URLs are often one of the most problematic labels for data in web analytics: they’re messy, full of inconsistency, gunked up with a bunch of query parameters that may or may not be useful to you. It tends to make analyzing your content a mess.
Here, sort this stack of needles.
There are a number of suggestions for cleaning up those URLs (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.
If you use Google Tag Manager or another tag management tool, you’re probably already familiar with the idea of a data layer. It’s basically a centralized place for information about the page to be passed to analytics and other measurement tools.
Up to now, there have been some informal conventions in tools like GTM. But it would help us all to have some standard guidelines, for interoperability between tools. So, if you need to switch from one tool to another, you can easily do that without rearranging the data. Or, if you build a plugin for a content management system, you can build to the standard and not worry about which tool it will be used with.
So a W3C Community Group was assembled to tackle this problem, including 56+ organizations (including Google Tag Manager) providing input on a specification that is standardized enough to provide interoperability, without being too rigid to represent many different industries and websites. (LunaMetrics also participated in the development of the specification.)
After much deliberation, version 1.0 of this specification has been published. Let’s take a look at what it says and does.
If you pay attention to developments in Google Analytics, you were probably glued to the live stream of the Google Analytics Summit opening presentations. GA made a number of announcements about forthcoming features. One of the most exciting is about automatically tracking events in Google Tag Manager. It’s a feature that’s been highly requested ever since Tag Manager was released, and it’s especially exciting because it’s available NOW (unlike a number of the other announcements, which are only “coming soon” — such as a forthcoming SLA for Tag Manager for Google Analytics Premium customers).
But, if you go and take a look at Tag Manager trying to figure these out, you might find yourself scratching your head over documentation that is mostly “coming soon”. Not to worry: I’ve banged on the pipes, and here’s a guide to how it all works. (more…)
Implementing Google Analytics can be pretty easy: copy and paste the code, hopefully into some sort of template file that’s used on every page on your website. Done!
But you know it’s not always that easy. First, there’s not just one template, of course, there’s that special one for the landing pages, oh, and this application on our subdomain uses a whole different server. Oh, and you wanted to put some AdWords tracking code or another tool on all those, too?
Then, of course, you’re not allowed to just copy and paste code into the website. It has to go into the update and testing queue, and three months later, if you’re lucky, it will go into production.
A tag management tool can help you with some of these issues. It’s not a cure-all, and it’s not necessarily any better for you if you don’t face these kind of issues, but if you do, it can pave the way for an easier experience. (more…)
Colliding galaxies, because the universe
Google Analytics has great site search tracking features, but they rely on the URLs of your search results pages having a query parameter (the part of the URL after a question mark, with something like “?searchterm=testing” when you search for “testing”). There are ways around this to track site search without a query parameter (that’s an oldie but still a goodie from 2010), but all those workarounds involved adding or altering the code on your site in some way. But now there’s actually a new way to go about this for some URL structures that involves no code at all. (more…)
You probably already know about the Funnel Visualization and Goal Flow reports in Google Analytics. They’re a great way to understand how users complete (or don’t) some kind of process on your website, such as filling out a series of forms, like a registration or checkout.
Sometimes, though, there isn’t a clear path. On this site, for example, we have a contact form that doesn’t just appear on one page, it appears in lots of pages, and this isn’t an uncommon feature of lead generation sites. Likewise, sometimes people say things like, “Well, page X is our goal. But you can actually get here either by going A > B > X, or by A > P > Q > X, depending on what options you choose.” How do we know which way people got to X?
The Reverse Goal Path is a report that helps fill in these details. You’ll find it under Conversions > Goals in the left-hand navigation in Google Analytics, and like all the goal reports, you can select a particular goal you want to see from the drop-down at the top. It’s very simple: it gives you the goal completion URL and the URL of each of the 3 pages that came immediately before. You don’t have to predefine a funnel or anything, it simply looks 3 pages back in the visit and tells you what they were.
So here’s an example from our contact form. The first column is the “Goal Completion Location”, which in this case is always /about-us/contact/thank-you/. Then each of the subsequent columns walks back one page, telling us whether someone was on the home page, the contact details page, the client list, etc. No funnel necessary!
To sort out this information, note that you can use the advanced filter. So if you’re only interested in one particular path or page, you can narrow down the possibilities you’ll see here.
We know you’re eager to start paid search; it can be a crucial way of bringing potential customers to your site. But there are a few things you should make sure you have in place to be successful.
1. Work the Numbers
Stop. Do not pass go. Do not deposit $200 in your AdWords account (yet).
First, figure out what your conversion is — a sale? a lead form submission? Then you have to try to figure out how much money it makes sense to pay to bring people to your site so that you get more value from that conversion than you spend on the advertising.
You can go at this two ways. If you know the value of the conversion (you sold a $100 widget), you can work the ROI calculation backwards to figure out what a reasonable cost per conversion and cost per click might be. Alternatively, if the value of the conversion is less well-defined (like in lead generation), you might simply pick a reasonable target for cost-per-lead.
As the avid users of AdWords know, Google Analytics has a great report that pulls in cost data from AdWords. If you have an ecommerce site or currency values assigned to your goal conversions, it’ll even calculate ROI.
A while back, Google Analytics announced new support for importing cost data from other sources: think Bing Ads, Facebook advertising, etc. This is great! It puts all the power of those AdWords reports to work on your data from any kind of advertising. (more…)