Around the middle of each year, a survey is conducted into the state of web analytics by training and publication group Econsultancy and web analytics consulting firm Lynchpin. Together they've been running the survey each year for the last four years, tracking the changes in the web analytics industry from year to year. Their survey offers an opportunity to watch the development of the field of web analytics in general.
Multiple productsWhen looking at the technological aspects of web analytics, the survey found that most companies use more than one web analytics package and that Google Analytics is becoming ubiquitous. Eighty-seven percent of those surveyed use Google Analytics, even though half of them also have an enterprise solution such as Omniture or Webtrends.
Stephane Hamel is director of strategic services for web analytics consultancy Cardinal Path and a senior member of the International Web Analytics Association. In his view, people use Google Analytics even when they have other products because Google Analytics is the easiest to customize and offers the best range of ancillary skills and services.
"Even if they have a commercial product, people still go to for products which are easy to use and where resources are available," he says. "Google Analytics (GA) is easier than other products for instant customization and segmentation, even if it is less accurate. In addition, there is now an ecosystem of GA skills and products."
In my own experience, the easy availability of the Google Analytics API is a significant factor in the development of an ecosystem of products and services based on Google Analytics. As a result, Google Analytics can be integrated into a wider range of other systems than any other web analytics product.
Reconciliation and data integrationData integration is the major problem facing the web analytics industry at the moment. As management and other branches of the organization become more web analytics aware, they are starting to ask questions of web analytics relating to their own spheres of activity. This trend is enhanced as web technology permeates a wider range of business processes and thus gives rise to a wider range of measurable activities. The most obvious example at the moment is measurement of social media and mobile. While we all know about the importance of mobile, few companies pay any attention to it. While mobile now forms at least 10 percent of traffic or more (peaking at 25 percent in India), only 20 percent of companies are measuring mobile traffic. Social media cannot be reliably measured by most web analytics systems at all. As a result, the social media measurement field is populated by an emergent ecosystem of startups. This inevitably leads to difficulties integrating data into existing analytics systems. Furthermore, we can anticipate a period of consolidation as the market matures. This places some degree of risk on the choice of product used to measure social media and other emerging areas such as media streaming.
This risk highlights another key issue confronting web analysts. Changing analytics products or adding new ones is a major challenge with current technology. There is a complete absence of technology standards equivalent to what we find in other web fields. There is no web analytics equivalent of HTML. Unlike other branches of web technology, there is no XML dialect for web analytics, which could serve to standardize data formats. As a result, shifting from one web analytics package to another while retaining the data is almost impossible.
For the same reason, exchanging data between web analytics packages or integrating data from multiple sources is almost impossible. Reconciliation (the integration of data from differing analytics sources) is currently the major challenge facing web analysts in their day-to-day jobs. The survey found that most data integration is done by hand. My own experience is that I spend much more time working in Excel, cross-referencing data from multiple sources, than I spend looking at dashboards in individual packages. The survey shows that many of us are in this position.
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"Exchanging data between web analytics packages or integrating data from multiple sources is almost impossible". I totally agree. That's why over at Bime HQ, we decided to change this. Today we launched the 'QueryBlender', a new feature in Bime (a SaaS analytics tool that you can use on top of your existing data storage investments like Google Analytics, Google spreadsheets and Excel) which allows you to mix data on the fly. That means you don't need to move your data around with ETL, and you don't need to federate everything in a data warehouse. You simply query your different systems in the pivot table and join everything on the fly.
I think this is going to be a huge advantage for anyone who analyzes data, as you said, the major challenge facing web analysts in their day-to-day jobs is the integration of data from differing analytics sources. Well now Bime can save you that time and effort you are spending working in Excel, cross-referencing data from multiple sources. To get a better idea of how it works, I'd invite you to watch a short screencast of the QB in action: http://vimeo.com/28939854.
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