Don’t wait until you urgently need a new tag to discover you also need your developers. Put the right infrastructure in place and reap the full benefits of Google Tag Manager.
Google Tag Manager is so easy to use, you can start adding tags to a site as soon as the developers put up the GTM container code. To make the most of it, though, you will need your developers’ help.
Some information should not (or cannot) be hard-coded into the tags, because it depends on each visitor’s behavior on your site. What did the visitor buy? What articles did they read? What videos did they watch? What forms did they complete? I could go on (and do, below).
Your developers can pull information from the back-end of your site and make it available on the page. They can also prepare various page elements to work with Google Tag Manager’s listeners, rules, and macros. It all means smoother sailing for you when you want to add tags later.
Follow this checklist to prep your site for Google Tag Manager, and you’ll be ready for almost any tagging request. You’ll be the hero who always knows where your towel is.
Some day, even after diligently testing, you may publish a new version of your Google Tag Manager container and disaster will strike. The site, or some critical site function, will break. Or tracking will drop to zero. (Or both!) Will you be ready to fix things?
It’s as easy as “the click of a button” to revert to a previous, working version of your tag container, according to many articles about Google Tag Manager. What most of these articles do not say is which button to choose.
Yes, there’s more than one way to restore a previous version. (more…)
Sometimes Tag Manager is so easy it feels like cheating. In a good way. Like getting a super acorn power-up and turning into Flying Squirrel Mario.
Recently I used my flying squirrel powers to beat the dynamic content boss. My client wanted to track how visitors used a couple different search forms, each with multiple options. Every time an option was selected, new search results would appear dynamically and a parameter would be added to the URL hash.
For example, if the visitor chose to view all the seminars on day 1, the URL would become /seminarsearch#day=1. Search those seminars by topic X and the URL would change to /seminarsearch#day=1&topic=x.
Or it might be a different search form, say for vendors, and the URL might look like /vendorsearch#category=abc&location=bldg2.
How was I going to tackle all those moving parts and get the data I needed into Google Analytics? I wrote a couple different pieces of code that were unsatisfactory for one reason or another.
And then I found my super acorn. (more…)
When visitors hover on your website, are they more likely to convert? Pick a hover target and add event tracking to find out.
If you want to listen for clicks or form submissions, Google Tag Manager has some seriously awesome automatic event tracking. It doesn’t cover hover events yet, though. So if you want to track a visitor hovering over a menu or pop-up window or other such thing-a-ma-jig, read on for a nifty bit of jQuery that will do the trick.
There’s nothing mysterious about the data layer for Google Tag Manager. It’s just a place to hold information so your tags can refer to that info when they need it. Do you need a developer or not though? Can you use the data layer if you’re not a developer?
This post discusses how information gets into the data layer, and how tags use that information. Understanding the data layer is the key to making the most of your Tag Manager implementation. Along the way we’ll see where you need a developer and where you can do things yourself. (more…)
Why do advanced segments get all the love in Google Analytics? What about report filters and profile (view) filters? Filters and segments work differently. Do you know when you need a filter instead of a segment?
You may think a segment is isolating the data you want and instead it returns too much data. Or you may think you’re getting all the data you want, and later find out a big chunk is missing.
To understand when you need a filter, it helps to know how filters and segments work. I highly recommend a read, or re-read, of Avinash Kaushik’s explanation of hits vs. sessions, because it all comes down to segments working on the session-level, and filters working on the hit-level.
But first let me show you how segments can go wrong. (more…)
The new goal setup in Google Analytics is great, unless you want to organize your goals. Here’s how to cope until (fingers crossed) Google fixes it.
Let me start by saying I love the new, clean look of the goal configuration screens. I love that GA is always adding new features and making adjustments. Every week there’s a surprise, often a pleasant one. One of the best things in the new goal setup is the next to last step: “Verify this Goal.” Why, yes! Yes, I would like to verify this goal before saving it and wondering next week where all my goal data is. Or without taking several extra steps to verify my goal first.
I’m perfectly happy about the clean, new direction of the administrative UI, except for one thing. The goals list is a jumbled mess!
Numbered Goals Now Alphabetized
Previously when I looked at the Goals UI, the goals were listed in the order they appeared in my reports. First I had Goal Set 1, and any goals I had configured in that set, then Goal Set 2, and so on.
Now the goals are alphabetized by the name of the goal, without regard to how they appear in my reports. All my macro conversions are in Set 1 (and they still are), but I can’t easily see that in this list. (more…)
One of the advantages of Google Analytics Premium is that you can get unsampled data, but it’s still processed data. Have you dreamed of getting access to your raw GA data?
Those dreams are about to come true. Announced today at Google I/O: later this year BigQuery will be available to users of Google Analytics Premium.
Query hit-level data at interactive speed
BigQuery is a web service that lets you query billions of rows, a.k.a. Big Data, with a response time in seconds. Without Google Analytics Premium, you upload some data first and then run your queries.
With Google Analytics Premium, your hit-level GA data will be available for the same type of interactive ad hoc queries. Pose a question, get an answer. Does that lead to another question? Rinse and repeat! You can batch queries, too.
Build complex queries and join data sets
Direct granular access to your GA data opens the door for all kinds of complex queries. You’ll also be able to combine data sets from other sources for powerful business insights.
Imagine having data at your fingertips to solve problems like these: (more…)
Your social media traffic data is split across several reports in Google Analytics. Are you taking steps to get it together?
Social media traffic sources appear in Social :: Network Referrals, as well as in Sources :: All Traffic and Sources :: Referrals. They also appear in Sources :: Campaigns if you use campaign-tagged links, not to mention the ones masquerading as direct traffic.
There’s little you can do about the direct traffic, but to get a handle on the rest of it, it’s helpful to understand where the reports overlap and where they don’t. Some of the sources for these visits are accounted for across reports. Others appear only in Sources reports and not in Social reports.
For example, the Sources :: All Traffic report shows visits from t.co and twitter.com and mobile.twitter.com (values of the Source dimension), while the Social :: Network Referrals report pulls them together as visits from Twitter (a single value of the Social Network dimension).
It’s not clear from these two reports whether the two campaign-tagged sources “twitter” and “Twitter” on the left are also pulled together into the social network “Twitter” on the right. Actually it’s not even clear that the other three sources are part of the social network, either, but we’d like to think that, wouldn’t we? (more…)
In parts one and two, I wrote about using both sides of your brain to do analysis and walked through a simple example of analysis. Now I’d like to turn to something complex, or at least with the potential for complexity: keyword analysis.
Keywords can be a rich source of visitor intent. I’m talking about search queries that lead to visits, as well as terms entered in site search after visitors arrive.
But looking at the top 100 or even top 1,000 keywords (ranked by your favorite metric: bounce rate, conversion rate, or whatever you like) won’t necessarily lead to the most accurate analysis because it neglects information in the long tail, which may be on the order of tens of thousands or more keywords.
If you’ve spent any time examining keyword data, you’ve observed similar terms dispersed throughout the long tail. I want to group those terms and analyze each group’s aggregated data to give a more complete picture. So what’s the best way to do that?