Google Universal Analytics
Fasten your seatbelts and get ready for a wild ride. Google Analytics is morphing into Universal Analytics.
What is Google Analytics?
Google Analytics is a service offered by Google that generates detailed statistics about a website’s traffic and traffic sources and measures conversions and sales. The product is aimed at marketers as opposed to webmasters and technologists from which the industry of web analytics originally grew. It is the most widely used website statistics service.
Wikipedia “Google Analytics”
What’s changing with the new Universal Analytics?
Universal Analytics has almost all the capabilities of Google Analytics, but in addition, gives you greater control over the data that you collect and how it is interpreted. You can control :Feature comparison
| Features | Classic Analytics | Universal Analytics BETA |
|---|---|---|
| Basic GA features (Visitor acquisition, behavior, and conversion data) | ||
| Event tracking | ||
| AdWords account linking | ||
| Custom variables | Upgrade to custom dimensions & metrics | |
| Custom dimensions & metrics | ||
| Online/offline data sync | ||
| Multi-platform tracking | ||
| Simplified configuration controls | ||
| Select new feature releases | ||
| Advanced advertisement tools (AdSense, Content Experiments, DFA, Remarketing) | Coming soon |
For many enterprises the most basic change will be 1) an end to figuring out how best to use what they can pull into their information platform from Google Analytics, and 2) figuring out how best to send data off to the Universal Analytics cloud for analysis. They will often need no new software. They will often be turning otherwise useless data into intelligence.
The ride will be smoothest for those who plan ahead.
The destination is higher conversion to cost ratios and other lovely places.
It begins with a simple, low-cost, in-house exercise: each consumer being tracked must have an ID number and no personal information about that consumer may ever enter the Universal Analytics cloud.
So a most basic point of departure in mapping out how an enterprise will interface with Universal Analytics is to be aware of what privacy restrictions apply.
Then one plans how to stream what data to Universal Analytics such that the analysis streamed back will interface with the in-house platform, putting flesh and blood back onto a particular ID number, then emailing them, calling them, placing a certain kind of ad in a certain kind of medium or whatever the purpose of the cloud analysis was.
The Cloud
These two simple considerations are at the heart of what is changing: 1) the Cloud will be doing more of the analysis but 2) it will not do certain things presently done in-house and they will still be done in-house because they involve a phone number, an email address or other personal information which must be excluded under Universal Analytics terms of use.
All an enterprise’s offline data will now have a place to visit. The Cloud. The enterprise will want to consider dusting off data that had no previous use and see if data can be woven into intelligence by the massive capabilities of the Cloud.
Industry Specific
What it means for a particular enterprise can often be investigated most easily by doing a Google search for “Universal Analytics” + (product, industry or profession). The possibilities are becoming new buzzwords of prominent trade publications these days.
Strategic customer insights are the objective and one doesn’t have to install and learn to use new in-house software. But the nature of the beast requires some thought, reflection and planning.
Best start now.
And where did all this start?
Some enterprises have had years of experience tracking visits to their home and other web pages. This has been done through online services which are often free for the most minimal services such as StatCounter.com and SiteMeter.com, two of the more prominent survivors from when the Internet first began to blossom.
The services[1] note and reports a visitor’s IP address, ISP, geographical location, whether they have visited the page previously, and the URL of the web page they were visiting immediately previously. There is also “funnel” analysis lately which somehow tracks back through the links that brought a visitor to the enterprise’s home or sales or contact page.
Statcounter.com reports about three million members with growth of about 1,500 members a day. SiteMeter.com does not appear to publish member or subscriber numbers on its website.
Google Analytics, on the other hand, is said to be in use in over 12 million websites, including over a third of the world’s top one million websites and nearly 60% of the world’s top 10,000 websites.[2]
The basic software for web visit analytics began to emerge in 1994 and 1995, the first company to provide such services being I/Pro and their “Log Analyser” in 1994. Today, Log Analyser has a website that has no content, is “Under Construction” and presumably has no members or subscribers.
Google Analytics began to emerge in 2005 upon Google acquiring “Urchin on Demand” from a Dublin man who was sixteen years old at the time he launched it a few years before.
