so much? Because they make displaying data about your marketing efforts super duper easy.
We’ve always had a way to label our incoming traffic in Google Analytics. If you’ve used Google Analytics Campaign Tracking Parameters properly, just mosey on over to the Traffic Sources reports and there’s your marketing channels. But what happens if you want to organize everything differently? What if something is labeled as “social” when you’d prefer that it get classified as “community”? Sure, you could write a filter to modify the fields, but that doesn’t apply to historical data. You’re stuck pulling data out into Excel and fudging it yourself. Bummer.
Now, with Channel Groupings, you can see everything in a different light. And you can customize it. Just click on Channel Grouping under the viewing options above the data table and then choose Copy Basic Channel Grouping template… You could create your own from scratch, but using Google’s as a template makes it much, much easier.
Here’s what you should see:
Google has already done most of the work for you. Each of those colored labels is a set of rules identifying what type of traffic it should include. Let’s check out the Social Network grouping to see how it’s set up. Just hover over the label and then click Edit:
Whoa! That’s a lot of rules. I don’t even know what half of those sites are, but apparently Google has been doing their homework. Weird that they have “vampirefreaks.com” but not “Google Plus”:
Do you know of a social networking site that isn’t here? Just go to the bottom and click on Add ‘OR’ statement. Then write your own rule. What about werewolf-freaks.com? Why let the vamps get all the love?
You may even want to make your own grouping. What if you have an affiliate program and there are a number of sites showing up as “Referrals,” despite the fact that they’re really just affiliates sending traffic to your site. Go down to the bottom of the list and click Add New Rule. Give the grouping a name, pick some rules, and then assign a color:
Now, whenever you want to view your own Custom Channel Groupings, you can pick them from the Channel Groupings dropdown above the data table. They’ll be available under the Assisted Conversions and Top Conversion Paths reports. The one drawback at the moment is that you can’t share Custom Groupings with anyone else, so they’ll only show up in the Google Analytics account in which you create them. They do show up in the new Profile Assets area, so I’m hopeful that Google will enable a sharing feature soon. ‘Til then, just be sure to create them in whatever account that you use most often.
What groupings are you planning on using? There are so many possibilities. Viral. ARG. Community or forum. Video. Television commercials. Mobile apps. You can further segment existing groupings, like “Official Facebook Links” versus “Word-of-mouth Facebook Links”, or “Official Twitter Clicks” versus “Retweet Links”. Back in the day, if you didn’t tag your URLs or set up a filter, you were out of luck. Now, if you know the referral URL, you can remap it to whatever Channel Grouping you want.
I think a lot of people have missed out on the power of this tucked-away feature of Multi-Channel Funnels, just because it’s not very well-advertised. If you’re looking for a way to wow the stakeholders at your next marketing meeting, try creating your own Custom Channel Grouping and showing off the new Google Analytics Multi-Channel Funnels. You’ll find a lot of really valuable data about how all of those channels interact, and you’ll get to do it your way.
Sometimes it’s important for certain people within an organization to have access to metrics within Google Analytics, but for whatever reason, they’re not allowed to have access to the whole shebang. Maybe ecommerce data is beyond their pay grade, or there’s sensitive data that they’re not privy to.
For whatever the reason, sometimes you have to restrict people’s access. Unfortunately, Google Analytics’ user access management leaves a little to be desired. You can either be an admin or a user. If you’re an admin, you have access to everything. If you’re a user, you can have limited access, but only by profiles. If you have access to a profile, you have access to every single report within that profile.
What if you wanted to restrict the type of data that a user had access to? Only give them a Pages report for a specific directory? Only grant them access to top level information about sources bringing traffic to the site?
Sure, you could create a bunch of profiles and try to uses some creative filters to ensure that only the right stuff gets into the filter and all the sensitive stuff gets blocked, but that can be extremely tricky, and downright impossible in some situations. If an employee needs to access some top-level sitewide metrics but not be able to drill down to certain others, you’re going to need a lot of different profiles.
Instead, I’ve found that creating custom limited-access dashboards with the Google Analytics Data Export API and a tool called Shufflepoint is straightforward and results in some pretty cool dashboards that can be installed on a static webpage or on a user’s iGoogle page.
