In the web publishing world, managing web content and measuring web results have tended to remain two distinct domains, with different tools (web CMS vs. web analytics packages), different skills (editorial vs. analytics), and different goals (publish vs. measure).
Increasingly, however, these two domains are converging, as website publishers and marketers seek to take action based on measurable results. Indeed, there is a strong case to be made for integrating your web CMS with your web analytics tool. You face two major opportunities in particular: First, using analytics to improve the effectiveness of your web content management. And second, using your web CMS to improve your analytic capability.
Nearly all management theory posits the centrality of measurement. In this case, web metrics should help web managers make better editorial judgments. Let’s say you’re updating a document. Don’t you want to know how popular it is? Or perhaps you’re thinking about re-sorting elements on a page. Ideally you’d have access to the metrics right there in your web CMS control panel that would inform you of those items’ popularity. Some CMS tools provide such an analytics dashboard, and similarly, many web analytics products will now overlay metrics over a representation of an actual page.
From there, though, you will likely find the need for more advanced metrics. You may become less interested in determining the most visited pages in favor of tracking the content that led to the most transactions, measuring the most popular content among registered visitors, or studying seasonal cycles of interest among your visitors.
At CMS Watch, our evaluations of the 13 major web analytics tools found that such capabilities are increasingly prevalent, but we also found that enterprises tended to lack the analytical resources to take full advantage of them.
The increasing need for advanced metrics and an integrated editorial/ marketing dashboard raises an important practical question: Where does the master data live? Analytics vendors have a very specific answer: in our tool. Most web analytics packages are trying to serve as a kind of website data warehouse, importing data from other web systems and providing broad analytics out the other side.
Web CMS vendors naturally proffer different answers. Many have built their own analytics capabilities. As you might imagine, those capabilities tend to pale in comparison to those available from web analytics vendors, but they have the advantage of tight integration with editorial functions so the web content manager can act right there on the metrics she sees, as opposed to toggling back and forth between two systems.
Other web CMS vendors are “partnering” with different analytics suppliers, but the integration challenges are not trivial. And some analytics vendors, like Omniture, are famous for offering APIs to ingest data for other systems while remaining quite tight about sharing data with other applications, including a web CMS.
These technical details can seem tedious, but they have important implications for web operations. Will you rely on your web analytics specialist to develop and distribute suitable reports to web authors? Or do you train your editorial managers or power contributors in how to use the web analytics system and regularly interpret the results? Will you end up with your web CMS and your web analytics packages dishing up two different sets of reports? The choices you make could have significant financial and operational consequences.
Analyzing the CMS
Thus far, I’ve been talking about humans improving editorial judgments when informed by good analytics. Clearly that’s essential. But since we’re talking about data, let’s also examine ways to make automated use of analytics within web pages.
The biggest trend here is to automate the elevation of most popular or most emailed articles and links. The more people visit a page, the more that link rises on the list. This capability has been present since the early days of the web, but was mastered by sites like Slashdot. Today it is increasingly prevalent as one more approach to socializing web publishing by having content consumers—and not just content producers—set priorities.
At a technical level, having an automated “most popular” list is not too complicated. It requires your CMS to tap reports developed by your analytics subsystem at some regular interval and to generate a list of items accordingly.
Popularity lists have actually proven to be a bit controversial. They tend to create feedback loops that multiply the popularity of certain links and, in the extreme, create a winner-take-all phenomenon. That might be fine for news sites with rapidly changing content and fickle readers, but is it suitable for your website? Perhaps the distortions really don’t matter if people are getting what they want. Proof, if any were needed, that we are herd animals after all.