Archive for the ‘Google Analytics’ Category
The Google Analytics interface was updated this week. Gone is the familiar orange navigation bar at the top of the page. In its place now is a unified interface that shares commonality with other Google properties around the web, especially after the interface changes in Google AdWords and Tag Manager.
One thing that was not changed, however, is the functionality of the left-hand navigation. We here at LunaMetrics have been jonesing for a return to the classic functionality of the interface, circa 2010, which allowed users to click on a menu header to immediately collapse all other open menus.
Internet marketing expands and changes too quickly to remember each piece of the puzzle and how they all fit together. Commit something to memory today and tomorrow it has a new interface, iteration or industry standard. There’s just so much information. (more…)
“Oh, it’s alive…. IT’S ALIVE! IT’S ALIVE!…IT’S ALIVE!”
-Henry Frankenstein, Frankenstein (1931)
Stop me if you’ve heard this one before… A man walks into a marketing department and says “Our website is so old! It’s like it was made in the 1990′s! Let’s update the design, and make it responsive! Mobile users are the future! Our competitors all have flashier newer websites, we’re getting left behind! We can make a new website! A better website!” Then they start cackling really evil like, and get twitchy eyed.
The department all nods in agreement, ignoring the obvious creepiness of the guy, because they’ve read stories about mobile users and those “kids today” with their newfangled “smart phones”. So they design a gorgeous new site, sleek, great uses of whitespace, a real pro job. Responsive too! Loads of new functionality. Looks great on their phones, their pads, their pods, their droids, and of course their laptops. So they launch it to great fanfare!
And their conversion gets cut in half. (more…)
Back in May, Google announced that GA Premium customers would be able to export analytics data to BigQuery. It’s now rolling out to all Premium customers. What does this really mean? What’s it let you do beyond what you could before?
How do you access the data?
BigQuery stores your GA data in what is basically a giant table. It gives you a SQL-like interface to query that data, either through a web interface or programmatically.
Today we are going to go on a quest to find the scientifically-proven best blog post ever. We will do so with math.
We have a hypothesis: the best blog post ever must contain these five things:
A handful of tasteful images
A YouTube video
A length between 1200 and 1500 words
A concise title
Published on a Friday
And there was much rejoicing.
Unfortunately, this post won’t work for payphones.
Sometimes when dealing with a website, it’s easy to throw on the classic tracking events – PDFS, mailto links, etc… But what if we wanted to track when people clicked on our phone links? In a perfect world, this should be easy. However, phone numbers can be written in many, many different ways and we don’t always have control over the content to add in appropriate phone tags. As if that’s not enough, dealing with different browsers on different devices supremely complicates the matter.
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…)
This has been a big year for keyword (not provided). It has become more difficult than ever to gauge the success of SEO campaigns. That single term is now showing for over 95% of LunaMetrics.com’s organic search traffic! Yikes!
Our SEO team has been hard at work finding ways to get back some of that keyword data, through Webmaster Tools, AdWords, and some fancy mathetmatizing. Reid Bandremer blogged about some ways to combat (not provided) in a post in October.
But what if we could do even better? Rather than focusing on a user’s search term, what if we could see, on a page-by-page basis inside Google Analytics, exactly which keywords we optimized those pages for? Then we’d be able to see which of our actual SEO keywords are performing best, using metrics like conversions, bounce rates, time-on-page, etc.
The following is a way to get optimized keyword data inside Google Analytics, across your entire website, using Google Tag Manager.
Regular Expressions: The Gift That
Keeps on Giving( and Giving)*!
When I came to LunaMetrics, I had never really used regular expressions. I had heard about them, knew they were important, but couldn’t give you one concrete use. “Learn regular expressions!” they said, so learn regular expressions is what I did, still unsure of how or why these would be useful. There were examples online, people talking about Advanced Segments or Custom Filters, but how can you begin to understand these concepts until you actually need to use them? It was only after I began taking on clients and working with Google Analytics and Google Tag Manager that I was able to try out my newfound skills and truly become a convert.
Yet still, I couldn’t help but think that there must be a better way to introduce regular expressions (we’ll call them regex from here on) to complete newcomers. There are plenty of resources out there, which I’ll link to. I’m not going to recreate all of the basic instructions, but I’m going to give examples that I would have found useful when beginning my regex journey.
Cross-domain tracking has been the bane of any analyst’s experience for, oh, just about ever. It is probably the hardest thing to get right in a Google Analytics implementation, and in our experience, more people ask us for help with this one issue than any other.
Over the years we’ve dealt with this problem in different ways. jQuery made it easy to drop in a couple lines of code to track behavior across domains, but even then it wasn’t exactly automatic.
Then along came Universal Analytics and Google Tag Manager – the perfect 1-2 punch combo to knock out cross domain tracking once and for all. We held a webinar to show people step-by-step how to implement cross-domain tracking in Google Tag Manager. Below is a recording of the webinar, along with the written step-by-step instructions.