This is Part 1 of a 2-part series. >> Part 2
You have some data about your email marketing (for example, open rate) in your email marketing software, and data about visits to your site from email marketing elsewhere (namely, Google Analytics).
Wouldn’t it be great to see an end-to-end view of all that data in one place? With Universal Analytics and the Measurement Protocol, you can, and I’ll show you how, step-by-step.
Today’s post will kick things off by looking first at how to track email opens in Google Analytics. My next post will show how to tag a visitor with a unique ID, so you’ll be able to track them across devices (like in the image below). Finally, we’ll tie it all together so you can see visitor behavior from opening your email to visiting your site and (hopefully!) converting.
We’ll use MailChimp - a popular (and free, if you want to play along) email marketing manager to walk you through how to set this up, but you should be able to apply the same steps to any email marketing solution you use.
Google Analytics Content Experiments are a great way to quickly and easily set up simple A/B tests for your website. And for most people, setting up these experiments can be done using the interface in Google Analytics.
However, there are some who desire a little more control over the variation pages, that just can’t be done through the setup wizard.
For example, when you’re choosing you’re variation pages, you can specify full (exact) URLs for the variations, or relative URLs. If you choose to specify the variations by the full URL, you’d end up with something like:
If you choose relative URLs, you can take advantage of query parameters to specify your variations. This makes it possible to do site-wide tests, by placing the Content Experiment code on every “original” page of the site. Then, for your variation URLs, you’d have:
Want to know the ROI of your email marketing? What about the performance of your print ads? Are your posts to Facebook leading to conversions on your site?
Tagging your marketing campaigns is essential to get these actionable insights from Google Analytics. But you might have more than one person responsible for all of your marketing initiatives (imagine that!). You might have teams of marketers and content writers who all dip their hands in the the campaign cookie jar from time to time. That’s great! If you’ve gotten to the point where your non-web analyst peers are tagging their URLs with campaign parameters, you’ve already overcome the biggest hurdle. Now, if only you could get them all to use the same naming conventions… (more…)
Have you ever set up a goal in Google Analytics, and later wanted to delete the goal from your profile? You go into the Admin section, click into the Goals tab for the profile, and search for the “delete” button. But you don’t find it.
That’s because it doesn’t exist.
This is a common question that’s been asked before, and it recently came up at our Google Analytics training last week.
In Google Analytics, you have four sets of goals, each with five goal slots available. Hence, you can create a total of 20 goals per profile.
Goals let you define success for your website. You tell Google Analytics what you want people to do on your site, and when they do it, it counts as a goal. You can even tell Google Analytics how valuable the goal is to you. (more…)
Dimensions and metrics are the building blocks of your reports in Google Analytics, but so often I see confusion about the difference between dimensions and metrics. And even when you have a fair understanding of what dimensions and metrics are, you may not realize how many of them you actually have to choose from.
There are more than 230 (!) metrics and dimensions you can choose from when you’re creating a custom report or advanced segment. I’ve created a simple spreadsheet that should help expose the many options you have. You can download it now, but before I talk about that, let’s get everyone up to speed on the basics.
Dimensions describe the data. They are the labels in the rows of your reports. Think of a dimension as describing the “what,” as in “what keyword did they use” or “what city is the visitor from” or “what pages were viewed.”
Metrics measure the data. Metrics are elements about a dimension that can be measured. Think of a metric as answering “how many” or “how long,” as in “how many visits” or “how long a visitor was on the site.”
Now, back to those 230+ metrics and dimensions. The spreadsheet organizes them into two tabs – Dimensions and Metrics (big surprise!).
For each dimension/metric, it lists the name and definition. It also tells you what type of data is being measured or described (visitor, page tracking, AdWords, etc.). I’ve also included the API reference for each metric/dimension that is available via the Google Analytics Reporting API.
There’s also a column labeled Where You’ll Find Them, which tells you how they are (unfortunately) categorized within the custom report and custom segment creation interfaces. For example, if you’re looking for the User Defined Value dimension, it’s located under Content (instead of Visitors, where it belongs). Looking for the % Exit metric, check under Visitors (instead of Content). You get the idea.