First of all, let’s talk a bit about Shufflepoint. What is it? It’s a “report integration hub” where you can pull data from multiple sources–in our case, Google Analytics–and then push it to other destinations. I can create a custom query to the Google Analytics Data Export API and then push the data retrieved from that query to the Google Charts API, to Google Maps, and even to an iGoogle Gadget.
Shufflepoint has an awesome drag-and-drop query tool that lets me pick the GA profile, metrics, and dimensions I want to pull, and then spits out a feed URI for the tool I want to import it into. Using the charts and table gadgets in the Google Chart Tools, I can just plug that URI into a field and it’ll spit out a graphic that shows up on my iGoogle page.
Now I can micro-manage the types of reports a user has access to. They don’t even need access to the Google Analytics interface. They just need an iGoogle page. For more information on signing up for Shufflepoint and using it with iGoogle gadgets, check out this page on the Shufflepoint site.
These are all pretty basic reports, though. What if the user needs to have something a little more fully-featured?
Right away, the gadget is pulling data from Google Analytics using Shufflepoint: the page path, the visitors, the pageviews, and the time on page. In addition, if the user clicks on the page path, it drills down and shows us the sources and mediums for visitors to that page:
Pretty cool, huh?
It’s not a common problem by any means. If you can, I highly recommend that you give analysts and stakeholders access to the Google Analytics interface. With new features being announced all the time, it’s the best, easiest place to go for sifting through your site’s data.
But if you have to restrict access, think about using the GA Data Export API and building some custom iGoogle Gadgets with Shufflepoint. You might be surprised with what you can accomplish!
In case you haven’t been paying attention, it’s been a big week at Google. On Monday, the +1 button was released on all Google search pages. On Tuesday, the Google+ Project was announced. Then, on Wednesday, Google Analytics and Google Webmaster Tools got new social tracking features. So far, no big announcements for today, but it’s early yet.
If you’re like me, you feel like the world of Google is moving too fast to wrap your head around it all. That’s why I took the time to put together a cheat sheet of the recent additions to Google Analytics. At least for one of Google’s many products, you’ll know exactly what is available, what’s new, and what you should keep an eye on in the future.
Wow. That’s a lot of new stuff! Let’s go into detail.
Quick Over-Time Insights with Plot Rows
The first real treat of the year was the new Plot Rows feature, which we covered when it was announced.
If you were one of the lucky ones who had access to the new version of Google Analytics, you could mark off rows on a data table and see those segments displayed in your timeline. It is, hands down, the quickest way to gain on-the-fly insight into the performance of your traffic over time.
Try It Now: Go into Traffic Sources / Incoming Sources / Campaigns and plot two of your largest campaigns. Change the timeline to view the Bounce Rate. See any big peaks or valleys?
Of course, this feature was only available in the new version of Google Analytics. Thankfully, the next big feature announcement was…
Google Analytics v5 is Available to Everyone!
Yes, that’s right. After months of waiting for beta invites, Google opened the floodgates and gave everyone the opportunity to try out (and critique) the new version of Google Analytics. Redesigned from the ground up, v5 meant more useful features right away, but also an easier time with ugprades down the road. Based on the slew of new features in May and June, it looks like the plan worked.
Try It Now: One of my favorite features of the new version gets overlooked a lot, but I absolutely love how I don’t have to wait around for reports to load while I’m navigating through the sections. Click on Content or Conversions and the report sections open up immediately. In the old version, you couldn’t have more than one section open at a time. This saves me so much time every day.
Mixed Attribution with Multi-Channel Funnels
It’s not officially available, except in an extremely limited beta, but the announcement that Google was introducing a mixed attribution model into Google Analytics got a lot of people talking. Measuring assisted conversions and labeling traffic sources after-the-fact are two features that many users have been waiting on for a very long time.
Try It Now: Chances are you don’t have Multi-Channel Funnels at this point. As soon as it opens up to more people, look for a post on the LunaMetrics Blog.