The rise of Google Analytics[3] proceeded steadily in the general Google environment of ready cash and products with which it could be integrated. Integration with Google AdWords began in early 2009, the Urchin brand name continuing as Google expanded its functionality, finally abandoning usage of the brand in 2012 and integrating what was needed of it into the general Google Analytics functionality with its partnered product, Google AdWords, close by its side.
AdWords
AdWords “hits” can be tracked like any other and by linking and integrating sources of origin, results of AdWords visits that involve clicking on the product offered are produced. When the browsing user then places an order and payment for the product on offer, the seller often has in hand a clear trail back to where the browsing user began their journey to the product’s purchase. The seller then has splendid information as to how effective an ongoing advertising campaign is in generating visits, browsing once in a target website and what sales result from it.
Beyond Zebra… Identify your fish
Google’s Universal Analytics is taking all this a step beyond Zebra by making the muscle of the Cloud more fully available to smaller and larger enterprise data analysis.
All an enterprise really has to do to get started is come up with a unique number for every fish in their particular sea… using, for instance, their in-house customer number as the Universal Analytics individual ID but then expanding the use of their customer numbers to include prospects about whom they hold data or experience or otherwise wish to track as an individual known to their system.
Tracking things in real life
Universal Analytics expands an existing free function of Google Analytics whereby you can submit data totally unrelated to website visits and tracking.
Online and offline information can be merged for individuals.
This expanded feature is called “Custom Dimensions and Metrics” in Universal Analytics and can include analysis of any measurable dimension (on/off, up/down, length, time, home/away, anything: size, shape, saleability) in relation to associations with another.
If one has data from a security system that is handled clumsily by the software that supports it, its data can be submitted to Google Analytics to discover any broader or narrower associations that would be of moment to the user.
Finding meaning in real life trends and correlation
Many routine measures in a facility can be analysed for associations.
Ski slopes that have lift passes that are scanned for both ski lift use and have credit available on them for drinks or meals produce such data. When compared, associations are revealed between time, type of slope skied (lift taken), type of meals taken, and type of beverages consumed. Beverage managers can do their own analyses of shifting patterns of consumption whether throughout the day for a particular day of the week or with respect to the total history of last ski season’s brand performance (by day of week, time of day… whatever is meaningful to them in some way).
Effects of an extended power outage or other loss of reputation event can be examined from the perspective of any product or user dimension over any following length of time by any day of the week, any time of day or any other unit for which knowledge of the relevant associations is meaningful.
Home page visits originating from Yellow Page listings can be treated as search engine referrals and SEO content evaluated according to visitor enquiries that brought them to an enterprise’s listing. Is it just one keyword that they are responding to? Is the enterprise paying hefty fees for Yellow Page keywords that never result in visits to the enterprise web pages?
The data from retail sales cash registers can be migrated to a Cloud examination by Universal Analytics for in-depth evaluation of a variety of associations. This includes the discovery of products that tend to be purchased at the same time but are presently on display at disparate locations around the establishment; discovery of times of day or week when demand for a product peaks and may need restocked displays according to patterns previously unknown. The relations of all that to marketing campaigns and other initiatives are revealed, on the one hand, and the effect of negative variables on the other. All the things one has always wanted to do but were beyond the limits of one’s existing software or possible only when standing on one’s head and reciting Chaucer.
Like the security system example, it can take the enterprise beyond the limits of the software that came with the product, in a situation where the data become dimensions and metrics in a larger merger of enterprise data and search for associations within it.
Consider your options now
So now is the time for an enterprise to consider what it means to have such new uses for their existing data available to them.
More and less expensive proprietary analytical software and their updates will no longer be necessary in many instances as all one needs are the data and a way to migrate it into the master database or other databases the enterprise maintains for Universal Analytics cloud analytics.
Large or small, there would seem to be something in it for almost everybody.
Experimental consultants are at the forefront and well ahead of the game in terms of understanding and planning what it means for enterprise in the context of beta transitioning to the full repertoire of Universal Analytics over the coming months.
Google Universal Analytics Examples
Google Universal Analytics could be used to see if there are correlations between class attendance & results, or seasonality & consumption to aid planning, stock management, to identify problems, or to help develop programmes.
Some specific examples:
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