Now it’s your turn
Still confused about dimensions and metrics? Wondering about some of those odd metrics, like TV Impressions are? Ask us below!
A question I hear frequently is “can I track form abandonment in Google Analytics?” The answer is yes, and I’ll explore the details in a moment, but you should first consider alternative solutions.
There are existing solutions (like ClickTale) that do this in a much more elegant manner, with reports dedicated specifically to form analytics. Think of it like the goal funnel visualization reports, but applied to forms.
However, if you don’t want to spend the money on an alternative solution, or you want to keep everything in one place (i.e., Google Analytics), I can help you.
Tracking forms with events
You can use event tracking to find out which fields of your form are being filled out, and which ones are causing people problems. To do this, you can fire an event whenever a user’s cursor exists a field of the form. The easiest way to do this is with a script like below:
Today I’m going to show you how to measure your owned social media traffic and your earned social media traffic. First, some definitions:
Owned Social Traffic – a visitor that comes to your site by clicking on a link that YOU shared on a social platform (Facebook, Twitter, etc.)
Earned Social Traffic – a visitor that comes to your site by clicking on a link that someone else has shared on a social platform
Here’s a quick guide on defining paid, owned and earned media that is applicable to what I’ll be talking about.
Tag, you’re it
To be able to measure owned vs. earned, you need to do something special to the links YOU share. You need to tag them with some extra information. So instead of sharing this:
You add some campaign parameters (in a way that Google Analytics recognizes) to indicate the source, medium and campaign. So you end up with one very long URL like below (which we’ll deal with in a moment):
Sources and mediums and campaigns, oh my!
For the utm_source, this is the social network on which you’re sharing the link. So if you’re sharing the link on Twitter, the source is twitter. It’s important to be consistent. These parameters are case sensative – Google Analytics makes a distinction between Twitter (with a capital T) and twitter (lowercase t). If you’re not consistent, you wont be able to easily roll up all of your data from each source into one report.
For the utm_medium, this should be social.
And for the utm_campaign, indicate either a marketing campaign that the tweet is part of, or the type of content you’re sharing. For example, blog posts are often commonly tweeted or posted to Facebook when they’re published, but it’s not necessarily part of a marketing campaign. For tweets with links to blog posts, consider using blog as the campaign.
Once you’ve added those campaign parameters to the URL, you’ll need to shorten it for 2 reasons:
1. So it doesn’t take up precious characters (in the example above, you’d only have 44 characters left for the actual tweet!)
2. So it doesn’t look so ugly. Purely aesthetic.
Bit.ly is a great tool to shorten links (my favorite) and there are many other options out there, like Google’s URL shortener (goo.gl) and ow.ly.
Of course, if you’re doing a lot of sharing on a lot of networks, you won’t want to manually create a unique shortened link for each piece of content that you’re sharing on each social site. That would get tedious and time consuming. Fortunately, I’ve built a tool to do this for you. All you have to do is enter the URL you’re sharing and it automatically creates the shortened links to share on Twitter, Facebook, Google+ and LinkedIn.
You can get that tool here, or read more about how it works on the Tracking Social Media with Google Spreadsheets post.
Reporting owned vs. earned
Once you get in the habit of tagging your own shared social links, you’ll be able to segment them in Google Analytics using Custom Segments. In a second, I’ll share the custom segments with you to do this. Then you can apply those custom segments to your Social Sources report, like below:
This graph shows visits to the site from owned social media in orange, and visits that resulted from other people sharing our content – earned social traffic – in blue. Below the graph we get the breakdown of owned vs. earned for each social source:
This is a great way to begin doing some correlative research to see how your sharing impacts not only traffic to your site, but other people’s sharing of your content.
Here are links to the custom segments. Keep in mind, these will only make sense in the context of the Social Reports, and you have to tag your links to make these work.
Owned Social Traffic
Earned Social Traffic
Check, check, is this thing on
Is this something you care about? Are there other areas of measuring social media that’s you’re more concerned with? Let me know in the comments!
