Many PR measurement practitioners have the skills and tools to do this sort of research, although relatively few companies are taking advantage of it. A couple of days ago,  Eric Peterson, of Web Analytics Demystified, and SAS  released a white paper outlining some predictions about the future of using web analytics to drive business intelligence (see Eric Peterson’s blog post about the paper here).  I think the paper hits the nail on the head as to why PR (or marketing in general) isn’t using web analytics to its fullest:

“The use of advanced digital analytics tools [e.g., SAS] is, for the most part, a back-room affair performed by data junkies and “Super-Quants” that have made the leap from ‘data for data’s sake’ to ‘data for the business’s sake.’ Third-generation analytics tools are not always pretty. They don’t necessarily provide the same “Ooohhhh” factor that applications like Google Analytics and Omniture SiteCatalyst have used to convert legions of users. It turns out, however, that ‘pretty’ is over-rated, especially when compared to ‘powerful’ and ‘flexible.’”

I think that anybody who has ever used SAS (or R or SPSS or any other piece of serious statistical software) would agree that it’s not particularly pretty, and it literally takes a mathematician to get it to produce useful results. But it’s necessary for moving communications research to the next level. As it stands, most monthly or quarterly media research dashboards show a snapshot of what happened in the past– whether in the form of coverage volume, impressions, AVE, sentiment, etc. The same thing goes for the out-of-the-box reports from Google Analytics or Omniture– they show what media channels drove traffic and engagement at your website. But combining those two types of reports and understanding what types of coverage is likely to help your business reach its future goals requires advanced analytics that don’t always produce the “Ooohhhh” factor of a real-time online dashboard (at least not at first glance).

Ad-hoc and out-of-the-box reports are very useful to show how well campaigns are performing, but there is an opportunity to take this much further. Peterson’s white paper contains a figure from Competing on Analytics: The New Science of Winning (Davenport and Harris, 2007) that does a nice job showing exactly how much further digital analytics can go. The reports and research/business intelligence questions below the dotted line show the current state of web analytics, while the “true analytics capabilities” of the future are above the dotted line:

While the figure wasn’t created with PR in mind, I think it’s fairly safe to say that the vast majority of corporate communications teams are (at best) only doing the stuff on the bottom of the figure and that predictive statistical models at the top seem pretty exotic. That being said, I’m starting to see companies adopt this forward-thinking approach to digital PR measurement. These companies seem to understand that investing in research that involves relatively complicated, sometimes un-pretty, statistical analysis can deliver insight that, several years ago, seemed unimaginable to most PR professionals (being able to figure out exactly what key messages targeted at which demographics produce the most sales, for example). I think that, as the success of these companies becomes more apparent, the “digital analytics revolution” will spread through the PR world pretty quickly.