Measuring Page Load Time with the Site Speed Report
One of the first new additions to v5 was the Site Speed report. With a minor addition to the Google Analytics Tracking Code, users could begin to see how quickly their content was loading for site visitors.
Try It Now: Pull your load time out of the Site Speed report and match it up against more interesting dimensions. Create a Custom Report that pairs browser, campaign, or location with the Average Page Load Time metric. See anything strange about those dimensions?
Integrate Google Analytics with Google Webmaster Tools
People have wanted a more fully featured SEO report set in Google Analytics for a while. Most of us use both GA and Google Webmaster Tools together, but now we can integrate the two and get search query information, clicks, impressions, and average organic position data right inside of Google Analytics. At the moment, this feature is still in a pilot program, so it hasn’t been rolled out to all accounts, but you can request an invite here.
Try It Now: If you’re lucky enough to be involved in the pilot, here’s a fun experiment to try. Pick a keyword that shows up in your Search Engine Optimization / Queries report and segment by landing page. Then modify your meta description for the top landing page and upload it. Monitor Google Analytics to see how the keyword’s CTR is affected. It’s a cheap and easy way to do A/B split testing on your organic results.
Improvements in Mobile Reporting
Based on anecdotal evidence (e.g., browsing the web on my Android phone) there are still a lot of site owners out there who aren’t convinced that mobile-designed websites are necessary. This may or may not be true, depending on the site, but you should be sure before making a decision either way. The updated Mobile report set shows precisely how many visitors are accessing your site from a mobile phone, and even shows you what model of phone is accessing your site. You can even see a picture of the device and find out how the user interfaces with the phone: touchscreen, clickwheel, or even stylus.
Try It Now: Before you do anything else, go to the Mobile Overview and change the report view to Percentage. What does the pie chart look like? What is the total percentage of visits to your site from mobile phones? If it’s small, it obviously means you don’t have a big share of mobile users. Do you need more, or is mobile browsing not something in your roadmap?
Social Tracking in Google Analytics
Tracking social media interaction on your website has been possible with Google Analytics, but up until now, it’s never had its own report set. Now, with the use of the new Google Analytics _trackSocial method on your site, you can start to track social interactions–Facebook likes, Twitter shares, and Google +1s–in the new Social report set.
Now, each time a visitor clicks one of those buttons, a special kind of event will be fired off and recorded by Google Analytics. You’ll be able to see the total amount of traffic that was “socially engaged” with your site and how it compares against the traffic that wasn’t. You can segment by the type of social actions and even see the specific pages that engaged visitors to click “Like” or “Share”.
Try It Now: By default, Google +1 clicks are tracked, so if you have a +1 button already installed on your site, you should already see some data in your Social report section. Take a look at the Social / Pages report and see what pages are getting +1’d. Is there anything special about them? As you think about ways to promote your content, keep an eye on this report and the Social / Engagement report to ensure that your social efforts are moving in the right direction.
It’s obvious that the Google Analytics team isn’t sitting still. They’re bringing out new features and new reports at blazing speeds. What are you hoping is in the pipeline? Share in our comments!
Getting your website to load faster is always a good idea. It can impact your rankings in both Google organic search and the Google AdWords auction, and it’ll make your users happier. No one likes to sit around and wait for a site to render. Sometimes it’s the difference between someone sticking around on your site and them bouncing.
That’s why the latest report announced in the new Google Analytics is all about Site Speed. Now you can find out which pages are loading slowly, how your site’s load times are affecting expensive advertising channels, and the correlation between load times and conversion rates.
Best of all, you now have access to the Average Page Load Time metric in the Custom Report builder, so you can pair it up against all sorts of fun segments: browser, campaign, geo-location.
To start using this new report, just make a small addition to your existing Google Analytics tracking code. Once you’ve done that, Google Analytics will begin to use a sample of your pages to calculate the load time. If you’re interested, you can actually see the number of pages it uses with the Page Load Sample metric.
The count begins as soon as the visitor has clicked to a page and uses the W3C’s NavigationTiming spec. No word yet on whether or not browsers that don’t support NavigationTiming (IE8, Firefox 3) will be tracked with a legacy mechanism.