It’s been about a year since Google Analytics launched Real Time reports. At first, they were cool to look at but provided seemingly limited functionality and actionable insights. One of the few examples of usefulness was measuring the immediate impact to your site from social media activities.
But lately, I’ve been turning to Real Time reports for a different use: research and troubleshooting. There is one area in particular that you can use Real Time reports to help with (more…)
Have you ever needed to make a tiny change to your Google Analytics tracking code, but your IT team told you it would be 6 weeks until the next code refresh? What if you could just log into a tool, make the change, and have it go live immediately – without IT involvement? Now you can.
Google announced the launch of Google Tag Manager this morning at the eMetrics conference in Boston. Google Tag Manager (GTM) is a free tool that lets you manage the marketing and measurement tags for your web site in one place. This means no more scattering scripts across your pages and waiting on IT to track them down.
Sometimes direct is good. For example, I would have much rather been on a direct flight to Denver for this week’s Google Analytics training than having a layover in Charlotte.
But not everything direct is good. Take visits to your website, for instance. Direct visits are the worst visits you can have (at least from the perspective of a web analyst).
Why, you ask? Because direct visits are a mystery. We don’t know why they came to our site, how they found out about us or whether our marketing and advertising worked.
When you have referral or campaign information about the visits to your site, you can start to see which marketing initiatves are working and which ones you should dump.
Here’s the problem: even with rock solid campaign tagging, you’re still going to get Direct visits. Even worse, the number of those visits that aren’t truly Direct is on the rise.
Let me say that again. Not all of the “Direct” visits to your site are Direct. We have a wolf in sheep’s clothing here.
I don’t see a lot of people talking about this issue (at least publicly) but I expect it to become one of the most important issues in the web analytics industry in the next year or two.
First, let’s look at where these wolves are coming from, then talk about ways to rip off their disguises.
Mobile Devices and Apps
Let’s face it, we’re living in a multi-device world, where people connect with your content not just from a computer, but from their phones and tablets too. And they don’t always use a web browser to pull up your site. They click on links within apps for Twitter, Facebook, Pinterest, LinkedIn and many, many more.
Many of these visits show up as Direct.
Clicks on (untagged) links within Outlook and other desktop email clients show up as Direct. That’s always been the case. But what’s become more common is for web-based email clients (Gmail, Yahoo! Mail, etc.) to use secure browsing (https). Consider your referrer lost – “Direct” visits strike again, more wolves.
Tweetdeck and other non-mobile Twitter apps can also show up as Direct, if a link shortener is used (bit.ly or goo.gl, for example).
How often do you send a link to someone in Google Talk or Skype? If they click on it, they are a “Direct” visit.
Aside from things you have little to no control over, there are some causes that you an fix. For example, you may have errors in you code or conflicts with scripts that cause your visitors’ sessions and/or cookies to be reset, resulting in more false Direct visits.
What can you do?
The best way to clean up your data and identify these wolves is to tag them. This means having a stringent campaign tagging plan in place for every marketing effort your company does. Paid search, display ads, email marketing, TV, radio, print, direct mail, you name it – it can (and should!) be tagged. Try this campaign tagging worksheet to get started. It’s a Google Doc spreadsheet – just click File > Make a copy and it’s all yours. If the Make a copy link is grayed out, look at the link in the top right to make sure you’re signed in.
The other important thing is to realize that even that won’t solve 100% of the problem. Although you can use campaign tagging on everything you share, there will always be people who come to your site, like what they see, and copy/paste your URL into Facebook, Twitter, etc. This is especially true for blog posts and other informational content that is more likely to be shared.
One thing that will help is to look for patterns and trends in your data. As Direct visits increase, look for correlations between visits from social media (that you can still identify as such) and direct visits from mobile devices. This will be especially apparent if the direct visits are landing on internal pages with long URLs (that are mot likely not being typed in directly).
What weapons are you using to hunt down these wolves? How has this issue affected your data? The comments are yours!